>>Welcome to the customer. Obsession begins with data session. Uh, thank you for, for attending. Um, at Cloudera, we believe that a custom session begins with, uh, with, with data. Um, and, uh, you know, financial services is Cloudera is largest industry vertical. We have approximately 425 global financial services customers, uh, which consists of 82 out of a hundred of the largest global banks of which we have 27 that are globally systemic banks, uh, four out of the five, uh, top stock exchanges, eight out of the 10 top wealth management firms and all four of the top credit card networks. Uh, so as you can see most financial services institutions utilize Cloudera for data analytics and machine learning. Uh, we also have over 20 central banks and it doesn't or so financial regulators. So it's an incredible footprint, which glimpse Cloudera, lots of insight into the many innovations that our customers are coming in up >>With >>Customers have grown more independent and demanding. Uh, they want the ability to perform many functions on their own and, uh, be able to do it. Uh, he do them on their mobile devices, uh, in a recent Accenture study, more than 50% of customers, uh, are focused on, uh, improving their customer experience through more personalized, uh, offers in advice. The study found that 75% of people are actually willing to share their data for better personalized offers and more efficient and intuitive of services >>Together. And >>A better understanding of your customers use all the data available to develop a complete view of your customer and, uh, and better serve them. Uh, this also breaks down, uh, costly silos, uh, shares data in, in accordance with privacy laws and assists with regulatory adherence. So different and organizations are going to be at different points in their data analytics and AI journey. Uh, there are several degrees of streaming and batch data, both structured and unstructured. Uh, you need a platform that can handle both, uh, with common, with a common governance layer, um, near real time and real real-time sources help make data more relevant. So if you look at this graphic, looking at it from left to right, uh, normal streaming and batch data comes from core banking and, uh, and lending operations data in pretty much a structured format as financial institutions start to evolve. >>Uh, they start to ingest near real-time streaming that comes not only from customers, but also from, from newsfeeds for example, and they start to capture more behavioral data that they can use to evolve their models, uh, and customer experience. Uh, ultimately they start to ingest more real-time streaming data, not only, um, standard, uh, sources like market and transaction data, but also alternative sources such as social media and connected sources, such as wearable devices, uh, giving them more, more data, better data, uh, to extract intelligence and drive personalized actions based on data in real time at the right time, um, and use machine learning and AI, uh, to drive anomaly detection and protect and predict, uh, present potential outcomes. >>So this >>Is another way to look at it. Um, this slide shows the progression of the big data journey as it relates to a customer experience example, um, the dark blue represents, um, visibility or understanding your customer. So we have a data warehouse and are starting to develop some analytics, uh, to know your customer and start to provide a better customer 360 experience. Uh, the medium blue area, uh, is, uh, customer centric or where we learn, uh, the customer's behavior. Uh, at this point we're improving our analytics, uh, gathering more customer centric information to perform, uh, some more exploratory, uh, data sciences. And we can start to do things like cross sell or upsell based on the customer's behavior, which should improve, uh, customer retention. The light blue area is, uh, is proactive customer inter interactions or where we now have the ability, uh, to predict customers needs and wants and improve our interaction with the customer, uh, using applied machine learning and, and AI, uh, clap the Cloudera data platform. >>Um, you know, business use cases require enabling, uh, the end-to-end journey, which we referred to as the data life cycle, uh, what the data life cycle, what is the data life cycle that our customers want to take their data through to enable the end-to-end data journey. If you ask our customers, they want different types of analytics, uh, for their diverse user bases to, to help them implement their, their, their use cases while managed by a centralized security and governance later layer. Uh, in other words, um, the data life cycle to them provides multifunction analytics, uh, at each stage within the data journey, uh, that, uh, integrated and centralized, uh, security, uh, and governance, for example, uh, enterprise data consists of real-time and transactional type type data. Examples include, uh, clickstream data, web logs, um, machine generated, data chatbots, um, call center interactions, uh, transactions, uh, within legacy applications, market data, et cetera. >>We need to manage, uh, that data life cycle, uh, to provide real enterprise data insights, uh, for use cases around enhance them personalized customer experience, um, customer journey analytics, next best action, uh, sentiment and churn analytics market, uh, campaign optimization, uh, mortgage, uh, processing optimization and so on. Um, we bring a diverse set of data then, um, and then enrich it with other data about our customers and products, uh, provide reports and dashboards such as customer 360 and use predictions from machine learning models to provide, uh, business decisions and, and offers of, uh, different products and services to customers and maintain customer satisfaction, um, by using, um, sentiment and turn analytics. These examples show that, um, the whole data life cycle is involved, um, and, uh, is in continuous fashion in order to meet these types of use cases, uh, using a single cohesive platform that can be, uh, that can be served by CDP, uh, the data, the Cloudera data platform. >>Okay. Let's, uh, let's talk about, uh, some of the experiences, uh, from our customers. Uh, first we'll talk about Bunco, something there. Um, Banco Santander is a major global bank headquartered in Spain, uh, with, uh, major operations and subsidiaries all over Europe and north and, and south America. Uh, one of its subsidiary, something there UK wanted to revolutionize the customer experience with the use of real-time data and, uh, in app analytics, uh, for mobile users, however, like many financial institutions send them there had a, he had a, had a large number of legacy data warehouses spread across many business use, and it's within consistent data and different ways of calculating the same metrics, uh, leading to different results. As a result, the company couldn't get the comprehensive customer insights it needed. And, uh, and business staff often worked on multiple versions of the truth. Sometimes there worked with Cloudera to improve a single data platform that could support all its workloads, including self-service analytics, uh, operational analytics and data science processes in processing 10 million transactions, daily or 30,000 transactions per second at peak times. >>And, uh, bringing together really, uh, nearly two to two petabytes of data. The platform provides unprecedented, uh, customer insight and business value across the organization, uh, over 80 cents. And Dera has realized impressive, uh, benefits spanning, uh, new revenues, cost savings and risk reductions, including creating analytics for, for corporate customers with near real-time shopping behavior, um, and, and helping identify 7,000 new corporate, uh, customer prospects, uh, reducing capital expenditures by, uh, 3.2 million annually and decreasing operating expenses by, uh, 650,000, um, enabling marketing to realize, uh, 2.4 million in annual savings on, on cash back on commercial transactions, um, and protecting 3.7 million customers from financial crime impacts through 95, new proactive control alerts, improving risk and capital calculations to reduce the amount of money. It must set aside, uh, as part of a, as part of risk mandates. Uh, for example, in one instance, the risk team was able to release a $5.2 million that it had withheld for non-performing credit card loans by properly identifying healthy accounts miscategorized as high risk next, uh, let's uh, talk about, uh, Rabo bank. >>Um, Rabobank is one of the largest banks in the Netherlands, uh, with approximately 8.3 million customers. Uh, it was founded by farmers in the late 19th century and specializes in agricultural financing and sustainability oriented banking, uh, in order to help its customers become more self-sufficient and, uh, improve their financial situations such as debt settlement, uh, rebel bank needed to access, uh, to a varied mix of high quality, accurate, and timely customer data, the talent, uh, to provide this insight, however, was the ability to execute sophisticated and timely data analytics at scale Rabobank was also faced with the challenge of, uh, shortening time to market. Uh, it needed easier access to customer data sets to ensure that they were using and receiving the right financial support at the right time with, with, uh, data quality and speed of processing. Um, highlighted as two vital areas of improvement. Robert bank was looking to incorporate, um, or create new data in an environment that would not only allow the organization to create a centralized repository of high quality data, but also allow them to stream and, uh, conduct data analytics on the fly, uh, to create actionable insights and deliver a strong customer service experience. >>Rabobank >>Leverage Cloudera due to its ability to cope with heavy pressures on data processing and its capability of ingesting large quantities of real-time streaming data. They were able to quickly create a new data lake that allowed for faster queries of both historical and real-time data to analyze customer loan repayment patterns, uh, to up to the minute transaction records, um, Robert bank and, and its customers could now immediately access, uh, the valuable data needed to help them understand, um, the status of their financial situation, this enabled, uh, rebel bank to spot financial disasters before they happened, enabling them to gain deep and timely insights into which customers were at risk of defaulting on loans. Um, having established the foundation of a modern data architecture Rabobank is now able to run sophisticated machine learning algorithms and, uh, financial models, uh, to help customers manage, um, financial, uh, obligations, um, including, uh, loan repayments, and are able to generate accurate, uh, current liquidity overviews, uh, no next, uh, let's, uh, speak about, um, uh, OVO. >>Uh, so OVO is the leading digital payment rewards and financial services platform in Indonesia, and is present in 115 million devices across the company across the country. Excuse me. Um, as the volume of, of products, uh, within Obos ecosystem increases, the ability to ensure marketing effectiveness is critical to avoid unnecessary waste of time and resources, unlike competitors, uh, banks, w which use traditional mass marketing, uh, to reach customers over, oh, decided to embark on a, on a bold new approach to connect with customers via a ultra personalized marketing, uh, using the stack, the team at OVO were able to implement a change point detection algorithm, uh, to discover customer life stage changes. This allowed OVO, uh, to, uh, build a segmentation model of one, uh, the contextual offer engine Bill's recommendation algorithms on top of the product, uh, including collaborative and context-based filters, uh, to detect changes in consumer consumption >>Patterns. >>As a result, OVO has achieved a 15% increase in revenue, thanks to this, to this project, um, significant time savings through automation and eliminating the chance of human error and have reduced engineers workloads by, by 30%. Uh, next let's talk about, uh, bank Bri, uh, bank Bri is one of the largest and oldest, uh, banks in Indonesia, um, engaging in, in general banking services, uh, for its customers. Uh, they are headquartered in, in Jakarta Indonesia, uh, BR is a well-known, uh, for its, uh, focused on financing initiative initiatives and serves over 75 million customers through its more than 11,000 offices and rural outposts, >>Um, Bri >>Needed to gain better understanding of their customers and market, uh, to improve the efficiency of its operations, uh, reduce losses from non-performing loans and address the rising concern around data security from regulators and consumers, uh, through enhanced fraud detection. This would require the ability to analyze vast amounts of, uh, historical financial data and use those insights, uh, to enhance operations and, uh, deliver better service. Um, Bri used Cloudera's enterprise data platform to build an agile and reliable, uh, predictive augmented intelligence solution. Uh, Bri was now able to analyze 124 years worth of historical financial data and use those insights to enhance its operations and deliver better services. Um, they were able to, uh, enhance their credit scoring system, um, the solution analyzes customer transaction data, and predicts the probability of a customer defaulting on, on payments. Um, the following month, it also alerts Bri's loan officers, um, to at-risk customers, prompting them to take the necessary action to reduce the likelihood of a Vanette profit lost. Uh, this resulted in improved credits in, in improved, uh, credit scoring system, uh, that cut down the approval of micro financing loans, uh, from two weeks to two days to two minutes and, uh, enhanced, uh, fraud detector. >>All right. Uh, this example shows a tabular representation, uh, the evolution of a customer retention use case, um, the evolution of data and analytics, uh, journey that, uh, that for that use case, uh, from aware, uh, text flirtation, uh, to optimization, to being transformative, uh, with every level, uh, data sources increase. And, uh, for the most part, uh, are, are less, less standard, more dynamic and less structured, but always adding more value, more insights into the customer, uh, allowing us to continuously improve our analytics, increase the velocity of the data we ingest, uh, from, from batch, uh, to, uh, near real time, uh, to real-time streaming, uh, the volume of data we ingest continually increases and we progress, uh, the value of the data on our customers, uh, is continuously improving, allowing us to interact more proactively and more efficiently. And, and with that, um, I would, uh, you know, ask you to consider an assess if you are using all the, uh, the data available to understand, uh, and service your customers, and to learn more about, about this, um, you know, visit cloudera.com and schedule a meeting with Cloudera to learn more. And with that, thank you for your time. And thank you for listening.

(upbeat music) >> Hi, I'm Joe Rodriguez, Managing Director of Financial Services at Cloudera. Welcome to the Fight Fraud with Data session. At Cloudera we believe that fighting fraud begins with data. So financial services is Cloudera's largest industry vertical. We have approximately 425 global financial services customers, which consists of 82 out of a hundred of the largest global banks of which we have 27 that are globally systemic banks. Four out of the five top stock exchanges, eight out of the top 10 wealth management firms and all four of the top credit card networks. So as you can see, most financial services institutions utilize Cloudera for data analytics and machine learning. We also have over 20 central banks and a dozen or so financial regulators. So it's an incredible footprint which gives Cloudera lots of insight into the many innovations that our customers are coming up with. Criminals can steal thousands of dollars before a fraudulent transaction is detected. So the cost to purchase your account data is well worth the price to fraudsters. According to Experian, credit and a debit card account information sells on the dark web for a mere $5 with the CVV number and up to $110 if it comes with all the bank information, including your name, social security number, date of birth, complete account numbers, and other personal data. Our customers have several key data and analytics challenges when it comes to fighting financial crime. The volume of data that they need to deal with is huge and growing exponentially. All this data needs to be evaluated in real time. There are new sources of streaming data that need to be integrated with existing legacy data sources. This includes biometrics data and enhanced authentication video surveillance, call center data, and of course all that needs to be integrated with existing legacy data sources. There is an analytics Arms Race between the banks and the criminals, and the criminal networks never stop innovating. They also have to deal with disjointed security and governance. Security and governance policies are often set per data source or application requiring redundant work across workloads. And they have to deal with siloed environments. The specialized nature of platforms and people results in disparate data sources and data management processes. This duplicates efforts and divides the business risk and crime teams, limiting collaboration opportunities between them. CDP enhances financial crime solutions to be holistic by eliminating data gaps between siloed solutions, with an enterprise data approach, advanced data analytics and machine learning. By deploying an enterprise wide data platform, you reduce siloed divisions between business risk and crime teams and enable better collaboration through industrialized machine learning, you tighten up the loop between detection and new fraud patterns. Cloudera provides the data platform on which a best of breed applications can run and leverage integrated machine learning. Cloudera stands rather than replaces your existing fraud modeling applications. So Oracle, SAS, Actimize, to name a few, integrate with an enterprise data hub to scale the data, increase speed and flexibility and improve efficacy of your entire fraud system. It also centralizes the fraud workload on data that can be used for other use cases in applications like Enhanced KYC and Customer 360 for example. I just wanted to highlight a couple of our partners in financial crime prevention, Simudyne and Quantexa. So Simudyne provides fraud simulation using agent-based modeling machine learning techniques to generate synthetic transaction data. This data simulates potential fraud scenarios in a cost-effective GDPR-compliant virtual environment to significantly improve financial crime detection systems. Simudyne identifies future fraud topologies for millions of simulations that can be used to dynamically train new machine learning algorithms for enhanced identification. And Quantexa connects the dots within your data using dynamic entity resolution, and advanced network analytics to create context around your customers. This enables you to see the bigger picture and automatically assesses potential criminal behavior. Now let's go over some of our customers and how they're using Cloudera. First, we'll talk about United Overseas Bank or UOB. UOB is a leading full service bank in Asia with a network of more than 500 offices in 19 countries and territories, in Asia Pacific, Western Europe and North America. UOB built a modern data platform on Cloudera that gives it the flexibility and speed to develop new AI and machine learning solutions and to create a data-driven enterprise. UOB set up it's big data analytics center in 2017. It was Singapore's first centralized big data unit within a bank to deepen the bank's data analytic capabilities and to use data insights to enhance the bank's performance. Essential to this work was implementing a platform that could cost efficiently bring together data from dozens of separate systems and incorporate a range of unstructured data, including voice and text. Using Cloudera CDP and machine learning, UOB gained a richer understanding of its customer preferences to help make their banking experience simpler, safer, and more reliable. Working with Cloudera, UOB has a big data platform that gives business staff and data scientists, faster access to relevant and quality data for self-service analytics, machine learning and emerging artificial intelligence solutions. With new self-service analytics and machine learning driven insights, UOB has realized improvements in digital banking, asset management, compliance, AML, and more. Advanced AML detection capabilities, help analysts detect suspicious transactions either based on hidden relationships of shell companies and high risk individuals with Cloudera and machine learning technologies, UOB was able to enhance AML detection and reduce the time to identify new links from months to three weeks. Next, let's speak about MasterCard. So MasterCard's principle business is to process payments between banks and merchants and the credit issuing banks and credit unions of the purchasers who use the MasterCard brand debit and credit cards to make purchases. MasterCard chose Cloudera Enterprise for fraud detection and to optimize their DW infrastructure, delivering deep insights and best practices and big data security and compliance. Next, let's speak about Bank Rakyat in Indonesia or BRI. BRI is one of the largest and oldest banks in Indonesia and engages in the provision of general banking services. It's headquartered in Jakarta, Indonesia. BRI is well-known for its focus on microfinancing initiatives and serves over 75 million customers through its more than 11,000 offices and rural service outposts. BRI required better insight to understand customer activity and identify fraudulent transactions. The bank needed a solid foundation that allowed it to leverage the power of advanced analytics, artificial intelligence, and machine learning to gain better understanding of customers and the market. BRI used Cloudera Enterprise data platform to build an agile and reliable, predictive augmented intelligence solution to enhance its credit scoring system. And to address the rising concern around data security from regulators and customers, BRI developed a real-time fraud detection service powered by Cloudera and Kafka, BRI's data scientists developed a machine learning model for fraud detection by creating a behavioral scoring model based on customer savings, loan transactions, deposits, payroll and other financial real-time data. This led to improvements in its fraud detection and credit scoring capabilities, as well as the development of a new digital microfinancing product. With the enablement of real-time fraud detection, BRI was able to reduce the rate of fraud by 40%. It improved relationship manager productivity by two and a half fold. It improved the credit scoring system to cut down on micro-financing loan processing times from two weeks to two days to now two minutes. So fraud prevention is a good area to start with data focus if you haven't already. It offers a quick return on investment and it's a focused area that's not too entrenched across the company. To learn more about fraud prevention, go to www.cloudera.com, and you should schedule a meeting with Cloudera to learn even more. And with that, thank you for listening and thank you for your time. (upbeat music)

>>Uh, hi, I'm Joe Rodriguez, managing director of financial services at Cloudera. Uh, welcome to the fight fraud with a data session, uh, at Cloudera, we believe that fighting fraud with, uh, uh, begins with data. Um, so financial services is Cloudera's largest industry vertical. We have approximately 425 global financial services customers, uh, which consists of 82 out of a hundred of the largest global banks of which we have 27 that are globally systemic banks, uh, four out of the five top, uh, stock exchanges, uh, eight out of the top 10 wealth management firms and all four of the top credit card networks. So as you can see most financial services institutions, uh, utilize Cloudera for data analytics and machine learning, uh, we also have over 20 central banks and a dozen or so financial regulators. So it's an incredible footprint which gives Cloudera lots of insight into the many innovations, uh, that our customers are coming up with. Uh, criminals can steal thousands of dollars before a fraudulent transaction is detected. So the cost of, uh, to purchase a, your account data is well worth the price to fraudsters. Uh, according to Experian credit and debit card account information sells on the dark web for a mere $5 with the CVV number and up to $110. If it comes with all the bank information, including your name, social security number, date of birth, uh, complete account numbers and, and other personal data. >>Um, our customers have several key data and analytics challenges when it comes to fighting financial crime. The volume of data that they need to deal with is, is huge and growing exponentially. Uh, all this data needs to be evaluated in real time. Uh, there is, uh, there are new sources of, of streaming data that need to be integrated with existing, uh, legacy data sources. This includes, um, biometrics data and enhanced, uh, authentication, uh, video surveillance call center data. And of course all that needs to be integrated with existing legacy data sources. Um, there is an analytics arms race between the banks and the criminals and the criminal networks never stop innovating. They also we'll have to deal with, uh, disjointed security and governance, security and governance policies are often set per data source, uh, or application requiring redundant work, work across workloads. And, and they have to deal with siloed environments, um, the specialized nature of platforms and people results in disparate data sources and data management processes, uh, this duplicates efforts and, uh, divides the, the business risk and crime teams, limiting collaboration opportunities between CDP enhances financial crime solutions, uh, to be holistic by eliminating data gaps between siloed solutions with, uh, an enterprise data approach, uh, advanced, uh, data analytics and machine learning, uh, by deploying an enterprise wide data platform, you reduce siloed divisions between business risk and crime teams and enable better collaboration through industrialized machine learning. >>Uh, you tighten up the loop between, uh, detection and new fraud patterns. Cloudera provides the data platform on which a best of breed applications can run and leverage integrated machine learning cloud Derrick stands rather than replaces your existing fraud modeling applications. So Oracle SAS Actimize to, to name a few, uh, integrate with an enterprise data hub to scale the data increased speed and flexibility and improve efficacy of your entire fraud system. It also centralizes the fraud workload on data that can be used for other use cases in applications like enhanced KYC and a customer 360 4 example. >>I just, I wanted to highlight a couple of our partners in financial crime prevention, uh, semi dine, and Quintex, uh, uh, so send me nine provides fraud simulation using agent-based modeling, uh, machine learning techniques, uh, to generate synthetic transaction data. This data simulates potential fraud scenarios in a cost-effective, uh, GDPR compliant, virtual environment, significantly improved financial crime detection systems, semi dine identifies future fraud topologies, uh, from millions of, of simulations that can be used to dynamically train, uh, new machine learning algorithms for enhanced fraud identification and context, um, uh, connects the dots within your data, using dynamic entity resolution, and advanced network analytics to create context around your customers. Um, this enables you to see the bigger picture and automatically assesses potential criminal beads behavior. >>Now let's go some of our, uh, customers, uh, and how they're using cloud caldera. Uh, first we'll talk about, uh, United overseas bank, or you will be, um, you'll be, is a leading full service bank in, uh, in Asia. It, uh, with, uh, a network of more than 500 offices in, in 19 countries and territories in Asia, Pacific, Western Europe and north America UA, um, UOB built a modern data platform on Cloudera that gives it the flexibility and speed to develop new AI and machine learning solutions and to create a data-driven enterprise. Um, you'll be set up, uh, set up it's big data analytics center in 2017. Uh, it was Singapore's first centralized big data unit, uh, within a bank to deepen the bank's data analytic capabilities and to use data insights to enhance, uh, the banks, uh, uh, performance essential to this work was implementing a platform that could cost efficiently, bring together data from dozens of separate systems and incorporate a range of unstructured data, including, uh, voice and text, um, using Cloudera CDP and machine learning. >>UOB gained a richer understanding of its customer preferences, uh, to help make their, their banking experience simpler, safer, and more reliable. Working with Cloudera UOB has a big data platform that gives business staff and data scientists faster access to relevant and quality data for, for self-service analytics, machine learning and, uh, emerging artificial intelligence solutions. Um, with new self-service analytics and machine learning driven insights, you'll be, uh, has realized improvements in, in digital banking, asset management, compliance, AML, and more, uh, advanced AML detection capabilities, help analysts detect suspicious transactions either based on hidden relationships of shell companies and, uh, high risk individuals, uh, with, uh, Cloudera and machine learning, uh, technologies. You you'll be, uh, was able to enhance AML detection and reduce the time to identify new links from months 2, 3, 3 weeks. >>Excellent mass let's speak about MasterCard. So MasterCard's principle businesses to process payments between banks and merchants and the credit issuing banks and credit unions of the purchasers who use the MasterCard brand debit and credit cards to make purchases MasterCard chose Cloudera enterprise for fraud detection, and to optimize their DW infrastructure, delivering deepens insights and best practices in big data security and compliance. Uh, next let's speak about, uh, bank Rakka yet, uh, in Indonesia or Bri. Um, it, VRI is one of the largest and oldest banks in Indonesia and engages in the provision of general banking services. Uh, it's headquartered in Jakarta Indonesia. Uh, Bri is well known for its focus on financing initiatives and serves over 75 million customers through it's more than 11,000 offices and rural service outposts. Uh, Bri required better insight to understand customer activity and identify fraudulent transactions. Uh, the bank needed a solid foundation that allowed it to leverage the power of advanced analytics, artificial intelligence, and machine learning to gain better understanding of customers and the market. >>Uh, Bri used, uh, Cloudera enterprise data platform to build an agile and reliable, predictive augmented intelligence solution, uh, to enhance its credit scoring system and to address the rising concern around data security from regulators, uh, and customers, uh, Bri developed a real-time fraud detection service, uh, powered by Cloudera and Kafka. Uh, Bri's data scientists developed a machine learning model for fraud detection by creating a behavioral scoring model based on customer savings, uh, loan transactions, deposits, payroll and other financial, um, uh, real-time time data. Uh, this led to improvements in its fraud detection and credit scoring capabilities, as well as the development of a, of a new digital microfinancing product, uh, with the enablement of real-time fraud detection, VRI was able to reduce the rate of fraud by 40%. Uh, it improved, uh, relationship manager productivity by two and a half fold. Uh, it improved the credit score scoring system to cut down on micro-financing loan processing times from two weeks to two days to now two minutes. So fraud prevention is a good area to start with a data focus. If you haven't already, it offers a quick return on investment, uh, and it's a focused area. That's not too entrenched across the company, uh, to learn more about fraud prevention, uh, go to kroger.com and to schedule, and you should schedule a meeting with Cloudera, uh, to learn even more. Uh, and with that, thank you for listening and thank you for your time. >>Welcome to the customer. Obsession begins with data session. Uh, thank you for, for attending. Um, at Cloudera, we believe that a custom session begins with, uh, with, with data, um, and, uh, you know, financial services is Cloudera is largest industry vertical. We have approximately 425 global financial services customers, uh, which consists of 82 out of a hundred of the largest global banks of which we have 27 that are globally systemic banks, uh, four out of the five top stock exchanges, eight out of the 10 top wealth management firms and all four of the top credit card networks. Uh, so as you can see most financial services institutions utilize Cloudera for data analytics and machine learning. Uh, we also have over 20 central banks and it doesn't or so financial regulators. So it's an incredible footprint, which glimpse Cloudera, lots of insight into the many innovations that our customers are coming up with. >>Customers have grown more independent and demanding. Uh, they want the ability to perform many functions on their own and, uh, be able to do it. Uh, he do them on their mobile devices, uh, in a recent Accenture study, more than 50% of customers, uh, are focused on, uh, improving their customer experience through more personalized offers and advice. The study found that 75% of people are actually willing to share their data for better personalized offers and more efficient and intuitive services to get it better, better understanding of your customers, use all the data available to develop a complete view of your customer and, uh, and better serve them. Uh, this also breaks down, uh, costly silos, uh, shares data in, in accordance with privacy laws and assists with regulatory advice. It's so different organizations are going to be at different points in their data analytics and AI journey. >>Uh, there are several degrees of streaming and batch data, both structured and unstructured. Uh, you need a platform that can handle both, uh, with common, with a common governance layer, um, near real time. And, uh, real-time sources help make data more relevant. So if you look at this graphic, looking at it from left to right, uh, normal streaming and batch data comes from core banking and, uh, and lending operations data in pretty much a structured format as financial institutions start to evolve. Uh, they start to ingest near real-time streaming data that comes not only from customers, but also from, from newsfeeds for example, and they start to capture more behavioral data that they can use to evolve their models, uh, and customer experience. Uh, ultimately they start to ingest more real time streaming data, not only, um, standard, uh, sources like market and transaction data, but also alternative sources such as social media and connected sources, such as wearable devices, uh, giving them more, more data, better data, uh, to extract intelligence and drive personalized actions based on data in real time at the right time, um, and use machine learning and AI, uh, to drive anomaly detection and protect and predict, uh, present potential outcomes. >>So this is another way to look at it. Um, this slide shows the progression of the big data journey as it relates to a customer experience example, um, the dark blue represents, um, visibility or understanding your customer. So we have a data warehouse and are starting to develop some analytics, uh, to know your customer and start to provide a better customer 360 experience. Uh, the medium blue area, uh, is a customer centric or where we learn, uh, the customer's behavior. Uh, at this point we're improving our analytics, uh, gathering more customer centric information to perform, uh, some more exploratory, uh, data sciences. And we can start to do things like cross sell or upsell based on the customer's behavior, which should improve, uh, customer retention. The light blue area is, uh, is proactive customer inter interactions, or where we now have the ability, uh, to predict customers needs and wants and improve our interaction with the customer, uh, using applied machine learning and, and AI, uh, the Cloudera data platform, um, you know, business use cases require enabling, uh, the end-to-end journey, which we referred to as the data life cycle, uh, what the data life cycle, what is the data life cycle that our customers want, uh, to take their data through, to enable the end to end data journey. >>If you ask our customers, they want different types of analytics, uh, for their diverse user bases to help them implement their, their, their use cases while managed by a centralized security and governance later layer. Uh, in other words, um, the data life cycle to them provides multifunction analytics, uh, at each stage, uh, within the data journey, uh, that, uh, integrated and centralized, uh, security, uh, and governance, for example, uh, enterprise data consists of real time and transactional type type data. Examples include, uh, click stream data, web logs, um, machine generated, data chat bots, um, call center interactions, uh, transactions, uh, within legacy applications, market data, et cetera. We need to manage, uh, that data life cycle, uh, to provide real enterprise data insights, uh, for use cases around enhanced them, personalized customer experience, um, customer journey analytics next best action, uh, sentiment and churn analytics market, uh, campaign optimization, uh, mortgage, uh, processing optimization and so on. >>Um, we bring a diverse set of data then, um, and then enrich it with other data about our customers and products, uh, provide reports and dashboards such as customer 360 and use predictions from machine models to provide, uh, business decisions and, and offers of, uh, different products and services to customers and maintain customer satisfaction, um, by using, um, sentiment and churn analytics. These examples show that, um, the whole data life cycle is involved, um, and, uh, is in continuous fashion in order to meet these types of use cases, uh, using a single cohesive platform that can be, uh, that can be served by CDP, uh, the data, the Cloudera data platform. >>Okay. Uh, let's talk about, uh, some of the experiences, uh, from our customers. Uh, first we'll talk about Bunco suntan there. Um, is a major global bank headquartered in Spain, uh, with, uh, major operations and subsidiaries all over Europe and north and, and south America. Uh, one of its subsidiaries, something there UK wanted to revolutionize the customer experience with the use of real time data and, uh, in app analytics, uh, for mobile users, however, like many financial institutions send them there had a, he had a, had a large number of legacy data warehouses spread across many business use, and it's within consistent data and different ways of calculating the same metrics, uh, leading to different results. As a result, the company couldn't get the comprehensive customer insights it needed. And, uh, and business staff often worked on multiple versions of the truth. Sometime there worked with Cloudera to improve a single data platform that could support all its workloads, including self-service analytics, uh, operational analytics and data science processes, processing processing, 10 million transactions daily or 30,000 transactions per second at peak times. >>And, uh, bringing together really, uh, nearly two to two petabytes of data. The platform provides unprecedented, uh, customer insight and business value across the organization, uh, over 80 cents. And there has realized impressive, uh, benefits spanning, uh, new revenues, cost savings and risk reductions, including creating analytics for, for corporate customers with near real-time shopping behavior, um, and, and helping identify 7,000 new corporate, uh, customer prospects, uh, reducing capital expenditures by, uh, 3.2 million annually and decreasing operating expenses by, uh, 650,000, um, enabling marketing to realize, uh, 2.4 million in annual savings on, on cash, on commercial transactions, um, and protecting 3.7 million customers from financial crime impacts through 95, new proactive control alerts, improving risk and capital calculations to reduce the amount of money. It must set aside, uh, as part of a, as part of risk mandates. Uh, for example, in one instance, the risk team was able to release a $5.2 million that it had withheld for non-performing credit card loans by properly identifying healthy accounts miscategorized as high risk next, uh, let's uh, talk about, uh, Rabobank. >>Um, Rabobank is one of the largest banks in the Netherlands, uh, with approximately 8.3 million customers. Uh, it was founded by farmers in the late 19th century and specializes in agricultural financing and sustainability oriented banking, uh, in order to help its customers become more self-sufficient and, uh, improve their financial situations such as debt settlement, uh, rebel bank needed to access, uh, to a varied mix of high quality, accurate, and timely customer data, the talent, uh, to provide this insight, however, was the ability to execute sophisticated and timely data analytics at scale Rabobank was also faced with the challenge of, uh, shortening time to market. Uh, it needed easier access to customer data sets to ensure that they were using and receiving the right financial support at the right time with, with, uh, data quality and speed of processing. Um, highlighted as two vital areas of improvement, Rabobank was looking to incorporate, um, or create new data in an environment that would not only allow the organization to create a centralized repository of high quality data, but also allow them to stream and, uh, conduct data analytics on the fly, uh, to create actionable insights and deliver a strong customer experience bank level Cloudera due to its ability to cope with heavy pressures on data processing and its capability of ingesting large quantities of real time streaming data. >>They were able to quickly create a new data lake that allowed for faster queries of both historical and real time data to analyze customer loan repayment patterns, uh, to up to the minute transaction records, um, Robert bank and, and its customers could now immediately access, uh, the valuable data needed to help them understand, um, the status of their financial situation in this enabled, uh, rebel bank to spot financial disasters before they happened, enabling them to gain deep and timely insights into which customers were at risk of defaulting on loans. Um, having established the foundation of a modern data architecture Rabobank is now able to run sophisticated machine learning algorithms and, uh, financial models, uh, to help customers manage, um, financial, uh, obligations, um, including, uh, long repayments and are able to generate accurate, uh, current real liquidity. I refuse, uh, next, uh, let's uh, speak about, um, uh, OVO. >>Uh, so OVO is the leading digital payment rewards and financial services platform in Indonesia, and is present in 115 million devices across the company across the country. Excuse me. Um, as the volume of, of products within Obos ecosystem increases, the ability to ensure marketing effectiveness is critical to avoid unnecessary waste of time and resources, unlike competitors, uh, banks, w which use traditional mass marketing, uh, to reach customers over, oh, decided to embark on a, on a bold new approach to connect with customers via, uh, ultra personalized marketing, uh, using the Cloudera stack. The team at OVO were able to implement a change point detection algorithm, uh, to discover customer life stage changes. This allowed OVO, uh, to, uh, build a segmentation model of one, uh, the contextual offer engine Bill's recommendation algorithms on top of the product, uh, including collaborative and context-based filters, uh, to detect changes in consumer consumption patterns. >>As a result, OVO has achieved a 15% increase in revenue, thanks to this, to this project, um, significant time savings through automation and eliminating the chance of human error and have reduced engineers workloads by, by 30%. Uh, next let's talk about, uh, bank Bri, uh, bank Bri is one of the largest and oldest, uh, banks in Indonesia, um, engaging in, in general banking services, uh, for its customers. Uh, they are headquartered in, in Jakarta Indonesia, uh, PR is a well-known, uh, for its, uh, focused on micro-financing initiative initiatives and serves over 75 million customers through more than 11,000 offices and rural outposts, um, Bri needed to gain better understanding of their customers and market, uh, to improve the efficiency of its operations, uh, reduce losses from non-performing loans and address the rising concern around data security from regulators and consumers, uh, through enhanced fraud detection. This would require the ability to analyze the vast amounts of, uh, historical financial data and use those insights, uh, to enhance operations and, uh, deliver better service. >>Um, Bri used Cloudera's enterprise data platform to build an agile and reliable, uh, predictive augmented intelligence solution. Uh, Bri was now able to analyze 124 years worth of historical financial data and use those insights to enhance its operations and deliver better services. Um, they were able to, uh, enhance their credit scoring system, um, the solution analyzes customer transaction data, and predicts the probability of a customer defaulting on, on payments. Um, the following month, it also alerts Bri's loan officers, um, to at-risk customers, prompting them to take the necessary action to reduce the likelihood of the net profit lost, uh, this resulted in improved credit, improved credit scoring system, uh, that cut down the approval of micro financing loans, uh, from two weeks to two days to, to two minutes and, uh, enhanced fraud detection. >>All right. Uh, this example shows a tabular representation, uh, the evolution of a customer retention use case, um, the evolution of data and analytics, uh, journey that, uh, that for that use case, uh, from aware, uh, text flirtation, uh, to optimization, to being transformative, uh, with every level, uh, data sources increase. And, uh, for the most part, uh, are, are less, less standard, more dynamic and less structured, but always adding more value, more insights into the customer, uh, allowing us to continuously improve our analytics, increase the velocity of the data we ingest, uh, from, from batch, uh, to, uh, near real time, uh, to real-time streaming, uh, the volume of data we ingest continually increases and we progress, uh, the value of the data on our customers, uh, is continuously improving, allowing us to interact more proactively and more efficiently. And, and with that, um, I would, uh, you know, ask you to consider and assess if you are using all the, uh, the data available to understand, uh, and service your customers, and to learn more about, about this, um, you know, visit cloudera.com and schedule a meeting with Cloudera to learn more. And with that, thank you for your time. And thank you for listening.

[Music] welcome back to red hat summit 2021 my name is dave vellante and you're watching the cube where we go out to the events and extract the signal from the noise of course virtually in this case and i'm pleased to welcome victor carumpus who is the senior vice president of digital banking at bank mandiri coming in from jakarta welcome to the cube victor great to see you hi dave great to see you and great to be invited here thank you yeah you're very welcome i i wonder if you could just give us an overview of the bank maybe talk a little bit about your strategy your customers you know what the what the focus is of your company and what your role is there okay uh maybe i'm i'll give a short overview about bang mandir itself so bang money is a state-owned enterprise owned by the government but we also public company currently we already have a very big distribution channel in so uh you know indonesia is an island country it's very huge country so we are we are representing all over indonesia from province of aceh and i'm up to profits of papua and we have about 2600 branches all over indonesia and about uh 15 000 atms all over indonesia so bangladesh itself is focused on a lot of segment customers like indonesia from the corporate side small medium enterprise and also retail banking now uh we are we are currently focused in turning ourselves to become having to have more digital capability and currently in our uh current situations actually it is very good uh about 95 percent of our transactions is already coming from the electronic channel so it's only about five percent that coming from the branches but we know that this is still a journey uh and we are building more digital capability and features and functions on our digital channels to our customer got it um okay and so your your your digital journey kind of coincides i guess in a way with your your your container uh adoption journey uh i think that started a few years ago um and so maybe you could talk a little bit about that i i mean in thinking about modernizing your application portfolio obviously containers been around forever but they weren't packaged in a way that could actually be easily you know utilized and now you're seeing people in i.t roles like yourself really leaning in maybe you could talk about some of the technology considerations that impacted that desire to actually leverage containers i think uh first it's about the scalability because with a monolithic architecture it's kind of difficult to scale up for only specific features by doing container microservices we have options to scale up in a very fast way because one of the features is auto scaling on the container architectures uh one monitor is a very focused on the transaction banking so you might say bangladesh is supporting the economy of the country because in a in any given time in bangladesh we we're running about four thousand transactions per seconds that's a huge transactions number and have having said that uh our channel like i told you already running about 95 percent of the transactions so scalability is always important for us because especially like like now is the the in indonesia is a festive month it's a ramadan month where muslim is actually doing fasting but at the same time actually there's a lot of needs and people do a lot of transactions and on this kind of festive seasons the transition can be increased up to 40 or 50 suddenly and that's kind of things always happen in bangladesh and we must be ready and we must have a scalability on demand now containerization is enabling us to do that other thing is about flexibility because on the old days actually when we want to set up a new environment it's very difficult and takes a lot of time and that's affecting the time to market our products by doing the containerizations and putting it on a ci cd continuous integration called the development plan platform we are we call devsecops platform that kind of things becoming automatic because we set up the devsecos platform and the third one is the consistency actually so by by doing the contact investigations we can put the the apis on our back-end apis in the container itself and actually it's deliverable environment and a consistent experience to our customer because for example we promise our customer that every transaction should be finished within two seconds from their mobile banking up to our hosts and back forward to their mobile banking is only two seconds so that kind of thing is driving us to move to the current technology which we're using containerization and micro services great okay so 4 000 transactions per second you can't can't do that on erc20 ethereum for all you crypto fans out there that's that's pretty high volume uh and if i understand it correctly victor your role is really to envision this digital environment and then ultimately make it happen from a technology standpoint is that correct that's product that's got it yeah so okay so you now have a number of of product lines and teams you're using the same container platform maybe you could share with our audience some of the best practices and learnings that that you've taken away on this journey so i think first of all we can reuse a lot of components by doing this containerization platform is different when we still use the monolithic platform like the application server of java application server uh by using containerization actually uh be providing like a service banking as a service so whenever we build a new channel for example the first one we built a new service for example like a fun transfer service but when we create another channel for example a corporate banking electronic channel or we create another uh let's say wealth management channel whatever we already built before can be reusable instantly by using this technology so uh if i might say that actually there is a lot of best practices coming by using this platform and my team get a lot of benefit in terms of faster development time and also they can deliver the product and service in a high quality manner minimize the number of errors as well you know there's a lot of choices out there obviously i wonder if you could share what led you to the choice of red hat and open shift okay so first of all before we choose the platform actually we also comparing ourselves with the with the fintechs and also with the big tech in indonesia as well so we see we see that actually they already start using kubernetes and uh their platform is quite stable and even they can support about 90 to 100 million of customers without any issues at all so when we see this uh we choose a lot of we learn about a lot of platform and we finally choose opencv because we think that openshift and we we already do our research openshift is quite stable and for banks like us that have for having 4500 transaction per seconds stability is number one uh availability is also number one now uh having said that after doing our research we choose openshift and we implemented openshift in our environment because we promise our customers to provide 99.95 percent uh availability can i just i'm sorry to interrupt you victor can you just repeat that you cut out a little bit so you you said you you promised your customers to deliver and then you cut out a little bit can you just repeat what you just said there okay so we're giving a promise to our to our customer providing a 99.95 availability so this is the starting point of our channel sure in the efficiency we have efficient also to providing four nines which is 99.99 but i mean the starting point is 99.95 and because we have that the demand that requirement that's one of the reason we choose the openshift and red hat as our technology stack platform got it okay and so i have a question um what was it like in terms of just the skills and the adoption uh for your developers uh was it was it a big gap to go from where you were to you know where you are today did you have to what kind of training did you have to do did you have to do any sort of outsourcing to accelerate that maybe you could describe that how you close that skills gap so definitely in the beginning is quite challenging because although they are using modern languages like jaffa or kotlin but uh to understand the concept and to design correctly yes we we did a lot of training to them uh it takes a it takes me about three months to give them the proper training uh in terms of building the right uh microservices platform and also to building modular architecture in terms of the customer channel because this will be the fundamental when you build it correctly in the beginning and actually at the later point you will enjoy the benefit so the first three months actually is training and doing research and development and doing a lot of trial and errors but after the three months actually we already have the right technology stack have the right models and our devsecops is already working then actually after that the speed is very fast because uh it sprints uh we do agile way of working the agiles dlc it's only one month so every one month we already have new features coming in so that's what we call a huge transformation a digital transformation inside of our bank it's three months actually not bad i mean i would i would have thought on average it's going to take five or six months to get people up to speed so three months is pretty good and i'm also inferring that you weren't just paving the cow path you weren't just saying okay let's take our traditional and then you know re refactor it to digital you had to re-envision what digital looked like because the digital is different uh than the traditional uh so so that's actually pretty good uh ramp rate i wonder if you could just go ahead and comment if you could because when you say about uh revamp so actually it's not on the id side not only but also the business side we implement new way as well so actually if clearly they're implementing a new model so they're using a design thinking and also a co-creation model where now when we building a product so we're not writing the old product in a new way no we totally building it from from scratch and involving our key customer and our stakeholder when we're building this product so actually we implementing new models what we call design thinking and also uh co-creation with our customer so that's actually changing the face of the customer electronic channel a lot and and actually when we when we want to to deploy we invite our customer to test it first we call it like usability testing if they like it we continue to design if they they don't like it they give us a feedback how they would like it to be changed and and that's we appreciate our customer feedback because customers experience is everything now yeah so so the product can be accepted if the experience on that product is really making customer uh solving their problem solving the customer problem and making them enjoying uh doing transactions in our mobile banking product i think this is a really important point for people to understand so you weren't just paving the cow path i call it you're taking the old and and just trying to refactor it and make it exactly turn it into digital you had to really think about the business the business processes the dependencies the customer experience and then bring it back um what have been some of the business outcomes of this initiative and maybe you could we then after that we can get into some of the the future plans so so the outcome uh i think this journey uh since last year uh not last year actually since no october 2019 we already started the journey uh what took us by surprise is actually the pandemic uh suddenly the first three months when we have the pandemic of coffee we are being forced to close a lot of branches for temporary because we want to avoid the pandemic situations and that time actually the the demand using our digital channel is increasing a lot but because we already prepared actually we get the benefit one of the thing is uh the business benefit is relating so during the pandemic nobody can come to the branch and mostly the account opening actually happening online so uh we even got about 9000 account opening per day which is something that we are not imagining before so uh the benefit is very clear by using this this technology actually enabling us to provide digital capability for our customer and enabling us to open more accounts we see ourselves can grow even not linear but exponentially grow by using this platform uh talking about that indonesia is a is a huge country with we have about 200 250 million populations and actually there's still a lot of people is not having a bank account at all now by doing this actually we open opportunity doing financial inclusion for those people that need a banking account now they can reach us by using the digital platform as well yeah that's an awesome story and it goes back to the to the reason the real motivator for for moving to kubernetes and containers was scale uh and and you know it's you obviously started your digital journey prior to the pandemic but a lot of customers and i'm sure you as well were were forced to speed up a portion anyway of the digital component uh because of the pandemic like you said you couldn't people couldn't walk into the branches so but now you've got some more time to think about that journey you've had a lot of learnings 2020 was like a petri dish of experimentation but but in real time having to serve customers what's the future look like for the bank's technology journey okay so basically we uh we are not stopping only on the retail side yeah uh we want to redefine our customer journey also on the wholesale side and also on the small medium enterprise there is still a lot of things that need to be done uh and required by the customer actually so uh on the on the on the sme side we want to give them easier access uh for uh financing their businesses i think when we are back to the new normal uh the business need to have funding for for starting their business again so building an sme platform for them will will help a lot and will help the country as well on the retail side actually like i told you uh we are focusing on the more financial inclusion because uh i give you example right uh from the 230 million of indonesians uh populations i think by today maybe it's only about 50 million customers that already have a banking account so there is still a lot of people that need an access faster and cheaper and more efficient way for doing banking transactions so that's this also will become our focus and the last part is actually corporate what we see now a lot of the corporate require us to open uh api connectivity doing open banking with them the government actually the central bank supporting it supporting all the banks they are trying to create an api playbooks now and then they create they want to create an api standard for all the core all the use corporate also can connect it to the bank directly using api so this is also our focus because it will help the country economy when the economy costs the transaction costs getting more efficient getting more cheaper and there's a lot of transaction can be supported by our bank as well so i think i think that's the the future that we are imagining and i'm really hope that the pandemi will be finished and we come back to the to the new normal and we can support more transactions for this country yeah you're here to that i call it the new abnormal but so this is this is a great story everybody loves to talk about disruption we do as well and but people think oh it's out with out with the old in with the new and it's not like that this is a great story victor of uh of an established incumbent that is modernizing its its applications and its digital experience and of course the incumbent has the advantage of it's a real business it has customers that has a data it has experiences it and if it can modernize its infrastructure and and it's in its application portfolio it actually has an advantage because it's got way more features way more data way more customers and more resources so victor thanks so much for coming on thecube i really appreciate you sharing your story thank you dave thank you for inviting me thank you that was our pleasure and thank you for watching red hat summit 21 this is thecube you

>> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Online brought to you by Amazon Web Services. >> Welcome back to theCUBE's Virtual coverage of Amazon Web Services, AWS Public Sector Summit Online. We couldn't be there in person, but we're doing remote interviews. I'm John Furrier, your host of the cube. We've got a great segment from Asia Pacific on the other side of the world from California, about social impact, transforming teaching and learning with Cloud technology we've got three great guests. Hugo Richard is the CEO and co-founder of Dystech and Janine Teo CEO and founder of Solve Education founders and CEOs of startups is great Vincent Quah is the APAC Regional Head of Education, Healthcare Not-For-Profit and Research for AWS. (indistinct) big program. Vincent, thanks for coming on Janine and Hugo thank you for joining. >> Thanks for having us, John. >> Thanks John So, we're not there in person. We're doing remote interviews. I'm really glad to have this topic because now more than ever social change is happening. This next generation is building software and applications to solve big problems. And it's not like yesterday's problems, they're today's problems and learning and mentoring and starting companies are all happening virtually, digitally, and also in person. So the world's changing. So I got to ask you, Vincent we'll start with you Amazon, obviously big (indistinct) culture. You got two great founders here and CEOs doing some great stuff. Tell us a little bit what's going on at APAC, a lot of activity. I mean re-invent and the summits out there are really popular. Give us an update on what's happening. >> Thank you, thank you for the question, John. I think it's extremely exciting, especially in today's context, that we are seeing so much activities, especially in the education technology sector. One of the challenges that we saw from our education technology customers is that they're always looking for help and support in many of the innovation that they're trying to develop. The second area of observation that we had was that they are always alone with very limited resources and they usually do not know where to look for in terms of support and in terms of not who they can reach out to from a community standpoint, that is actually how we started and developed this program called AWS EdStart. It is a program specifically for education technology companies that are targeting, delivering innovative education solutions for the education sector. And we bring specific benefits to these education technology companies when they joined the program, AWS EdStart. Yeah, three specific areas, one is that we support them with technical support, which is really, really key trying to help them navigate in the various ranges of AWS services that allows them to develop innovative services. The second area is leaking them and building a community of like-minded education technology founders, and linking them also to investors and VCs. And lastly, of course, in supporting innovation, we support them with a bit of AWS Cloud credits, promotional credits for them so that they can go and experiment and develop innovations for their customers. >> That's great stuff I want to get into that program a little bit further because I think, you know, that's a great example of kind of benefits AWS provides (indistinct) free credits or, no one is going to turn away free credits. We'll take the free credits all the time, all day long, but really it's about the innovation. Janine I want to get your thoughts. How was Solve Education born? What problems were you solving? What made you start this company and tell us your story. >> Thank you so much for the question. So actually my co-founder was invited to speak at an African Innovation Forum couple of years back, and the topic that he was sharing with, how can Africa skip over the industrialization phase and go direct to the knowledge economy and that discussion went towards, in order to have access to the knowledge commonly you need knowledge and how do you get knowledge well through education. So that's when everybody in the Congress was a bit stuck, right? And the advice was in order to scale fast, we need to figure out a way to not while, you know, engaging the government and schools and teachers, but not depend on them for the success of the education initiative. So, and that's was what (indistinct) walk away from the conference. And when we met in Jakarta, we started talking about that also. So while I'm Singaporean, I worked in many developing countries. And the problem that we're trying to solve is it might be shocking to you, but UNESCO recently published over 600 million children and youth are not learning. And that is a big number globally, right? And out of all the SDGs per se, from UN, education, and perhaps I'm biased, because I'm a computer engineer, but I see that education is the only one that can be solved by transforming (indistinct) versus the other SDGs like, you know, poverty or hunger, right? Actually require big amount of logistic coordination and so on. So we saw a very interesting trend with mobile phones, particularly smart phones becoming more and more ubiquitous. And with that, we saw a very interesting opportunity for us to disseminate education through mobile technology. So we in self-education elevate people on a public through providing education and employment opportunities, (indistinct) on tech. And we.. our vision is to enable people to empower themselves. And what we do is that we build an open platform that provides everyone active education. >> Hugo How about your company? What problem are you solving? How did it all get started? Tell us your vision. >> Thanks, John. Well, look, it all started with a joke, one of the co-founder, Matthew, had a, he has a child who has severe learning disorder and dyslexia, and he made a joke one day about having (indistinct) that could support those kids. And I took the joke seriously. So we started sitting down and, you know, trying to figure out how we can make this happen. So it turns out that dyslexia is the most common learning disorder in the world. We have an estimated 10 to 20% of the worldwide population with the disorder, due to in context, that's between 750 million up to 1.5 billion individuals with that learning disorder. And so where we sort of try and tackle the problem is that we've identified that there's two key things for children with dyslexia. The first one is that knowing that it is dyslexia, meaning being assessed. And the second one is, so what, what do we do about it? And so given all expertise in data science and AI, we clearly saw an opportunity of sort of building something that could assess individual children and adults with dyslexia. The big problem with the assessment is that it's very expensive. We've met parents in the U.S. specifically who paid up to 6,000 U.S. Dollars for a diagnosis with an educational psychologist. On the other side, we have parents who wait 12 months before having a spot. So what we saw clearly is that the observable symptom of dyslexia are reading, and everyone has a smartphone and (indistinct) from smartphone is actually really good to record your voice. So we started collecting audio recordings from children and adults who have been diagnosed with dyslexia. And we then try to model and to recognize the likelihood of dyslexia by analyzing audio recording. So in theory, it's like diagnosed dyslexic, helping other undiagnosed dyslexic being diagnosed. So we have now (indistinct) them. That can take about 10 minutes, which requires no prior training costs, 20 U.S. Dollar, and anyone can use it to assess someone's likelihood of dyslexia. >> You know, this is the kind of thing that really changes the game because you also have learning for questions that are nonlinear and different. You've got YouTube, you've got videos, you have knowledge bases, you've got community. Vincent mentioned that Janine, you mentioned, you know, making the bits of driver and changing technology. This is the kind of thing that seems obvious now as look at it, but now you've got to put it into action. So, you know, one of the benefits of Cloud on AWS, we'll give a plug for Vincent's company here is that you can move faster. And that's something that Andy Jassy always talks about and Teresa Carlson, being builders and moving fast, but you got to build it. So Janine and Hugo, please take a minute to explain, okay, you got the idea, you're kicking the tires, you're putting it together. Now you've got to actually start writing code. What happens next? Janine, we'll start with you. >> Well, what happens next? Okay. So for us, we know education technology is not new, right. And education games are not new, but before we even started, we look at what's available and we quickly realized that the digital divide is very real, most technology out there first are not designed for (indistinct) devices, and also not designed for people who do not have internet at home. so with just that assessment, we quickly realized we need to do something about, and that's something that problem is. One is just one part of the whole puzzle. There's two other very important things. One is advocacy. Can we prove that we can teach through mobile devices? And then the second thing is motivation. And again, it's also really obvious, but, and people might think that, you know, marginalized communities are super motivated to learn. Well, I wouldn't say that they are not motivated, but just like all of us behavioral change is really hard, right? I would love to workout everyday, but you know, I don't really do that. So how do we use technology to, you know, to induce that behavioral change so that we can help support their motivation to learn. So those are the different things that we work on, certainly with it. >> Yeah, and then a motivated community, is even more impactful because then once the flywheel gets going, then it's powerful. Hugo your reaction to, you know, you got the idea, you got the vision, you're starting to put, take one step in front of the other. You got AWS, take us through the progression on the startup. >> Yeah, sure. I mean, what Janine said is, very likely to, to what we're trying to do, but for us, there's three key things that in order for us to be successful and help as much people as we can, it is three things. The first one is reliability. The second one is accessibility and the other one is affordability. So the reliability means that we have been doing a lot of work in the scientific approach as to how are we going to make this work And so we've.. We have a couple of scientific publications and we had to collect data and, you know, sort of publish this into AI conferences and things like that. So it makes sure that we have the scientific evidence behind us that support us. And so what that means is that we have to have a large amount of data and then put this to work, right on the other side of the accessibility and affordability means that Janine said, you know, it needs to be on the Cloud because if it's on the Cloud, it's accessible for anyone with any device, with an internet connection, which is, you know, covering most of the globe. So it's a good start. And so, the Cloud obviously allow us to deliver the same experience and the same value to clients and parent and teacher and (indistinct) professional around the world. And that's why, you know, it's been amazing, to be able to use the technology on the AI side as well obviously there is a lot of benefit of being able to leverage the computational power of the Cloud, to make better algorithm and better training. >> (indistinct) to come back to both of you on the AI question. I think that's super important. Vincent I want to come back to you though, because in Asia Pacific and that side of the world, you still have the old guard, the incumbents around education and learning, but there's great penetration with mobile and broadband. You have great trends as a tailwind for Amazon and these kinds of opportunities EdStart, what trends are you seeing that are now favoring you? Because with COVID, you know, the world is almost kind of like been a line in the sand is before COVID and after COVID, there's more demand for learning and education and community now than ever before, not just for education, the geopolitical landscape, everything around the younger generation is more channels, more data, the more engagement, how are you looking at this? What's your vision of these trends? Can you share your thoughts on how that's impacting learning and teaching? >> So there're three things that I want to quickly touch on. Number one, I think governments are beginning to recognize that they really need to change the way they approach solving social and economic problems. The pandemic has certainly calls into question that if you do not have a digital strategy, you can't find a better time to now develop and not just develop a digital strategy, but actually to put it in place. And so government are shifting very, very quickly into the Cloud and adopting digital strategy and use digital strategy to address some of the key problems that they are facing. And they have to solve them in a very short period of time. Right, We will talk about speed, the agility of the Cloud, and that's why the Cloud is so powerful for government to adopt. The second thing is that we saw a lot of schools close down across the world, UNESCO reported, what 1.5 billion students out of schools. So how then do you continue teaching and learning when you don't have physical classroom open and that's where education technology companies and, you know, heroes like Janine's company and others, there are so many of them around are able to come forward and offer their services and help schools go online, run classrooms online, continue to allow teaching and learning, you know, online. And this has really benefited the overall education system. The third thing that is happening is that I think tertiary education and maybe even (indistinct) education model will have to change. And they recognize that, you know, again, it goes back to the digital strategy that they've got to have a clear digital strategy and the education technology companies like what, who we have here today. Just the great partners that the education system need to look at to help them solve some of these problems and get to addressing giving a solution very, very quickly. >> Well, I know you're being kind of polite to the old guard, but I'm not that polite. I'll just be, say it. There's some old technology out there and Janine and Hugo, you're young enough not to know what IT means because you're born in the Cloud. So that's good for you. I remember what I teach. Like in fact, there's a, there's a joke here in the United States so with everyone at home the teachers have turned into the IT department, meaning they're helping the parents and the kids figure out how to go unmute and how to configure a network address translation if their routers don't work, real problems. I mean, this was technology, schools were operating with low tech Zoom's out there. You've got video conferencing, you've got all kinds of things, but now there's all that support that's involved. And so what's happening is it's highlighting the real problems of the institutional technology. So Vincent, I'll start with you. This is a big problem. So Cloud solves that one, you guys have pretty much helped IT do things that they don't want to do anymore by automation. This is an opportunity, not necessarily.. There's a problem today, but it's an opportunity tomorrow. Could you just quickly talk about how you see the Cloud, helping all this manual training and learning new tools. >> Absolutely. So I want to say and put forth a hypothesis and that hypothesis is simply this. We are all now living in a Cloud empowered economy, whether we like it or not, we are touching and using services that are powered by the Cloud. And a lot of them are powered by the AWS Cloud, but we don't know about it. A lot of people just don't know, right? Whether you are watching Netflix, well in the old days, you're buying tickets and booking hotels on Expedia, or now you're actually playing games on Epic Entertainment, you know, playing Fortnite and all those kinds of games you're already using and a consumer of the Cloud. And so one of the big ideas that we have is we really want to educate and create awareness of top computing for every single person. If it can be used for innovation and to bring about benefits to society that is a common knowledge that everyone needs to have. And so the first big idea is, want to make sure that everyone actually is educated on Cloud literacy. The second thing is for those who have not embarked on a clear Cloud strategy, this is the time don't wait for another pandemic to happen because you want to be ready. You want to be prepared for the unknown, which is what a lot of people are faced with. And you want to get ahead of the curve. And so education, training yourself, getting some learning done. And that's really very, very important as a next step to prepare yourself to face the uncertainty and having programs like AWS EdStart actually helps to empower and catalyze innovation in the education industry that our two founders have actually demonstrated. So back to you, John. >> Congratulation on the EdStart, we'll get into that and real quickly, EdStart but let's first get the born in the Cloud generation Janine and Hugo you guys are competing, you got to get your apps out there. You've got to get your solutions. You're born in the Cloud. You have to go compete with the existing solutions. How do you view that? What's your strategy? What's your mindset, Janine, we'll start with you. >> So for us, we are very aware that we are solving a problem that has never been solved, right? If not, we wouldn't have so many people who are not learning. So this is a very big problem. And being able to leverage on Cloud technology means that we are able to just focus on what we do best, right? How do we make sure that learning is sufficient and learning is effective. And how do we get people motivated and all those sort of great things leveraging on game mechanics, social network, and incentives. And then while we do that on the Cloud side, we can just put that almost ourselves, everything to AWS Cloud technology to help us not worry about that. And you were absolutely right. The pandemic actually woke up a lot of people and has organizations like myself. We start to get queries from governments and other, even big NGOs on, you know, because before COVID we had to really do our best to convince them until (indistinct) are dry >> (indistinct) knock on doors and convince people. >> Yes. And now we don't have to do that. It's the other way around. So we are really, you know, we appreciate this opportunity and also we want to help people realize that in order to.. By adopting either a blended approach or adopting technology means that you can do mass customization of learning as well. And that's, what we could do to really push learning to the next level. So, and, there are a few other creative things that we've done with governments, for example, with the government of East Java on top of just using the education platform, as it is an educational platform, which is education (indistinct) on our civilization, they have added in a module that teaches COVID because, you know, their health care system is really under a lot of strain there, right? And adding this component in and the most popular mini game in that component is this game called Hoax Or Not. And it teaches people to identify what's fake news and what's real news. And that really went very popular and very well in that region of 25 million people. So that became not only just boring school subjects, but it can be used to teach many different things. And following that project, we are working with the Federal Government of Indonesia to talk about (indistinct) and even a very difficult topic like sex education as well. >> Yeah. And the learning is nonlinear, it's horizontally scalable, it's network graph. So you can learn, share about news. And this is contextual data. It's not just learning, it's everything. It's not like, you know, linear learning. It's a whole nother ballgame, Hugo, your competitive strategy. You're out there now, you got the COVID world. How are you competing? How's Amazon helping you? >> Absolutely John, look, this is an interesting one because the common competitor that we have are educational psychologist, they're not at tech. So I wouldn't say that we're competing against a competitor per se. I would say that we are competing against some old way of doing things. The challenge for us is to empower people, to be comfortable with having a machine, you know, analyzing your kid's audio recording and telling you if it's likely to be dyslexia. And this concept obviously is very new. You know, we can see this in other industry with AI, you know, you have the app that Stanford created to diagnose skin cancer by taking a photo of your skin. So it's being done in different industry. So the biggest challenge for us is really about the old way of doing things. What's been really interesting for us is that you know, education is lifelong, you know, you have a big pot in school, but when you're an adult you learn and, you know, we've been doing some very interesting work with the Justice Department where, you know, we look at inmate and, and, you know, often when people go to jail, they have, you know, some literacy difficulty. And so we've been doing some very interesting work in this field. We're also doing some very interesting work with HR and company who want to understand their staff and put management in place so that every single person in the company are empowered to do the job and, you know, achieve success. So, you know, we're not competing against Ed Tech. And often when we talk to other Ed Tech company, we come before, you know, we don't provide a learning solution. We provide an assessment solution, an E assessment solution. So really John, what we competing against is an old way of doing things. >> And that's exactly why the Cloud's so successful. You change the economics. You're actually a net new benefit. And I think the Cloud gives you speed. And your only challenge is getting the word out because the economics are just game changing, right? So that's how Amazon does so well, by the way, you can take all our recordings from theCUBE interviews, all my interviews and let me know how I do, okay. So got all the, got all the voice recordings for my interview. I'm sure the test will come back challenging. So take a look at that. >> Absolutely. >> Vincent I want to come back to you, but I want to ask the two founders real quick for the folks watching okay and hear about Amazon. They know the history, they know the startups that started on Amazon that became unicorns that went public. I mean, just a long list of successes born in the Cloud. You get big pay when you're successful, love that business model. But for the folks watching that are in the virtual garages or in their houses innovating and building out new ideas, what does EdStart mean for them? How does it work? Would you would recommend it? And what are some of the learnings that you have from working with EdStart? Janine We'll start with you. >> For me. So I would, for me, I would definitely highly recommend EdStart. And the reason is because EdStart, our relationship with EdStart, is almost not like a client-supplier relationship it's almost like business partners. So they not only help us with providing the technology. But on top of that, they have their system architects to work with my tech team and they have, you know, open technical hours for us to interact. And on top of that, they do many other things like building a community where, you know, people like me and Google can meet. And also other opportunities like getting out there, right? As you know, all of the startups run on a very thin budget. So how do we not pour millions of dollars into getting all that out there is another big benefit as well. So I'll definitely very much recommend EdStart. And I think another big thing is this, right? Now that we have COVID and we have demands coming from all other places including like, even (indistinct) from the Government of Gambia, you know, so how do we quickly deploy our technology right there? Or how do we deploy our technology from the people who are demanding our solution in Nigeria, right? With technology it is almost brainless. >> Yeah. The great enabling technology ecosystem to support you. I think, at the regions too. So the regions do help. I love we call them cube regions because we're on Amazon, we have our Cloud Hugo, EdStart your observations, experience and learnings from working with AWS. >> Absolutely. Look, there's a lot to say, so I'll try and make it short for anyone, but, so for us and me personally, and also as an individual and as a founder, it's really been a 365 sort of support. So like Janine mentioned, there's the community where you can connect with existing entrepreneur. You can connect with experts in different industry. You can ask technical experts and have a, you know, office hour every week. Like you said, Janine with, your tech team talking to a Cloud architect just to unlock any problem that you may have. And, you know, on the business side, I would add something which for us has been really useful is the fact that when we've approached government, being able to say that we have the support of AWS and that we work with them to establish data integrity, making sure everything is properly secured and all that sort of thing has been really helpful in terms of moving forward with discussion with potential client and government as well. So there's also the business aspect side of things, where when people see you, there's a perceived value that, you know, your entourage is smart people and people who are capable of doing great things. So that's been also really helpful. >> You know, that's a great point. The AppSec review process as you do deals is a lot easier when you're on AWS. Vincent we're a little bit over time. What a great panel here. Close us out, share with us what's next for you guys. You've got a great startup ecosystem and doing some great work out there and education as well, healthcare, how's your world going on? Take a minute to explain what's going on in your world. >> John I'm part of the public sector team worldwide in AWS, we have very clear mission statements. And the first is, you know, we want to bring about disruptive innovation. And the AWS Cloud is really the platform where so many of our Ed Techs, whether it's (indistinct) Health Tech, Gulf Tech, all those who are developing solutions to help our governments and our education institutions, our healthcare institutions to really be better at what they do. We want to bring about those disruptive innovations to the market, as fast as possible. It's just an honor and a privilege for us to be working. And why is that important? It's because it's linked to our second mission, which is to really make the world a better place to really deliver.. The kind of work that Hugo and Janine are doing. We cannot do it by ourselves. We need specialists and really people with brilliant ideas and think big vision to be able to carry out what they are doing. And so we're just honored and privileged to be part of their work. And in delivering this impact to society. >> The expansion of AWS out in your area has been phenomenal growth. I've been saying to Teresa Carlson and Andy Jassy and the folks at AWS for many, many years, that when you move fast with innovation, the public sector and the private partnerships come together, you starting to see that blending. And you've got some great founders here making a social impact, transforming teaching and learning. So congratulations, Janine and Hugo. Thank you for sharing your story on theCUBE. Thanks for joining. >> Thank you for having us >> thanks John >> Thank you, John. I'm John Furrier with theCUBE Virtual we're remote. We're not in person this year because of the pandemic you're watching AWS Public Sector Online Summit. Thank you for watching. (soft music)

>> Announcer: Live, from Las Vegas, it's the Cube. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to ServiceNow Knowledge18 the Cube's live coverage. We are the Cube, the leader in live tech coverage. I'm your host, Rebecca Knight, along with my co-host, Dave Vellante. We're joined by Jason Scott-Taggart. He is the head of Business Technology Support at WorldPay. He's in direct from London. So welcome, Jason, to the show. >> Thank you, it's good to be here. >> So first lay the scene for our viewers. Tell us a little bit about what WorldPay is and what you do. >> So WorldPay is the largest payments company in the world. So it's a hidden gem that not a lot of people know about. So recently we merged with Vantiv, which is huge in domestic US. And WorldPay is very large in the rest of the world. So a marriage made in heaven. We're what's technically known as a merchant acquirer, which is a fancy way of saying that we take credit card payments. And we do that for both online or in the store, putting your card in a machine. So billions of transactions a year. >> And what's your relationship with the banking infrastructure around the world? How does that all work? >> Sure, so the banks issue credit cards and your relationship as an individual is with the bank. So you pay your bills to the bank and have that transaction. We look after the merchants. So we're the ones that do the services for the, we quaintly call the merchants still, so for the shops and the traders, we have that relationship. And basically the transactions then go between the two. So individuals to the bank, bank to us, us to the merchants. And we just aggregate that because if you're, even if you're a large company like Costco or Google, you don't want to have to have a relationship with every one of the credit cards let alone every one of the banks. So we aggregate that. >> So tell us about your ServiceNow journey. When did you start using the platform? >> So ServiceNow, we're on our third year now I think with ServiceNow. And it's been explosive. It was a quite seamless transition. We were really pleased with the previous platform we were on, how we moved over. And we slowly added to it. We slowly turned on other modules, other functionality. And it's just become ingrained in our day-to-day IT operations. >> It was simpler because you had had other processes in place? You didn't have to rip and replace those processes and skill sets? >> We took it as an opportunity to do best-of-breed. So there were some things that we carried over. But we took the opportunity for a clean start as well. Even before a lot of the buzz here is back to basics and staying out of the box, and we did that for a lot of it, and that was quite refreshing, and it was quite cathartic in a way that we could make that change. But then there were some bits that weren't really well and were ingrained in our business process so we had to carry those over. But we found it easy to do a mixture of both. >> And you carried those over in the form of custom modifications? >> Some, not a lot. We tried to stay as much out of the box as possible. >> So how does that having some custom mods affect your ability to go to subsequent releases? >> I think it's fair to say that ServiceNow is one of the easier platforms to upgrade. I probably shouldn't say that. They should be doing more work to make it easier for me. (laughing) >> Dave: Do a better job of upgrades. >> But compared to some other platforms we have even Cloud ones, it's not the hardest. It's not the worst. However, we've tried to stay close to the box to make it even easier. We want to stay N plus one no more, and when you're coming out with a major upgrade twice a year, that means we've got to factor that into our road map. But we do. We make sure that we try and stay up to date. >> So where are you now? You're in, are you? >> We're in Jakarta. >> Jakarta, okay. >> Yeah. >> So you're pretty current. >> Yeah, only just though, so. >> Okay, but we heard a lot about Madrid today. >> Yeah. >> Which is Q119. And a lot about DevOps. So talk about, it was very good that the DevOps 101 that Pat Casey gave. I'll give my version of DevOps 101 if I can. (laughs) Back in the day, the developers would write some code, maybe on their laptop or whatever, they'd throw it over the fence to the ops guys, and say, here, deploy this. And the ops guys would go to deploy, and they say, ah, this thing doesn't meet up to our enterprise standards. It doesn't have the security and the governance. So they go in and they hack the code, invariably break it, and then they go to deploy it, and it doesn't work. And they go back to the developers and your code doesn't work. And the developers say, well it worked when I gave it to you. And you get this back and forth, back and forth, back and forth. So DevOps consolidates that into a single programming environment. >> That's good, I appreciate this. >> Infrastructure is code. And so that's my version. Pat Casey gave a much more eloquent description, but what is DevOps to you guys and how are you applying it? >> So we've got two major competitive drivers in the market. One is scale. So we're the largest payments company in the world so we need to leverage that. We can operate in most countries of the world, take most currencies, so that's a scale thing that we try and leverage. Scale tends to lend itself more to waterfall kind of traditional projects. (laughs) The other competitive pressure that we face is from small fintech startups that are nibbling away at our ankles for niche products and new services or disrupting the whole way we do payments. Will there be banks tomorrow? Who knows. The whole way could be disrupted. That innovation lends itself more to a DevOps kind of, or at least an agile form of development. You want rapid prototyping, trying things, seeing what works. So one of the things we've been struggling with at WorldPay is how can we foster more of the DevOps whilst not endangering the traditional kind of waterfall that we need to do. The vast majority of our development is done agile, but hardly any of it is DevOps. And a lot of people confuse agile for being DevOps. And agile is just the dev part of it, it isn't the ops bit of it. So where's the ops in DevOps? What we did, you just outlined classic reasons why people might want to do that, and having a single team owning something all the way through the life cycle. What we've done is we've tried to separate out different layers and kinds of services to allow that to happen. So with scale, you have to have one level one. You have to have a front door for IT that everybody comes to. Whether you're a squidgy resource, a human needing to phone someone or your tin and wires, there's got a problem and alerting an event. So you have one front door. What you need to do is you need to try and have a high first-time fix. That's cheapest and that's most best experience for the end user. So we aim for 60, 70% of issues to just be killed at that front door. That's the aim. After that, we then put a lot of work and effort to make sure that we had a business-oriented, service-oriented CMDB. So we worked with the lines of business to describe WorldPay and what we do in a way that they understood and the IT understood, and then we translated that into a service management language in the CMDB. Once you go past that level one, the level one know they can't fix it, they know what's broken, or they're pretty certain what's broken, they will put it into the right service line. That level two is still run only. So we split, the dev and the run at that level two. You're aiming for 25% of things to stop there. That leaves only about 5% of things that would ever go wrong needing to go to a third line. That third line we refer to as technical services. So you've got business services in the middle of that level two, that the business would recognize and they consume or our merchants would. The technical services at the third line are the components. They're the building blocks that we use to make those business services. And those are where we start doing the DevOps. Another word for it is microservices. So microservices, we have components, sensors of excellence, in both infrastructure, so a virtualized platform, or applications. So a fraud module or a billing module, or a authorization module. And those teams, because they're only getting 5% of things coming through to them that are wrong, they can cope with being small teams that do both the dev and the ops. And that makes it feasible, and we're fostering that. And we're starting to get live services that are being supplied in that DevOps manner, and that means that that can grow as it succeeds or fail as it doesn't, and it's not endangering the huge machine that is the rest of the organization. >> So the huge machine, the core piece of your systems, you still apply waterfall, is that right? >> Jason: Yes. >> And then in the new stuff where you don't mind breaking things, you're applying agile and DevOps. >> Exactly. And that's what we're seeing is that that then what succeeds and what the ways of working or the particular needs that that microservices is addressing, if they're successful it feeds it, awards it, and they do more. So the teams that are going live with some of these microservices, if they put enough effort into making it resilient, doing the non-functional as well as the functional requirements, which is a DevOps thing as well, so you make something and you get it right first time, so it's not breaking all the time, they can then have spare cycles to go and do other sprints where they're building the next thing. And what we hope to see over time is that we will have a larger and larger proportion of the components that make those business services being supplied in the DevOps way. And that is also complementary with going to Cloud services 'cause they're just other building blocks. They're just components that you use to put together something. >> You saw Pat Casey and C. J. Desai, they showed a little leg today on Madrid. They basically developed a DevOps capability for their own purposes and they're going to release it in Madrid. The problem they're trying to solve if I understood it was you've got 500 DevOps tools out there and there's complexity, did that resonate with you? Is that something you'll adopt? Or are you comfortable with your DevOps tools? >> No we're keen and eager to adopt. Well, I'm an IT ops guy by trade. That's what I've been doing for the last 20, 30 years, but I'm not afraid of DevOps. I love DevOps. DevOps means faster delivery with more control. It's automated ITIL. And what the ServiceNow road map is giving me is a way that I can continue to be the air traffic control for IT. I want people to come to me and my team and say, where are we at? What's moving where? And if we get the hooks into ServiceNow into all of those DevOps tools, the names are up there, the Jenkins, the Chef, the Puppets, if we get the hooks in, then it expands more of the PMO work that we almost do as well. So instead of talking about just a single change ticket or a release that's happening here, we can go, that train in the safe framework or this, that sprint over there, they've got to this point. They're in testing. They're about to release this. Actually I can tell you the features that they're proposing will come with this. Because that's hooked in. So that's the dream. That's where we want to get. Because we want to facilitate more of this happening within our development community. >> So from a legacy talent standpoint, are you more DevOps or are you OpsDev? (laughs) >> Rebecca: Oh, I like that. >> Me personally I'm OpsDev. >> Well right, but I mean for your organization was it kind of retraining the ops guys to think more like devs or was it kind of jamming the ops piece into-- >> We've got challenged with both. And the real success that we've had so far has mainly been greenfield. We've set up teams from scratch with the purpose of testing out DevOps as a theory. And it's worked brilliantly. Now though, the bigger struggle is how do you get existing teams? We've got hundreds of developers in our own squad, so working on agile, but they do pure dev. They build it and they hand it over and then they're off, they're onto the next thing. How do we mix those teams? How do you get multi-disciplinary teams that have both the operational knowledge as well as the development? And that's a cultural thing as well as the tooling. Tooling helps. If you get nice tooling that makes it easier for them to operate in a particular way, that's a big important thing, but it's only half the battle. You've got to get people thinking in a slightly different way. And that's true of the ops people have got to think more of the life cycle. How do they feed back what's working and what's not into the next development cycle. And the development people have got to think about what happens once they let it go. And they've got skin in the game now. It's going to come back and bite them. If they didn't do it well, if they didn't put the dashboards for the support people to see how well it's working, then the support people are going to be banging on their door to get it. So it's a cultural thing as well. >> It's a cultural thing. >> So I'm going to ask you a business question. You referred a little bit to disruption before. You talked about banks and the future of banks. Do you think, and you're very tied into the banks, obviously, do you think, and I wonder if this is a discussion inside the organization that banks, traditional banks will lose control of today's payment systems? >> Well, arguably they're not fully in control of it today anyway. (laughs) And so that's not to mean that they're not in control of what they are to do, but they don't own the payment process end-to-end. >> But they own the consumer. >> They own the consumer relationship, yeah. And that's going to be disrupted in the same way the way that we take payments at the other end of the life cycle is disrupted as well. Contactless, block chain, these kind of things mean that it's not going to be the same. However, you're not going to get rid of large organizations overnight. Because what is also increasing day-by-day, is regulation, security requirements. You want to know that your card's going to be safe. You don't want, if you're going to use Apple Pay, or a new contactless technology, you're only going to do that if you know there's no danger of you losing money by doing it. To have that certainty and to meet the regulators' requirements you need organizations like WorldPay looking after the merchants' interests, you need organizations like banks looking after the individual's interests. So I think, unfortunately, it's not as sexy an answer, but I'm afraid that they're not going to disappear overnight. They're adding valuable service. >> A lot of barriers to entry to those Fintech startups that are nibbling at your ankle. >> However though, it's changed dramatically in the last five years, 10 years, so what on earth it's going to look like in the next five or 10 years, bringing it back, that's why I think innovation is so important. We need to be trying to stay ahead of the curve. We need to meet the needs of our merchants so that they can get as many transactions as possible successfully. And we need to do that at the lowest cost possible. So that's all about innovation. Innovation is hard to do top-down. You've got to find ways of fostering it bottom-up. We have have great leadership top-down. This is where we're going. But actually the way that we're going to get there is down to the troops. It's down to the people on the coal face, so. >> When did you buy your first Bitcoin? >> My first Bitcoin? I bought Bitcoin about four years ago. >> Awesome. >> So yeah, I've done all right. It's paid for a holiday. >> There you go. (laughing) That's good for you. That's great. >> Well, Jason, thanks so much for coming on the show. >> Jason: Thank you. >> It's great talking to you. I'm Rebecca Knight for Dave Vellante. We will have more from ServiceNow Knowledge18 just after this. (upbeat music)

San Francisco it's the Red Hat summit 2018 brought to you by Red Hat okay welcome back everyone this is the cube live in San Francisco for Red Hat summit 2018 I'm John for the co-host of the cube and this week for three days of wall-to-wall coverage my co-host analyst is John Tory the co-founder of check reckoning and advisory and community development services firm industry legend formerly VMware's Bentley he was at the Q in 2010 our first ever cube nine years ago John Day one wrap up let's analyze what we heard and dissect and and put Red Hat into day one in the books but you know clearly it's a red-letter day for red hat so to speak your thoughts big day for open shift I think and hybrid cloud right we just saw a lot of signs here that we'll talk about that it's real there's real enterprises here real deployments in the cloud multi-cloud on-site hybrid cloud and i think there's really no doubt about that they really brought a brought the team out and you know red hat's become a bellwether relative to the tech industry because if you look at what they do there's so many irons on the fires but more the most important is that they have huge customer base in the enterprise which they've earned over a decades of work being the open source renegade to the open source darling and Tier one citizen they got a huge install basin they got to manage this so they can't just throw you know spaghetti at the wall they gotta have big solutions they're very technical company very humble but they do make some good tech bets absolutely we'll be talking with the folks from core OS tomorrow they have a couple of other action you know things we'll be talking about a lot of interesting partnerships the the most you know the thing here Linux is real and it's is the 20-year growth and that it's real in the enterprise and I mean the top line think the top line slowed and John is is is kubernetes than the gnu/linux for the cloud and I got to say there's some reality there yeah it's there's no doubt about it I mean then I've got my notes here just my summary for the day is on that point the new wave is here okay the glue layer that kubernetes and containers provide on top of say Linux in this case OpenShift a you know alternative past layer just a few years ago becomes the centerpiece of red hats you know architecture really providing some amazing benefits so I think what's clear is that this new shift this new wave is massive and we've heard on the cube multiple references to tcp/ip HTTP these are seminal moments where there's a massive inflection point where the games just radically changes for the better wealth creation happens startups boom new brands emerged that we've never heard of that just come out of the woodwork entrepreneurial activity hits an all-time high and they all these things are coming yeah I said John I was really impressed if we talk to a number of folks who are involved with technologies that some people might call legacy right we the Java programmers the IBM WebSphere folks they've been you you look at these technologies solid proven tested but yet still over here and adapted for today right and they talked about how they're fitting into openshift how they're fitting into modern application development and you're not leaving those people behind they're really here and you know the old joke going back to say Microsoft when Steve Ballmer was the CEO hell will freeze over when Linux isn't in in Microsoft ecosystem look today no further than what's going on in their developer Commerce called Microsoft build where Linux is the centerpiece of their open-source strategy and Microsoft has transformed themselves into a total open-source world so you know now you got Oracle with giving up Java II calling a Jakarta essentially bringing Java into an the Eclipse community huge move it's a kind of a nuance point but that's another signal of the shifts going on out in the open where communities aren't just yesterday's open source model a new generation of open source actors are coming in a new model I think the CNC F is showing it the Linux Foundation proves that you can have commercialization downstream with open source projects as that catalyst point as a big deal and I think that is happening at a new new level and it's super exciting to see yeah I mean open source is the new normal sure that that works it's in the enterprise but that doesn't mean that open source disappears it actually means that open source and communities and companies coming together to drive innovation actually gets more and more important I kind of thought well you know it's open source well everybody does open source but actually the the dynamics we're seeing of these both large companies partnering with small companies foundations like you talked about the Linux cutlasses various parts the Linux Foundation cloud boundary foundation etc right are really making a big impact well we had earlier on assistant general counsel David Levine and bringing about open source I think one key thing that's notable is this next generation of open source wave comes is the business model of open source and operationalizing it in not just server development lifecycle but in the business operation so for example spending resources on managing proprietary products with that have open source components separate from the community is a resource that you don't have to spend anymore if you just contribute everything to open source that energy can go away so I think open source projects and the product monetization component not new concepts is now highlighted as a bonafide competitive advantage across the company not just proven but like operationally sound legally verified certified and I think also you have to look at the distribution of open source versus the operation and management of open source we see a lot of management managed kubernetes coming out and in fact we didn't talk about today Microsoft big announcement here at the show Microsoft is on Azure is running a managed open ship not not kubernetes they already have kubernetes they're running a managed open ship another way of adding value to an open open source platforms to date directly to the IT operator honestly do you think these kind of deals would happen if you go back four years three years ago oh no way as you're running an open shift absolutely I mean were you crazy the you know the kingdom is turned upside down absolutely this is a notable point I want to get your reaction is because I see this absolutely as validation to the new wave being here with kubernetes containers as a de facto rallying point an inflection point big deals are happening IBM and Red Hat big deal we just talked about them with the players here two bellwether saying we're getting behind containers and two bays in a big way from that relationship essentially it changes the game literally overnight for IBM changes the game for Red Hat I think a little bit more for IBM than Red Hat already gets a ton of benefit but IBM instantly gets a cloud strategy that has a real scalable product market to it Arvind the the head of research laid that out and IBM now can go and compete with major players on deals with the private cloud more deals are coming absolutely this is the beginning now that everyone snapped into place is saying okay kubernetes and containers we now understand this the rallying cry a de facto standard I think a formation is going to happen in the next six to 12 months of major major major players now I mean we are in a not one size does not fit all world John so I mean we will continue to see healthy ecosystems I mean mesosphere and DT cos is still out there Dockers still out there right you will see very functional communities and and functioning application platforms and cloud platforms but you got to say the momentum is here I mean look at amine docker mace those fears look at when things like this happened this is my opinion so I'm just gonna say it out there when you have de facto standards that happen like this it's an opportunity to differentiate so I think what's gonna happen is docker meso sphere and others including the legacy guys like IBM and in others they have to differentiate their products they have to compete software companies so I think docker I think is come tonight at docker con but my opinion looking at from the outside is I think Dockers realized looking we can't make money from containers kubernetes is happening we're a great standard in that let's be a software company let's differentiate around kubernetes so this is just more pressure or more call-to-action to deliver good software hey it's never been of somebody said it's never been a better time to be an IT and IT infrastructure right this is a you think that the tools we have available to us super-powerful another key point I want to get your reaction on with kubernetes and containers this kind of de facto standardization is breathing new life into good initiatives and legacy projects so you think about OpenStack okay OpenStack gets a nice segmented approach is now clear with a where the swim lanes are you're an app developer you go over here and if you are a network and infrastructure guy you're going here but middleware a from talk to the Red Hat guys here we talk to IBM those legacy and apps can put a container around it and don't have to be thrown away and take their natural course now I think it's gonna be a three line through this holy a second life is for legacy and stuff and then to cloud is and it's in second inning because now you have the enablement for cloud your reaction the enablement of cloud Ibn iBM has cloud and then the market shares of nm who you believe they're not in that they're in the top three but they're not double digits according to synergy research and he bought us a little bit higher but still if you compare public cloud they're small they look at IBM's and tire and small base and saying if they have a specialty cloud that can be assembled quit Nellie yeah and scaled and maybe instantly successfully overnight yeah I think a few years ago you know there was a lot different always a few years back it always looks confusing right a few years back we were still arguing public cloud private cloud as private cloud ed is what is a true private cloud is that even valuable I still see people on Twitter making fun of everything anybody who's not 100% into the full public cloud which means they must not have talked to you know a lot of IT folks who have to business to run today so I think you're saying it's a it's a it's a multivalent world multi-cloud there's going to be differentiated clouds there's going to be operational clouds there's gonna be financial clouds and just it's it seems clear that you know from the perspective of right now here in San Francisco and 2018 that that you know the purpose of public-private hybrid seems pretty clear just like the purpose of like I said we're gonna in two weeks we'll be an openstack summit I mean the purpose of that seems pretty clear it's it's funny it's like I had this argument and each Assateague he thinks everything should go the public cloud goes eaten has one of the public clouds but he's kind of right and I and I and we talked about this way I with him I said if everything is running cloud operation we're talking about cloud ops we're talking about how its managed how its deployed code bases across the board if everything is clarified from an OP raishin standpoint the Dearing on Prem and cloud and IOT edge is there's no difference stuffs moving around so you almost treats a data center as an edge network so now it's sexually all cloud in my mind so then and also you do have to keep in mind time time horizons right anybody who has to do work the today this quarter right has to keep in mind what's what what portfolio of business deeds and tools do I have right now versus what it's gonna look like in a few years all right so I want to get your thoughts on your walk away from today I'll start my walk away from day one was talking some of the practitioners Macquarie Bank and Amadeus to me they're a tell signed the canary in the coalmine what's happening horizontally scalable synchronous infrastructure the new model is here now we're seeing them saying things like it's a streaming world not just Kafka for streaming data streaming services levels of granularity that at workers traded with containers and kubernetes up and down the stack to me architects who think that way will have a preferred advantage over everybody else that to me was like okay we're seeing it play out I guess I totally agree right the future isn't evenly distributed my takeaway though is there's certainly a future here and the people we talked to today are doing real-world enterprise scale multi-cloud micro services and modern architectures incorporating their legacy applications and components and that and they're just doing it and they're not even breaking a sweat so I think IT has really changed ok day one coverage continues day two tomorrow we have three days of wall-to-wall coverage day two and then finally day three Thursday here in San Francisco this is the cubes live coverage go to the cube dotnet to check out all the videos they're gonna be going up as soon as they are done live here and check out all the cube alumni and check out Silicon angle comm for all news coverage then of course you got tech reckoning Jon's company's the co-founder of for John Fourier and John Shroyer that's day one in the books thanks for watching see you tomorrow

[Music] [Music] [Music] [Laughter] [Laughter] [Laughter] [Laughter] [Music] [Music] [Music] [Music] you you [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] wake up feeling blessed peace you warned that Russia ain't afraid to show it I'll expose it if I dressed up riding in that Chester roasted nigga catch you slippin on myself rocks on I messed up like yes sir [Music] [Music] [Music] [Music] our program [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] you are not welcome to Red Hat summit 2018 2018 [Music] [Music] [Music] [Laughter] [Music] Wow that is truly the coolest introduction I've ever had thank you Wow I don't think I feel cool enough to follow an interaction like that Wow well welcome to the Red Hat summit this is our 14th annual event and I have to say looking out over this audience Wow it's great to see so many people here joining us this is by far our largest summit to date not only did we blow through the numbers we've had in the past we blew through our own expectations this year so I know we have a pretty packed house and I know people are still coming in so it's great to see so many people here it's great to see so many familiar faces when I had a chance to walk around earlier it's great to see so many new people here joining us for the first time I think the record attendance is an indication that more and more enterprises around the world are seeing the power of open source to help them with their challenges that they're facing due to the digital transformation that all of enterprises around the world are going through the theme for the summit this year is ideas worth exploring and we intentionally chose that because as much as we are all going through this digital disruption and the challenges associated with it one thing I think is becoming clear no one person and certainly no one company has the answers to these challenges right this isn't a problem where you can go buy a solution this is a set of capabilities that we all need to build it's a set of cultural changes that we all need to go through and that's going to require the best ideas coming from so many different places so we're not here saying we have the answers we're trying to convene the conversation right we want to serve as a catalyst bringing great minds together to share ideas so we all walk out of here at the end of the week a little wiser than when we first came here we do have an amazing agenda for you we have over 7,000 attendees we may be pushing 8,000 by the time we got through this morning we have 36 keynote speakers and we have a hundred and twenty-five breakout sessions and have to throw in one plug scheduling 325 breakout sessions is actually pretty difficult and so we used the Red Hat business optimizer which is an AI constraint solver that's new in the Red Hat decision manager to help us plan the summit because we have individuals who have a clustered set of interests and we want to make sure that when we schedule two breakout sessions we do it in a way that we don't have overlapping sessions that are really important to the same individual so we tried to use this tool and what we understand about people's interest in history of what they wanted to do to try to make sure that we spaced out different times for things of similar interests for similar people as well as for people who stood in the back of breakouts before and I know I've done that too we've also used it to try to optimize room size so hopefully we will do our best to make sure that we've appropriately sized the spaces for those as well so it's really a phenomenal tool and I know it's helped us a lot this year in addition to the 325 breakouts we have a lot of our customers on stage during the main sessions and so you'll see demos you'll hear from partners you'll hear stories from so many of our customers not on our point of view of how to use these technologies but their point of views of how they actually are using these technologies to solve their problems and you'll hear over and over again from those keynotes that it's not just about the technology it's about how people are changing how people are working to innovate to solve those problems and while we're on the subject of people I'd like to take a moment to recognize the Red Hat certified professional of the year this is known award we do every year I love this award because it truly recognizes an individual for outstanding innovation for outstanding ideas for truly standing out in how they're able to help their organization with Red Hat technologies Red Hat certifications help system administrators application developers IT architects to further their careers and help their organizations by being able to advance their skills and knowledge of Red Hat products and this year's winner really truly is a great example about how their curiosity is helped push the limits of what's possible with technology let's hear a little more about this year's winner when I was studying at the University I had computer science as one of my subjects and that's what created the passion from the very beginning they were quite a few institutions around my University who were offering Red Hat Enterprise Linux as a course and a certification paths through to become an administrator Red Hat Learning subscription has offered me a lot more than any other trainings that have done so far that gave me exposure to so many products under red hair technologies that I wasn't even aware of I started to think about the better ways of how these learnings can be put into the real life use cases and we started off with a discussion with my manager saying I have to try this product and I really want to see how it really fits in our environment and that product was Red Hat virtualization we went from deploying rave and then OpenStack and then the open shift environment we wanted to overcome some of the things that we saw as challenges to the speed and rapidity of release and code etc so it made perfect sense and we were able to do it in a really short space of time so you know we truly did use it as an Innovation Lab I think idea is everything ideas can change the way you see things an Innovation Lab was such an idea that popped into my mind one fine day and it has transformed the way we think as a team and it's given that playpen to pretty much everyone to go and test their things investigate evaluate do whatever they like in a non-critical non production environment I recruited Neha almost 10 years ago now I could see there was a spark a potential with it and you know she had a real Drive a real passion and you know here we are nearly ten years later I'm Neha Sandow I am a Red Hat certified engineer all right well everyone please walk into the states to the stage Neha [Music] [Applause] congratulations thank you [Applause] I think that - well welcome to the red has some of this is your first summit yes it is thanks so much well fantastic sure well it's great to have you here I hope you have a chance to engage and share some of your ideas and enjoy the week thank you thank you congratulations [Applause] neha mentioned that she first got interest in open source at university and it made me think red hats recently started our Red Hat Academy program that looks to programmatically infuse Red Hat technologies in universities around the world it's exploded in a way we had no idea it's grown just incredibly rapidly which i think shows the interest that there really is an open source and working in an open way at university so it's really a phenomenal program I'm also excited to announce that we're launching our newest open source story this year at Summit it's called the science of collective discovery and it looks at what happens when communities use open hardware to monitor the environment around them and really how they can make impactful change based on that technologies the rural premier that will be at 5:15 on Wednesday at McMaster Oni West and so please join us for a drink and we'll also have a number of the experts featured in that and you can have a conversation with them as well so with that let's officially start the show please welcome red hat president of products and technology Paul Cormier [Music] Wow morning you know I say it every year I'm gonna say it again I know I repeat myself it's just amazing we are so proud here to be here today too while you all week on how far we've come with opens with open source and with the products that we that we provide at Red Hat so so welcome and I hope the pride shows through so you know I told you Seven Summits ago on this stage that the future would be open and here we are just seven years later this is the 14th summit but just seven years later after that and much has happened and I think you'll see today and this week that that prediction that the world would be open was a pretty safe predict prediction but I want to take you just back a little bit to see how we started here and it's not just how Red Hat started here this is an open source in Linux based computing is now in an industry norm and I think that's what you'll you'll see in here this week you know we talked back then seven years ago when we put on our prediction about the UNIX error and how Hardware innovation with x86 was it was really the first step in a new era of open innovation you know companies like Sun Deck IBM and HP they really changed the world the computing industry with their UNIX models it was that was really the rise of computing but I think what we we really saw then was that single company innovation could only scale so far could really get so far with that these companies were very very innovative but they coupled hardware innovation with software innovation and as one company they could only solve so many problems and even which comp which even complicated things more they could only hire so many people in each of their companies Intel came on the scene back then as the new independent hardware player and you know that was really the beginning of the drive for horizontal computing power and computing this opened up a brand new vehicle for hardware innovation a new hardware ecosystem was built around this around this common hardware base shortly after that Stallman and leanness they had a vision of his of an open model that was created and they created Linux but it was built around Intel this was really the beginning of having a software based platform that could also drive innovation this kind of was the beginning of the changing of the world here that system-level innovation now having a hardware platform that was ubiquitous and a software platform that was open and ubiquitous it really changed this system level innovation and that continues to thrive today it was only possible because it was open this could not have happened in a closed environment it allowed the best ideas from anywhere from all over to come in in win only because it was the best idea that's what drove the rate of innovation at the pace you're seeing today and it which has never been seen before we at Red Hat we saw the need to bring this innovation to solve real-world problems in the enterprise and I think that's going to be the theme of the show today you're going to see us with our customers and partners talking about and showing you some of those real-world problems that we are sought solving with this open innovation we created rel back then for this for the enterprise it started it's it it wasn't successful because it's scaled it was secure and it was enterprise ready it once again changed the industry but this time through open innovation this gave the hardware ecosystem a software platform this open software platform gave the hardware ecosystem a software platform to build around it Unleashed them the hardware side to compete and thrive it enabled innovation from the OEMs new players building cheaper faster servers even new architectures from armed to power sprung up with this change we have seen an incredible amount of hardware innovation over the last 15 years that same innovation happened on the software side we saw powerful implementations of bare metal Linux distributions out in the market in fact at one point there were 300 there are over 300 distributions out in the market on the foundation of Linux powerful open-source equivalents were even developed in every area of Technology databases middleware messaging containers anything you could imagine innovation just exploded around the Linux platform in innovation it's at the core also drove virtualization both Linux and virtualization led to another area of innovation which you're hearing a lot about now public cloud innovation this innovation started to proceed at a rate that we had never seen before we had never experienced this in the past in this unprecedented speed of innovation and software was now possible because you didn't need a chip foundry in order to innovate you just needed great ideas in the open platform that was out there customers seeing this innovation in the public cloud sparked it sparked their desire to build their own linux based cloud platforms and customers are now are now bringing that cloud efficiency on-premise in their own data centers public clouds demonstrated so much efficiency the data centers and architects wanted to take advantage of it off premise on premise I'm sorry within their own we don't within their own controlled environments this really allowed companies to make the most of existing investments from data centers to hardware they also gained many new advantages from data sovereignty to new flexible agile approaches I want to bring Burr and his team up here to take a look at what building out an on-premise cloud can look like today Bure take it away I am super excited to be with all of you here at Red Hat summit I know we have some amazing things to show you throughout the week but before we dive into this demonstration I want you to take just a few seconds just a quick moment to think about that really important event your life that moment you turned on your first computer maybe it was a trs-80 listen Claire and Atari I even had an 83 b2 at one point but in my specific case I was sitting in a classroom in Hawaii and I could see all the way from Diamond Head to Pearl Harbor so just keep that in mind and I turn on an IBM PC with dual floppies I don't remember issuing my first commands writing my first level of code and I was totally hooked it was like a magical moment and I've been hooked on computers for the last 30 years so I want you to hold that image in your mind for just a moment just a second while we show you the computers we have here on stage let me turn this over to Jay fair and Dini here's our worldwide DevOps manager and he was going to show us his hardware what do you got Jay thank you BER good morning everyone and welcome to Red Hat summit we have so many cool things to show you this week I am so happy to be here and you know my favorite thing about red hat summit is our allowed to kind of share all of our stories much like bird just did we also love to you know talk about the hardware and the technology that we brought with us in fact it's become a bit of a competition so this year we said you know let's win this thing and we actually I think we might have won we brought a cloud with us so right now this is a private cloud for throughout the course of the week we're going to turn this into a very very interesting open hybrid cloud right before your eyes so everything you see here will be real and happening right on this thing right behind me here so thanks for our four incredible partners IBM Dell HP and super micro we've built a very vendor heterogeneous cloud here extra special thanks to IBM because they loaned us a power nine machine so now we actually have multiple architectures in this cloud so as you know one of the greatest benefits to running Red Hat technology is that we run on just about everything and you know I can't stress enough how powerful that is how cost-effective that is and it just makes my life easier to be honest so if you're interested the people that built this actual rack right here gonna be hanging out in the customer success zone this whole week it's on the second floor the lobby there and they'd be glad to show you exactly how they built this thing so let me show you what we actually have in this rack so contained in this rack we have 1056 physical chorus right here we have five and a half terabytes of RAM and just in case we threw 50 terabytes of storage in this thing so burr that's about two million times more powerful than that first machine you boot it up thanks to a PC we're actually capable of putting all the power needs and cooling right in this rack so there's your data center right there you know it occurred to me last night that I can actually pull the power cord on this thing and kick it up a notch we could have the world's first mobile portable hybrid cloud so I'm gonna go ahead and unplug no no no no no seriously it's not unplug the thing we got it working now well Berg gets a little nervous but next year we're rolling this thing around okay okay so to recap multiple vendors check multiple architectures check multiple public clouds plug right into this thing check and everything everywhere is running the same software from Red Hat so that is a giant check so burn Angus why don't we get the demos rolling awesome so we have totally we have some amazing hardware amazing computers on this stage but now we need to light it up and we have Angus Thomas who represents our OpenStack engineering team and he's going to show us what we can do with this awesome hardware Angus thank you Beth so this was an impressive rack of hardware to Joe has bought a pocket stage what I want to talk about today is putting it to work with OpenStack platform director we're going to turn it from a lot of potential into a flexible scalable private cloud we've been using director for a while now to take care of managing hardware and orchestrating the deployment of OpenStack what's new is that we're bringing the same capabilities for on-premise manager the deployment of OpenShift director deploying OpenShift in this way is the best of both worlds it's bare-metal performance but with an underlying infrastructure as a service that can take care of deploying in new instances and scaling out and a lot of the things that we expect from a cloud provider director is running on a virtual machine on Red Hat virtualization at the top of the rack and it's going to bring everything else under control what you can see on the screen right now is the director UI and as you see some of the hardware in the rack is already being managed at the top level we have information about the number of cores in the amount of RAM and the disks that each machine have if we dig in a bit there's information about MAC addresses and IPs and the management interface the BIOS kernel version dig a little deeper and there is information about the hard disks all of this is important because we want to be able to make sure that we put in workloads exactly where we want them Jay could you please power on the two new machines at the top of the rack sure all right thank you so when those two machines come up on the network director is going to see them see that they're new and not already under management and is it immediately going to go into the hardware inspection that populates this database and gets them ready for use so we also have profiles as you can see here profiles are the way that we match the hardware in a machine to the kind of workload that it's suited to this is how we make sure that machines that have all the discs run Seth and machines that have all the RAM when our application workouts for example there's two ways these can be set when you're dealing with a rack like this you could go in an individually tag each machine but director scales up to data centers so we have a rules matching engine which will automatically take the hardware profile of a new machine and make sure it gets tagged in exactly the right way so we can automatically discover new machines on the network and we can automatically match them to a profile that's how we streamline and scale up operations now I want to talk about deploying the software we have a set of validations we've learned over time about the Miss configurations in the underlying infrastructure which can cause the deployment of a multi node distributed application like OpenStack or OpenShift to fail if you have the wrong VLAN tags on a switch port or DHCP isn't running where it should be for example you can get into a situation which is really hard to debug a lot of our validations actually run before the deployment they look at what you're intending to deploy and they check in the environment is the way that it should be and they'll preempts problems and obviously preemption is a lot better than debugging something new that you probably have not seen before is director managing multiple deployments of different things side by side before we came out on stage we also deployed OpenStack on this rack just to keep me honest let me jump over to OpenStack very quickly a lot of our opens that customers will be familiar with this UI and the bare metal deployment of OpenStack on our rack is actually running a set of virtual machines which is running Gluster you're going to see that put to work later on during the summit Jay's gone to an awful lot effort to get this Hardware up on the stage so we're going to use it as many different ways as we can okay let's deploy OpenShift if I switch over to the deployed a deployment plan view there's a few steps first thing you need to do is make sure we have the hardware I already talked about how director manages hardware it's smart enough to make sure that it's not going to attempt to deploy into machines they're already in use it's only going to deploy on machines that have the right profile but I think with the rack that we have here we've got enough next thing is the deployment configuration this is where you get to customize exactly what's going to be deployed to make sure that it really matches your environment if they're external IPs for additional services you can set them here whatever it takes to make sure that the deployment is going to work for you as you can see on the screen we have a set of options around enable TLS for encryption network traffic if I dig a little deeper there are options around enabling ipv6 and network isolation so that different classes of traffic there are over different physical NICs okay then then we have roles now roles this is essentially about the software that's going to be put on each machine director comes with a set of roles for a lot of the software that RedHat supports and you can just use those or you can modify them a little bit if you need to add a monitoring agent or whatever it might be or you can create your own custom roles director has quite a rich syntax for custom role definition and custom Network topologies whatever it is you need in order to make it work in your environment so the rawls that we have right now are going to give us a working instance of openshift if I go ahead and click through the validations are all looking green so right now I can click the button start to the deploy and you will see things lighting up on the rack directors going to use IPMI to reboot the machines provisioned and with a trail image was the containers on them and start up the application stack okay so one last thing once the deployment is done you're going to want to keep director around director has a lot of capabilities around what we call de to operational management bringing in new Hardware scaling out deployments dealing with updates and critically doing upgrades as well so having said all of that it is time for me to switch over to an instance of openshift deployed by a director running on bare metal on our rack and I need to hand this over to our developer team so they can show what they can do it thank you that is so awesome Angus so what you've seen now is going from bare metal to the ultimate private cloud with OpenStack director make an open shift ready for our developers to build their next generation applications thank you so much guys that was totally awesome I love what you guys showed there now I have the honor now I have the honor of introducing a very special guest one of our earliest OpenShift customers who understands the necessity of the private cloud inside their organization and more importantly they're fundamentally redefining their industry please extend a warm welcome to deep mar Foster from Amadeus well good morning everyone a big thank you for having armadillos here and myself so as it was just set I'm at Mario's well first of all we are a large IT provider in the travel industry so serving essentially Airlines hotel chains this distributors like Expedia and others we indeed we started very early what was OpenShift like a bit more than three years ago and we jumped on it when when Retta teamed with Google to bring in kubernetes into this so let me quickly share a few figures about our Mario's to give you like a sense of what we are doing and the scale of our operations so some of our key KPIs one of our key metrics is what what we call passenger borders so that's the number of customers that physically board a plane over the year so through our systems it's roughly 1.6 billion people checking in taking the aircrafts on under the Amarillo systems close to 600 million travel agency bookings virtually all airlines are on the system and one figure I want to stress out a little bit is this one trillion availability requests per day that's when I read this figure my mind boggles a little bit so this means in continuous throughput more than 10 million hits per second so of course these are not traditional database transactions it's it's it's highly cached in memory and these applications are running over like more than 100,000 course so it's it's it's really big stuff so today I want to give some concrete feedback what we are doing so I have chosen two applications products of our Mario's that are currently running on production in different in different hosting environments as the theme here is of this talk hybrid cloud and so I want to give some some concrete feedback of how we architect the applications and of course it stays relatively high level so here I have taken one of our applications that is used in the hospitality environment so it's we have built this for a very large US hotel chain and it's currently in in full swing brought into production so like 30 percent of the globe or 5,000 plus hotels are on this platform not so here you can see that we use as the path of course on openshift on that's that's the most central piece of our hybrid cloud strategy on the database side we use Oracle and Couchbase Couchbase is used for the heavy duty fast access more key value store but also to replicate data across two data centers in this case it's running over to US based data centers east and west coast topology that are fit so run by Mario's that are fit with VMware on for the virtualization OpenStack on top of it and then open shift to host and welcome the applications on the right hand side you you see the kind of tools if you want to call them tools that we use these are the principal ones of course the real picture is much more complex but in essence we use terraform to map to the api's of the underlying infrastructure so they are obviously there are differences when you run on OpenStack or the Google compute engine or AWS Azure so some some tweaking is needed we use right at ansible a lot we also use puppet so you can see these are really the big the big pieces of of this sense installation and if we look to the to the topology again very high high level so these two locations basically map the data centers of our customers so they are in close proximity because the response time and the SLA is of this application is are very tight so that's an example of an application that is architectures mostly was high ability and high availability in minds not necessarily full global worldwide scaling but of course it could be scaled but here the idea is that we can swing from one data center to the unit to the other in matters of of minutes both take traffic data is fully synchronized across those data centers and while the switch back and forth is very fast the second example I have taken is what we call the shopping box this is when people go to kayak or Expedia and they're getting inspired where they want to travel to this is really the piece that shoots most of transit of the transactions into our Mario's so we architect here more for high scalability of course availability is also a key but here scaling and geographical spread is very important so in short it runs partially on-premise in our Amarillo Stata Center again on OpenStack and we we deploy it mostly in the first step on the Google compute engine and currently as we speak on Amazon on AWS and we work also together with Retta to qualify the whole show on Microsoft Azure here in this application it's it's the same building blocks there is a large swimming aspect to it so we bring Kafka into this working with records and another partner to bring Kafka on their open shift because at the end we want to use open shift to administrate the whole show so over time also databases and the topology here when you look to the physical deployment topology while it's very classical we use the the regions and the availability zone concept so this application is spread over three principal continental regions and so it's again it's a high-level view with different availability zones and in each of those availability zones we take a hit of several 10,000 transactions so that was it really in very short just to give you a glimpse on how we implement hybrid clouds I think that's the way forward it gives us a lot of freedom and it allows us to to discuss in a much more educated way with our customers that sometimes have already deals in place with one cloud provider or another so for us it's a lot of value to set two to leave them the choice basically what up that was a very quick overview of what we are doing we were together with records are based on open shift essentially here and more and more OpenStack coming into the picture hope you found this interesting thanks a lot and have a nice summer [Applause] thank you so much deeper great great solution we've worked with deep Marv and his team for a long for a long time great solution so I want to take us back a little bit I want to circle back I sort of ended talking a little bit about the public cloud so let's circle back there you know even so even though some applications need to run in various footprints on premise there's still great gains to be had that for running certain applications in the public cloud a public cloud will be as impactful to to the industry as as UNIX era was of computing was but by itself it'll have some of the same limitations and challenges that that model had today there's tremendous cloud innovation happening in the public cloud it's being driven by a handful of massive companies and much like the innovation that sundeck HP and others drove in a you in the UNIX era of community of computing many customers want to take advantage of the best innovation no matter where it comes from buddy but as they even eventually saw in the UNIX era they can't afford the best innovation at the cost of a siloed operating environment with the open community we are building a hybrid application platform that can give you access to the best innovation no matter which vendor or which cloud that it comes from letting public cloud providers innovate and services beyond what customers or anyone can one provider can do on their own such as large scale learning machine learning or artificial intelligence built on the data that's unique probably to that to that one cloud but consumed in a common way for the end customer across all applications in any environment on any footprint in in their overall IT infrastructure this is exactly what rel brought brought to our customers in the UNIX era of computing that consistency across any of those footprints obviously enterprises will have applications for all different uses some will live on premise some in the cloud hybrid cloud is the only practical way forward I think you've been hearing that from us for a long time it is the only practical way forward and it'll be as impactful as anything we've ever seen before I want to bring Byrne his team back to see a hybrid cloud deployment in action burr [Music] all right earlier you saw what we did with taking bare metal and lighting it up with OpenStack director and making it openshift ready for developers to build their next generation applications now we want to show you when those next turn and generation applications and what we've done is we take an open shift and spread it out and installed it across Asia and Amazon a true hybrid cloud so with me on stage today as Ted who's gonna walk us through an application and Brent Midwood who's our DevOps engineer who's gonna be making sure he's monitoring on the backside that we do make sure we do a good job so at this point Ted what have you got for us Thank You BER and good morning everybody this morning we are running on the stage in our private cloud an application that's providing its providing fraud detection detect serves for financial transactions and our customer base is rather large and we occasionally take extended bursts of traffic of heavy traffic load so in order to keep our latency down and keep our customers happy we've deployed extra service capacity in the public cloud so we have capacity with Microsoft Azure in Texas and with Amazon Web Services in Ohio so we use open chip container platform on all three locations because openshift makes it easy for us to deploy our containerized services wherever we want to put them but the question still remains how do we establish seamless communication across our entire enterprise and more importantly how do we balance the workload across these three locations in such a way that we efficiently use our resources and that we give our customers the best possible experience so this is where Red Hat amq interconnect comes in as you can see we've deployed a MQ interconnect alongside our fraud detection applications in all three locations and if I switch to the MQ console we'll see the topology of the app of the network that we've created here so the router inside the on stage here has made connections outbound to the public routers and AWS and Azure these connections are secured using mutual TLS authentication and encrypt and once these connections are established amq figures out the best way auda matically to route traffic to where it needs to get to so what we have right now is a distributed reliable broker list message bus that expands our entire enterprise now if you want to learn more about this make sure that you catch the a MQ breakout tomorrow at 11:45 with Jack Britton and David Ingham let's have a look at the message flow and we'll dive in and isolate the fraud detection API that we're interested in and what we see is that all the traffic is being handled in the private cloud that's what we expect because our latencies are low and they're acceptable but now if we take a little bit of a burst of increased traffic we're gonna see that an EQ is going to push a little a bi traffic out onto the out to the public cloud so as you're picking up some of the load now to keep the Layton sees down now when that subsides as your finishes up what it's doing and goes back offline now if we take a much bigger load increase you'll see two things first of all asher is going to take a bigger proportion than it did before and Amazon Web Services is going to get thrown into the fray as well now AWS is actually doing less work than I expected it to do I expected a little bit of bigger a slice there but this is a interesting illustration of what's going on for load balancing mq load balancing is sending requests to the services that have the lowest backlog and in order to keep the Layton sees as steady as possible so AWS is probably running slowly for some reason and that's causing a and Q to push less traffic its way now the other thing you're going to notice if you look carefully this graph fluctuate slightly and those fluctuations are caused by all the variances in the network we have the cloud on stage and we have clouds in in the various places across the country there's a lot of equipment locked layers of virtualization and networking in between and we're reacting in real-time to the reality on the digital street so BER what's the story with a to be less I noticed there's a problem right here right now we seem to have a little bit performance issue so guys I noticed that as well and a little bit ago I actually got an alert from red ahead of insights letting us know that there might be some potential optimizations we could make to our environment so let's take a look at insights so here's the Red Hat insights interface you can see our three OpenShift deployments so we have the set up here on stage in San Francisco we have our Azure deployment in Texas and we also have our AWS deployment in Ohio and insights is highlighting that that deployment in Ohio may have some issues that need some attention so Red Hat insights collects anonymized data from manage systems across our customer environment and that gives us visibility into things like vulnerabilities compliance configuration assessment and of course Red Hat subscription consumption all of this is presented in a SAS offering so it's really really easy to use it requires minimal infrastructure upfront and it provides an immediate return on investment what insights is showing us here is that we have some potential issues on the configuration side that may need some attention from this view I actually get a look at all the systems in our inventory including instances and containers and you can see here on the left that insights is highlighting one of those instances as needing some potential attention it might be a candidate for optimization this might be related to the issues that you were seeing just a minute ago insights uses machine learning and AI techniques to analyze all collected data so we combine collected data from not only the system's configuration but also with other systems from across the Red Hat customer base this allows us to compare ourselves to how we're doing across the entire set of industries including our own vertical in this case the financial services industry and we can compare ourselves to other customers we also get access to tailored recommendations that let us know what we can do to optimize our systems so in this particular case we're actually detecting an issue here where we are an outlier so our configuration has been compared to other configurations across the customer base and in this particular instance in this security group were misconfigured and so insights actually gives us the steps that we need to use to remediate the situation and the really neat thing here is that we actually get access to a custom ansible playbook so if we want to automate that type of a remediation we can use this inside of Red Hat ansible tower Red Hat satellite Red Hat cloud forms it's really really powerful the other thing here is that we can actually apply these recommendations right from within the Red Hat insights interface so with just a few clicks I can select all the recommendations that insights is making and using that built-in ansible automation I can apply those recommendations really really quickly across a variety of systems this type of intelligent automation is really cool it's really fast and powerful so really quickly here we're going to see the impact of those changes and so we can tell that we're doing a little better than we were a few minutes ago when compared across the customer base as well as within the financial industry and if we go back and look at the map we should see that our AWS employment in Ohio is in a much better state than it was just a few minutes ago so I'm wondering Ted if this had any effect and might be helping with some of the issues that you were seeing let's take a look looks like went green now let's see what it looks like over here yeah doesn't look like the configuration is taking effect quite yet maybe there's some delay awesome fantastic the man yeah so now we're load balancing across the three clouds very much fantastic well I have two minute Ted I truly love how we can route requests and dynamically load transactions across these three clouds a truly hybrid cloud native application you guys saw here on on stage for the first time and it's a fully portable application if you build your applications with openshift you can mover from cloud to cloud to cloud on stage private all the way out to the public said it's totally awesome we also have the application being fully managed by Red Hat insights I love having that intelligence watching over us and ensuring that we're doing everything correctly that is fundamentally awesome thank you so much for that well we actually have more to show you but you're going to wait a few minutes longer right now we'd like to welcome Paul back to the stage and we have a very special early Red Hat customer an Innovation Award winner from 2010 who's been going boldly forward with their open hybrid cloud strategy please give a warm welcome to Monty Finkelstein from Citigroup [Music] [Music] hi Marty hey Paul nice to see you thank you very much for coming so thank you for having me Oh our pleasure if you if you wanted to we sort of wanted to pick your brain a little bit about your experiences and sort of leading leading the charge in computing here so we're all talking about hybrid cloud how has the hybrid cloud strategy influenced where you are today in your computing environment so you know when we see the variable the various types of workload that we had an hour on from cloud we see the peaks we see the valleys we see the demand on the environment that we have we really determined that we have to have a much more elastic more scalable capability so we can burst and stretch our environments to multiple cloud providers these capabilities have now been proven at City and of course we consider what the data risk is as well as any regulatory requirement so how do you how do you tackle the complexity of multiple cloud environments so every cloud provider has its own unique set of capabilities they have they're own api's distributions value-added services we wanted to make sure that we could arbitrate between the different cloud providers maintain all source code and orchestration capabilities on Prem to drive those capabilities from within our platforms this requires controlling the entitlements in a cohesive fashion across our on Prem and Wolfram both for security services automation telemetry as one seamless unit can you talk a bit about how you decide when you to use your own on-premise infrastructure versus cloud resources sure so there are multiple dimensions that we take into account right so the first dimension we talk about the risk so low risk - high risk and and really that's about the data classification of the environment we're talking about so whether it's public or internal which would be considered low - ooh confidential PII restricted sensitive and so on and above which is really what would be considered a high-risk the second dimension would be would focus on demand volatility and responsiveness sensitivity so this would range from low response sensitivity and low variability of the type of workload that we have to the high response sensitivity and high variability of the workload the first combination that we focused on is the low risk and high variability and high sensitivity for response type workload of course any of the workloads we ensure that we're regulatory compliant as well as we achieve customer benefits with within this environment so how can we give developers greater control of their their infrastructure environments and still help operations maintain that consistency in compliance so the main driver is really to use the public cloud is scale speed and increased developer efficiencies as well as reducing cost as well as risk this would mean providing develop workspaces and multiple environments for our developers to quickly create products for our customers all this is done of course in a DevOps model while maintaining the source and artifacts registry on-prem this would allow our developers to test and select various middleware products another product but also ensure all the compliance activities in a centrally controlled repository so we really really appreciate you coming by and sharing that with us today Monte thank you so much for coming to the red echo thanks a lot thanks again tamati I mean you know there's these real world insight into how our products and technologies are really running the businesses today that's that's just the most exciting part so thank thanks thanks again mati no even it with as much progress as you've seen demonstrated here and you're going to continue to see all week long we're far from done so I want to just take us a little bit into the path forward and where we we go today we've talked about this a lot innovation today is driven by open source development I don't think there's any question about that certainly not in this room and even across the industry as a whole that's a long way that we've come from when we started our first summit 14 years ago with over a million open source projects out there this unit this innovation aggregates into various community platforms and it finally culminates in commercial open source based open source developed products these products run many of the mission-critical applications in business today you've heard just a couple of those today here on stage but it's everywhere it's running the world today but to make customers successful with that interact innovation to run their real-world business applications these open source products have to be able to leverage increase increasingly complex infrastructure footprints we must also ensure a common base for the developer and ultimately the application no matter which footprint they choose as you heard mati say the developers want choice here no matter which no matter which footprint they are ultimately going to run their those applications on they want that flexibility from the data center to possibly any public cloud out there in regardless of whether that application was built yesterday or has been running the business for the last 10 years and was built on 10-year old technology this is the flexibility that developers require today but what does different infrastructure we may require different pieces of the technical stack in that deployment one example of this that Effects of many things as KVM which provides the foundation for many of those use cases that require virtualization KVM offers a level of consistency from a technical perspective but rel extends that consistency to add a level of commercial and ecosystem consistency for the application across all those footprints this is very important in the enterprise but while rel and KVM formed the foundation other technologies are needed to really satisfy the functions on these different footprints traditional virtualization has requirements that are satisfied by projects like overt and products like Rev traditional traditional private cloud implementations has requirements that are satisfied on projects like OpenStack and products like Red Hat OpenStack platform and as applications begin to become more container based we are seeing many requirements driven driven natively into containers the same Linux in different forms provides this common base across these four footprints this level of compatible compatibility is critical to operators who must best utilize the infinite must better utilize secure and deploy the infrastructure that they have and they're responsible for developers on the other hand they care most about having a platform that can creates that consistency for their applications they care about their services and the services that they need to consume within those applications and they don't want limitations on where they run they want service but they want it anywhere not necessarily just from Amazon they want integration between applications no matter where they run they still want to run their Java EE now named Jakarta EE apps and bring those applications forward into containers and micro services they need able to orchestrate these frameworks and many more across all these different footprints in a consistent secure fashion this creates natural tension between development and operations frankly customers amplify this tension with organizational boundaries that are holdover from the UNIX era of computing it's really the job of our platforms to seamlessly remove these boundaries and it's the it's the goal of RedHat to seamlessly get you from the old world to the new world we're gonna show you a really cool demo demonstration now we're gonna show you how you can automate this transition first we're gonna take a Windows virtual machine from a traditional VMware deployment we're gonna convert it into a KVM based virtual machine running in a container all under the kubernetes umbrella this makes virtual machines more access more accessible to the developer this will accelerate the transformation of those virtual machines into cloud native container based form well we will work this prot we will worked as capability over the product line in the coming releases so we can strike the balance of enabling our developers to move in this direction we want to be able to do this while enabling mission-critical operations to still do their job so let's bring Byrne his team back up to show you this in action for one more thanks all right what Red Hat we recognized that large organizations large enterprises have a substantial investment and legacy virtualization technology and this is holding you back you have thousands of virtual machines that need to be modernized so what you're about to see next okay it's something very special with me here on stage we have James Lebowski he's gonna be walking us through he's represents our operations folks and he's gonna be walking us through a mass migration but also is Itamar Hine who's our lead developer of a very special application and he's gonna be modernizing container izing and optimizing our application all right so let's get started James thanks burr yeah so as you can see I have a typical VMware environment here I'm in the vSphere client I've got a number of virtual machines a handful of them that make up my one of my applications for my development environment in this case and what I want to do is migrate those over to a KVM based right at virtualization environment so what I'm gonna do is I'm gonna go to cloud forms our cloud management platform that's our first step and you know cloud forms actually already has discovered both my rev environment and my vSphere environment and understands the compute network and storage there so you'll notice one of the capabilities we built is this new capability called migrations and underneath here I could begin to there's two steps and the first thing I need to do is start to create my infrastructure mappings what this will allow me to do is map my compute networking storage between vSphere and Rev so cloud forms understands how those relate let's go ahead and create an infrastructure mapping I'll call that summit infrastructure mapping and then I'm gonna begin to map my two environments first the compute so the clusters here next the data stores so those virtual machines happen to live on datastore - in vSphere and I'll target them a datastore data to inside of my revenue Arman and finally my networks those live on network 100 so I'll map those from vSphere to rover so once my infrastructure is map the next step I need to do is actually begin to create a plan to migrate those virtual machines so I'll continue to the plan wizard here I'll select the infrastructure mapping I just created and I'll select migrate my development environment from those virtual machines to Rev and then I need to import a CSV file the CSV file is going to contain a list of all the virtual machines that I want to migrate that were there and that's it once I hit create what's going to happen cloud forms is going to begin in an automated fashion shutting down those virtual machines begin converting them taking care of all the minutia that you'd have to do manually it's gonna do that all automatically for me so I don't have to worry about all those manual interactions and no longer do I have to go manually shut them down but it's going to take care of that all for me you can see the migrations kicked off here this is the I've got the my VMs are migrating here and if I go back to the screen here you can see that we're gonna start seeing those shutdown okay awesome but as people want to know more information about this how would they dive deeper into this technology later this week yeah it's a great question so we have a workload portability session in the hybrid cloud on Wednesday if you want to see a presentation that deep dives into this topic and how some of the methodologies to migrate and then on Thursday we actually have a hands-on lab it's the IT optimization VM migration lab that you can check out and as you can see those are shutting down here yeah we see a powering off right now that's fantastic absolutely so if I go back now that's gonna take a while you got to convert all the disks and move them over but we'll notice is previously I had already run one migration of a single application that was a Windows virtual machine running and if I browse over to Red Hat virtualization I can see on the dashboard here I could browse to virtual machines I have migrated that Windows virtual machine and if I open up a tab I can now browse to my Windows virtual machine which is running our wingtip toy store application our sample application here and now my VM has been moved over from Rev to Vita from VMware to Rev and is available for Itamar all right great available to our developers all right Itamar what are you gonna do for us here well James it's great that you can save cost by moving from VMware to reddit virtualization but I want to containerize our application and with container native virtualization I can run my virtual machine on OpenShift like any other container using Huebert a kubernetes operator to run and manage virtual machines let's look at the open ship service catalog you can see we have a new virtualization section here we can import KVM or VMware virtual machines or if there are already loaded we can create new instances of them for the developer to work with just need to give named CPU memory we can do other virtualization parameters and create our virtual machines now let's see how this looks like in the openshift console the cool thing about KVM is virtual machines are just Linux processes so they can act and behave like other open shipped applications we build in more than a decade of virtualization experience with KVM reddit virtualization and OpenStack and can now benefit from kubernetes and open shift to manage and orchestrate our virtual machines since we know this virtual machine this container is actually a virtual machine we can do virtual machine stuff with it like shutdown reboot or open a remote desktop session to it but we can also see this is just a container like any other container in openshift and even though the web application is running inside a Windows virtual machine the developer can still use open shift mechanisms like services and routes let's browse our web application using the OpenShift service it's the same wingtip toys application but this time the virtual machine is running on open shift but we're not done we want to containerize our application since it's a Windows virtual machine we can open a remote desktop session to it we see we have here Visual Studio and an asp.net application let's start container izing by moving the Microsoft sequel server database from running inside the Windows virtual machine to running on Red Hat Enterprise Linux as an open shipped container we'll go back to the open shipped Service Catalog this time we'll go to the database section and just as easily we'll create a sequel server container just need to accept the EULA provide password and choose the Edition we want and create a database and again we can see the sequel server is just another container running on OpenShift now let's take let's find the connection details for our database to keep this simple we'll take the IP address of our database service go back to the web application to visual studio update the IP address in the connection string publish our application and go back to browse it through OpenShift fortunately for us the user experience team heard we're modernizing our application so they pitched in and pushed new icons to use with our containerized database to also modernize the look and feel it's still the same wingtip toys application it's running in a virtual machine on openshift but it's now using a containerized database to recap we saw that we can run virtual machines natively on openshift like any other container based application modernize and mesh them together we containerize the database but we can use the same approach to containerize any part of our application so some items here to deserve repeating one thing you saw is Red Hat Enterprise Linux burning sequel server in a container on open shift and you also saw Windows VM where the dotnet native application also running inside of open ships so tell us what's special about that that seems pretty crazy what you did there exactly burr if we take a look under the hood we can use the kubernetes commands to see the list of our containers in this case the sequel server and the virtual machine containers but since Q Bert is a kubernetes operator we can actually use kubernetes commands like cube Cpl to list our virtual machines and manage our virtual machines like any other entity in kubernetes I love that so there's your crew meta gem oh we can see the kind says virtual machine that is totally awesome now people here are gonna be very excited about what they just saw we're gonna get more information and when will this be coming well you know what can they do to dive in this will be available as part of reddit Cloud suite in tech preview later this year but we are looking for early adopters now so give us a call also come check our deep dive session introducing container native virtualization Thursday 2:00 p.m. awesome that is so incredible so we went from the old to the new from the close to the open the Red Hat way you're gonna be seeing more from our demonstration team that's coming Thursday at 8 a.m. do not be late if you like what you saw this today you're gonna see a lot more of that going forward so we got some really special things in store for you so at this point thank you so much in tomorrow thank you so much you guys are awesome yeah now we have one more special guest a very early adopter of Red Hat Enterprise Linux we've had over a 12-year partnership and relationship with this organization they've been a steadfast Linux and middleware customer for many many years now please extend a warm welcome to Raj China from the Royal Bank of Canada thank you thank you it's great to be here RBC is a large global full-service is back we have the largest bank in Canada top 10 global operate in 30 countries and run five key business segments personal commercial banking investor in Treasury services capital markets wealth management and insurance but honestly unless you're in the banking segment those five business segments that I just mentioned may not mean a lot to you but what you might appreciate is the fact that we've been around in business for over 150 years we started our digital transformation journey about four years ago and we are focused on new and innovative technologies that will help deliver the capabilities and lifestyle our clients are looking for we have a very simple vision and we often refer to it as the digitally enabled bank of the future but as you can appreciate transforming a hundred fifty year old Bank is not easy it certainly does not happen overnight to that end we had a clear unwavering vision a very strong innovation agenda and most importantly a focus towards a flawless execution today in banking business strategy and IT strategy are one in the same they are not two separate things we believe that in order to be the number one bank we have to have the number one tactic there is no question that most of today's innovations happens in the open source community RBC relies on RedHat as a key partner to help us consume these open source innovations in a manner that it meets our enterprise needs RBC was an early adopter of Linux we operate one of the largest footprints of rel in Canada same with tables we had tremendous success in driving cost out of infrastructure by partnering with rahat while at the same time delivering a world-class hosting service to your business over our 12 year partnership Red Hat has proven that they have mastered the art of working closely with the upstream open source community understanding the needs of an enterprise like us in delivering these open source innovations in a manner that we can consume and build upon we are working with red hat to help increase our agility and better leverage public and private cloud offerings we adopted virtualization ansible and containers and are excited about continuing our partnership with Red Hat in this journey throughout this journey we simply cannot replace everything we've had from the past we have to bring forward these investments of the past and improve upon them with new and emerging technologies it is about utilizing emerging technologies but at the same time focusing on the business outcome the business outcome for us is serving our clients and delivering the information that they are looking for whenever they need it and in whatever form factor they're looking for but technology improvements alone are simply not sufficient to do a digital transformation creating the right culture of change and adopting new methodologies is key we introduced agile and DevOps which has boosted the number of adult projects at RBC and increase the frequency at which we do new releases to our mobile app as a matter of fact these methodologies have enabled us to deliver apps over 20x faster than before the other point about around culture that I wanted to mention was we wanted to build an engineering culture an engineering culture is one which rewards curiosity trying new things investing in new technologies and being a leader not necessarily a follower Red Hat has been a critical partner in our journey to date as we adopt elements of open source culture in engineering culture what you seen today about red hearts focus on new technology innovations while never losing sight of helping you bring forward the investments you've already made in the past is something that makes Red Hat unique we are excited to see red arts investment in leadership in open source technologies to help bring the potential of these amazing things together thank you that's great the thing you know seeing going from the old world to the new with automation so you know the things you've seen demonstrated today they're they're they're more sophisticated than any one company could ever have done on their own certainly not by using a proprietary development model because of this it's really easy to see why open source has become the center of gravity for enterprise computing today with all the progress open-source has made we're constantly looking for new ways of accelerating that into our products so we can take that into the enterprise with customers like these that you've met what you've met today now we recently made in addition to the Red Hat family we brought in core OS to the Red Hat family and you know adding core OS has really been our latest move to accelerate that innovation into our products this will help the adoption of open shift container platform even deeper into the enterprise and as we did with the Linux core platform in 2002 this is just exactly what we did with with Linux back then today we're announcing some exciting new technology directions first we'll integrate the benefits of automated operations so for example you'll see dramatic improvements in the automated intelligence about the state of your clusters in OpenShift with the core OS additions also as part of open shift will include a new variant of rel called Red Hat core OS maintaining the consistency of rel farhat for the operation side of the house while allowing for a consumption of over-the-air updates from the kernel to kubernetes later today you'll hear how we are extending automated operations beyond customers and even out to partners all of this starting with the next release of open shift in July now all of this of course will continue in an upstream open source innovation model that includes continuing container linux for the community users today while also evolving the commercial products to bring that innovation out to the enterprise this this combination is really defining the platform of the future everything we've done for the last 16 years since we first brought rel to the commercial market because get has been to get us just to this point hybrid cloud computing is now being deployed multiple times in enterprises every single day all powered by the open source model and powered by the open source model we will continue to redefine the software industry forever no in 2002 with all of you we made Linux the choice for enterprise computing this changed the innovation model forever and I started the session today talking about our prediction of seven years ago on the future being open we've all seen so much happen in those in those seven years we at Red Hat have celebrated our 25th anniversary including 16 years of rel and the enterprise it's now 2018 open hybrid cloud is not only a reality but it is the driving model in enterprise computing today and this hybrid cloud world would not even be possible without Linux as a platform in the open source development model a build around it and while we have think we may have accomplished a lot in that time and we may think we have changed the world a lot we have but I'm telling you the best is yet to come now that Linux and open source software is firmly driving that innovation in the enterprise what we've accomplished today and up till now has just set the stage for us together to change the world once again and just as we did with rel more than 15 years ago with our partners we will make hybrid cloud the default in the enterprise and I will take that bet every single day have a great show and have fun watching the future of computing unfold right in front of your eyes see you later [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] anytime [Music]

>> Voiceover: Live from Las Vegas, it's The Cube, covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back everyone to The Cube's live coverage of ServiceNow Knowledge 2018, #Know18. I'm Rebecca Knight your host, along with my co-host Dave Vellante. We have two guests joining us, we have Mitch Kenfield who is an Advisory Principal CIO advisory at KPMG, And Adrian Hubbard, Service and Process Manager at Linklaters, thanks so much for joining us. >> Thank you. >> Thank you. >> Adrian, I want to start with you. Can you describe for our viewers what was sort of happening, what was going on at Linklaters, sort of the inflection point when you realized you needed to step up your game in this arena, and just lay that our for our viewers. >> Yeah, I think, from Linklaters' point of view, we're very much, kind of, use the telephone more than anything else, it's very much a contact organization through voice. And we wanted to implement a platform that would engage the users in a different way, more to be self-serving, more chats, more routes to service, if you like. And we saw ServiceNow as the right tool for that. We did some due diligence, an RFP process, but that wasn't enough, we had to build a strong business case to make sure we were doing the right things. And that's where we kind of reached out to KPMG to see what they could offer us in this space. >> Talk more about your business, and-- >> So we're a global firm, we're kind of part of the magical circle, so there's four or five in that arena we call our strong peers. And yeah, as I say, fairness can be very challenging, their day themselves needs to be very efficient and very effective, and they don't always want to have to tell Serve. So one of our challenges is the more time they spend with us the less time they're billing their clients, which is obviously the revenue of the firm. But then when you've got 450 plus partners they all feel they want to run the firm in a way that perhaps is regional, office-based. So some of those challenges play into delivering service also. >> You talked about doing your due diligence, how did you go about that? What was the, what was your process? >> So we engaged with a consultancy firm to help us through the process. Through that, we worked out where do we want to get to, our vision. We short-listed some top-set firms, there was about three or four on the list that we knew met the requirement. So we then went through the process of the next layer down and series of workshops with each provider. Obviously, there was a cost model, we got supplier guys involved from a contract perspective, tried to get the best price. But I think deep down we always felt ServiceNow was the right fit for us. And I've been at Linklaters six years, when I first joined Linklaters that time ago, we went through the same process. We chose the different tool then, but ServiceNow was in the list and we really would have liked to have gone there six years ago. But I think ServiceNow have improved a lot during that time, and now was the right time for us to choose them. >> It was the one that got away, and now you've brought it back. >> Absolutely, yeah, yeah. >> So, Linklaters reached out to you, so then describe about, describe how you sort of shepherded them through the process? >> Yeah, so they had reached out in our London office, and I guess I had happened to be there and jumped on the phone with them, and first of all, when Adrian mentions about the culture of a law firm, so we are a consulting firm you know, consultants and tax and audit and finance folks, so we kind of understand that, it's kind of like the industry where everybody's the boss and nobody's the boss. So we jumped on the phone, and one thing that I mentioned as Adrian was describing, is that we see this space as an opportunity to truly change the way the technology business is running, and therefore change the ultimate business. >> Adrian: Yeah. >> And so, we tell our clients a lot, if you're just going to kind of implement, it might not be the right thing for you. But if you're ready to transform the way you run technology, and the way that supports the business, we think we can help, and we brought something to them that we call Powered IT, which I can give some details on, but just at the highest levels it's our view of an accelerated transformation that includes some technology components, but more than that includes operating models and process to say let's not reinvent things, let's bring to you what's good, and that way we can spend our time focusing on the specifics for you, to get you to the business result you're looking for, and that was kind of that first conversation we had. >> Sure. >> The word "agile transformation" is popping into my head. It's such a common theme today, but is it relevant to what we're talking about? >> Yeah, absolutely. So, I'll start, Adrian, and maybe you can give your perspective on it. When we bring our view, and again, we call it Powered just as a tag, but really what it is, it's an acceleration. It's the components from an organizational aspect's process, metrics, supporting ServiceNow with some kind of near-the-box configurations to add in to that. And then, to your question, it's how do we deliver that in an agile way, where you see it constantly. We don't take six months before we show something, you're seeing it regularly and we can course correct and tweak to say we have a limited amount of effort we can spend, let's spend that in that agile methodology for things that transform you sooner and get it done. Would you, what was y'all's reaction? >> Yeah, to add to that, so what's really important for me is that we hadn't worked with KPMG before although, we were talking early doors, we didn't know what this Powered IT was, what it would bring us. So we made sure we had a number of kind of pre-sales workshops, where I could see the product and they've got a very strong environment where I could see exactly was I was going to get at the end, which is important for me because there's always a risky element, going in with a new incumbent, it was going to be success of this, or not, and I had to be sure that we did the right risk assessment. So actually, to be able to be provided with that kind of out-of-the-box experience, because often you go into sales call, or into the RFP process, and then you come out the back end of it and actually you see, actually getting what you saw in that sales demo. So it's important that we did that extra look. So I think we're able to see the end product, if you like, and then through talking with Mitch and the team and the UK guys, we then knew what the approach would be, very agile and quite aggressive as well. We delivered end-to-end in 14 weeks, which, considering that it took us from the old tool to ServiceNow, it took us from the old way of working to a new way of working on day one. We switched the old tool off on day one. There was a lot going on, it was... you know, we had to really stick to scope, as well, to manage mistake holders. >> I'm interested in how you managed risk, because that's the one thing that popped into my head. When you transform and your business processes are affected you know, you want to move fast, but there are dependencies. So how did you identify those, how did you guys manage the risks? >> I think, in terms of... We were quite strong on what our service improvement plans were looking like, we knew that we needed a new tool, we knew the tool would unlock it, but we didn't know is the extras that KPMG would bring through the Powered IT. So it's more than just the tool set itself, it's actually the processes and the policies. So because we're able to look at those day one, we knew what the end product was going to be. And plus we went with the preferred Powered IT platform. What we didn't try to do was to impose our current way of thinking. We took the KPMG way of thinking, which was the less risky approach, it meant that we weren't customizing, which was a big danger for us, potentially. So we also knew it was fully supported, because KPMG have put this Powered IT module together, built with other clients as well, so we knew we were adopting best practices from other clients. But actually it was fitting, the way we needed to get to from our vision. I think the thing that made me a little bit nervous was we'd been through a number of maturity assessments over the years that said our processes were quite mature. Where we were weak, really, was some of the reporting, the visibility of performance. So again, but they were kind of the key things from risk assessment, let's make sure the key things we could see working. And then we knew the risk was less. But, you know, as always, when you engage with a new incumbent for the first time, we had to make sure that we met the team as well, that was also a key part for us, to make sure the people we'd be working with, from day one, we met them at the beginning. And they stayed throughout. So that was also very good for us. >> So, Adrian, I'm curious about your particular experience, and then Mitch, I wonder if you could chime in on other clients that you might see. You always hear, "You got to have buy-in from the C-suite, top down." But when you go change the operating model, I often hear, the senior management goes, and then the rest of the company's like, "Well, we got to run the business," and they're trying to catch up. >> Yep. >> Is that a common problem? How do you guys deal with that? >> I think our senior team have been in place, they've been very supportive. There hasn't really been an issue there. And a lot of the senior team also supported the decision to go ServiceNow, which is important for me. I have to say, not all parts of the IT organization thought it was the right decision, but we had to demonstrate that as we went through, and the series of workshops was important, early doors. So we made sure we engaged the right stakeholders, they felt part of the whole solution end-to-end. And yes, people tried to push the scope at times, tried to scope creep, but actually senior management were very good and supportive of me to stick to scope. Stick to what we've agreed to do, help me push back certain people when they became challenging. And because we stuck to that scope, we delivered on-time. The fear would've been, as you know, you customize, you go off track-- >> I think what we see, to your analogy and I think your degree, you have to have that senior commitment. There can't be a question of why. But what breaks down often is that kind of next layer of key managers and stakeholders that maybe didn't show up to that meeting, and you know, didn't, you know... And those are the little things that can kind of take it off rail. And to your question earlier about agile, the great thing about a well-executed agile methodology is not about doing agile configuration it's about doing agile business transformation. It's about having regular interaction points where those stakeholders are involved in the process. And every day they're in those sessions and they're seeing something, and they get the chance, and we connect together. And that's what gets you to the end of it, to where instead of just in 14 weeks, we deployed a technology that kind of feels the same way we used to work. You deploy a technology and people are doing things different, and that's a key aspect. >> Dave: Lot of repetition. >> A lot of repetition. >> A lot of overcommunicating-- >> And we tell our clients a lot, it's going to be a rough 14 weeks, because you're going to be involved. This isn't the old-- >> Adrian: You didn't tell me that. >> Well (laughs). It's not where you're going to give me requirements we're going to go away and build something and hope we got it right and you're going to say, like you said, "That's not, wait, I thought I was going to get..." We're going to be in it and the teams are working collaboratively, stand up meetings, and all those kind of things. And it can be interesting, and for many of our clients, it changes the way they think about programs, right? >> So how's it going? I mean, what's the business impact been? >> It's been really positive. Of course, it talks for itself, it's really good. The fact that you've got 20 thousand people here kind of demonstrates that, but it is the industry platform, and there isn't anything that comes close to it, if we're being honest. But in terms of where we are now, we are gaining a lot of benefit from the dashboards, the reporting. We've still got to make sure the quality of data is good, of course, but actually visualizing our performance is really powerful. But we've also introduced new ways of interacting with our user base, so chat is a big thing for us. We now have a user pool to what we want to market out to the firm. So we're trying to get away from the telephone as the first point of contact, and move into other contact areas, like the portal. So that's the kind of areas that we need to kind of market outwards. But we're about three months in from go live. So we're now kind of looking back on some of the improvements already that we want to make, so looking at how we're using it, working with teams on using it better. So the improvement cycle is kicking in. And we've already made some minor improvements, and there will be more to come. >> So you avoided custom mods-- >> Yes. - Which is very important because the allure of custom modifications, it's so attractive, and then you know, you get technical debt and stuck with it. What have you learned, if you had a mulligan, would you choose anything differently? >> Yeah, it's an interesting point, because I think one of the things we could've done better already was the training. Because what was really powerful about Powered IT, there was training material, we had to kind of adapt that for our own change process, of course. Understanding our culture and how training with Linklaters, isn't necessarily the same as perhaps other technology firms, where they're expected to sell flurn. Very much the model at Linklaters is kind of classroom-led training, that tends to be our culture. And we perhaps didn't do enough of that before go live. So yes, everyone went live day one, they could log a ticket, but they couldn't unlock all the other benefits that we were really trying to deliver. So I guess that training's one of those areas that you could always overdo, but I think I would go back and arrange training earlier, make sure people know the training's coming, make sure their diaries are free as well, because we're all busy people. But I think, yeah, I think for now, I think we did a good job in the 14 weeks, but I'd come back and look at training again. >> And when was your go live? >> We went live on the 12th of February, this year. >> Oh okay, and single CMDB is the vision, or goal, or? >> Yeah, so we went live with the CMDB, we're now able to populate that out, and everyone knows that can be a pain point. So that's one of the kind of evolutions we're going through now, but as I said, we switched off the old tool on the day one, so we had to make sure the customer-facing processes were working, that we could may control changes, problem management could deal with issues that reoccur. So all of that was in place, but actually we've unlocked the power of the tool for visibility, managing the tasks across teams is quite big for us, as well. But that whole transparency of data has really improved the way we work. >> Rebecca: Great. >> I think one aspect, to play on your question, there are certain aspects of the platform in that transformation that you may not do all, but you need to design an architecture right the first time. So on the CMDB, you might not have it all the way populated, but if it's not architected with a good CMDB data model, it'll catch up later on, to your point. And so, a lot of, I think, that effort is a certain amount of time you have to show value, and then you lay that groundwork, you start improving, and then you make the decision of if and when do we expand into new things. When do we move into new areas, outside of the core, and those kind of things. >> For you know this, Mitch, too, and one of... I'm going to comment, maybe you could... You could give me your observations, early on in the ServiceNow, before the big ascendancy, a lot of mistakes were made, in terms of companies not standardizing, getting the CMDB architecture right, for a lot reasons, you had politics, people were trying to slide it in. And now you see a much more consistent vision around CMDB, how to architect it, single CMDB, one throat to choke, essentially. >> Yeah, I agree totally, and I think if you look at the ecosystem of what this all is, you have to level set on it, it was drastically different from a platform perspective, and three or four years ago to now. And to your point, I think there were a lot of relatively quick implementations, if you will. And again, quick implementation is okay, as long as it's architected and thought through for the long term, and I think we're seeing in the market some implementations that maybe made some short cuts, if you will, but to your point, the things that you got to get right, you got to get the CMDB and the data model, that layer, right. You got to get the employee experience right. You only get one chance to set an employee experience. If you underwhelm, then you've lost that audience, right? Then they're like, "Eh, well, yeah," you know? And you only get one chance to have some transformation, and it doesn't have to be going from crawling to, you know, sprinting, but if you go from crawling and it feels kind of the same way, you lose interest in expanding the capabilities. So I think that's, we've all, you know, the ecosystem has learned from that, and there are some things that you've got to get correct, and what we try to do with our clients is try to say, "Hey, let's not argue about those things, right, let's not start with a whiteboard and argue about the things that should be the same for Linklaters, that should be the same for anybody." Let's get that 80% where it's, let's focus on the things that are specific to you and not deal with that common stuff. >> Right, capture their attention right away. >> Absolutely. And we use a term internally, and sometimes with our clients too, everybody knows the 80/20 rule, right? You do 80% of it, you just should stop, it's not worth the effort. We switch that, we say 20% is what makes it work for you. We should just power through the 80% that should be the same for everybody else, and the 20% that makes it work for you. How do you deal with employee experience in a law firm, right, where everybody are knowledge workers, that have all, that's very different than employee experience in a, you know, industrial manufacturing firm, right? So that's what matters and what makes it transformational to a specific organization. >> And you're in Jakarta, or Kingston? >> We're on Jakarta-- >> Yeah, okay. - Yeah. >> Great. >> And again, because it's delivered through Powered IT, KPMG do a lot of the testing, once the new version's available, it's their offer to us in terms of making sure it's fit for purpose for their Powered IT platform. And as been said, it's the 20% that we've configured for Linklaters is what we need to test. >> So we're big believers, and John mentioned it this morning of only stay one behind at most. We're big believers in we should help our clients learn what's in the new upgrade, and how it applies to them. So we've heard this week, there's some great things coming out with London, some new things in the experience, and some automations, and so on. So our job is to bring that to our clients with Powered, and say, "Yep, we're ready, here's what's in it, and by the way, here's what they've advanced, and here's what you should look to add, and let's have that ready for you." >> So, you keep people, at worst, in minus one-- >> Correct. - Is really your objective-- >> And our general advice to clients, is if you need to go to N, if there's functional new capabilities that change your business, go to N right away. If it's more just add-ons, stay at N-1, learn from the others, and keep advancing, but never go later than that, absolutely. >> And but, ServiceNow will allow you to be N-2, right? >> They will. Going forward, they're going to keep you more to N-1-- >> Dave: Pushing you along, right? >> Exactly. So you want to save just one release back and you want to make sure, and again, to use that term I used earlier, as long as you stay near-to-the-box, you know, and out-of-the-box, if you turn it on, you need to add it, get it into your environment, you need tailor it, right? But there's a fine line between staying close to that and doing way too much, and over-configuring, not even customization, just making it to where it's really complex, and that's where we try to keep our clients away from. >> Do they still do cakes, you get a cake? >> Yes. >> Had a good one. >> Yeah, we had a really good one on go live. Yeah, it's actually on LinkedIn so yeah, go and have a look. >> A bunch of law books, it looks really smart. >> It looks really good. >> Yeah, it looked very good. >> And it tasted great, too. (laughing) >> That's important. Adrian, Mitch, thanks so much for coming on The Cube, we had a great time. >> Thank you both. >> You're welcome, thank you. >> I'm Rebecca Knight, for Dave Vellante, we will have more from ServiceNow Knowledge18, coming up just after this. (music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to theCUBE's live coverage of ServiceNow Knowledge '18, #Know18. I'm your host, Rebecca Knight, along with my co-host, Dave Vellante. We're joined by Walid Saleh. He is the Senior Director, Enterprise Service Management and Automation at CIBC, based in Toronto. Thanks so much for coming on the show, Walid. >> It's great to be here. >> So I wanted to talk about the digital transformation, the enterprise service transformation journey that you are on at CIBC. Can you give our viewers a little bit of a sense of that? >> Yeah, I would say, we're actually focused on three different pillars. Obviously we're a financial institution, so security, and visibility, and compliance, that's paramount. You want to make sure that your financial institution is taking care, and has stable stakes. But we also are focused on user experience. It's very important for us. And we're focused, also, on delivery and agility of the delivery. Enabling our businesses to have their products out for our customers as fast as possible. And in the same time, making sure that our internal employees do have a great experience that can actually mirror the experience they give our customers as well. So those are the three, I would say, pillars that we're focused on. And this is where ServiceNow helps us with the transformation, for sure. >> Can you follow up on that? Elaborate a little bit. >> Yeah, I would say, you know I've been in technology for over 20 years, and I think it's really exciting times, you know? They always talk about the Jevons Paradox, which says, with computers, you get this efficiency, but that efficiency is really eaten up by the rate of consumption. So eventually, you're not getting really, the benefits that everybody talks about, but that we have been predicting for years and years. I actually believe that this is the time where we're going to see some of this efficiency. In the keynotes this morning, they were talking about the automation, were talking about the customer experience, and I think in it was the automation, the artificial intelligent. I think John, was here talking about the artificial intelligence and how it solves problems. I think this is where we're going to start seeing some of those efficiencies really manifest itself. And finally, maybe that paradox will be resolved, right? So that's really, I would say, a very important part of what you do in automation. Making sure we take all of those repetitive tasks that maybe are low value, not only that, but connecting the different areas, these are the ones we need to take out of the system, and focus on the higher function values, I would say. >> So the keynote resonated with you today. You're not running away from automation, you're embracing it. >> Absolutely. And would you say your organization is, as well? >> Yes, for sure. I've been around through multiple transformations, that's how the technology is. And I would say, throughout many of those transformations, we actually see that, our staff, it's about how do you prepare them with the skills that are required for that next wave. And in many cases, we see people, they're moving around to different jobs, doing different things that actually adds more value. Where those pieces that maybe they were complaining about because, it's just repetitive, maybe it's late at night, I don't want to be up, you know? I don't want to be doing the same things over and over. Those are the pieces that really can leave automation. Machine and machine learning actually do, execute and have your staff. So in my mind, absolutely not shying away from it. We're continuously looking at how do we have our staff ready? What's the next skill required for our transformation? And how do we actually have the teams do those higher functions? >> I was just thinking when you were describing how the kind of, grunt work, that employees are happy about, we tend to hear about this great anxiety about automation, and that people are worried that the robots are coming for their jobs, but what you're describing is the opposite, and that employees are actually grateful and really excited to have that stuff done for them. >> I would say as part of that transformation, I think there is no such thing as over-communicating. I think you have to communicate once, and twice, and thrice, and keep communicating, right? Especially in a large, classical organization, where there's a long chain of command. Actually, you have to do a lot of communication. Explain to people what the end view is. And I think what's really important is to focus on the purpose. That's really, really important. It's not the task, it's what the purpose is behind it, right? And how do we actually, maybe, take some of that task that again, are low value, and have a better experience for our employee, and subsequently for our customers as well. >> Could you talk a little bit more about the ServiceNow journey? How did it start? Where is it going? Maybe give us some detail on the timeline. >> I would say it's an interesting subject because I think when we started, it was all about, again, itel, the problem management, incident management, the usual, managing IT, IT managing. Making sure that everything is up and running and recovery is solid. I think we absolutely are seeing now that the platform, and it is really a platform, I think there will be never an argument, now, saying "Well, it is a platform." It has grown from just that area, which is just focused on being really internalized and looking internally into IT to how do we look outward to our clients, and how do we look outward to the business. And I think the business absolutely sees the value as well, and sees how we can help them automate some, again, of those workflows that enables them to be agile and faster, for sure. >> When did you first install ServiceNow? >> We actually started in 2012. >> Wow, okay. >> So one of the really early in the Canadian space, I would say. >> And what was your first move, beyond IT? >> Yes, I would say roughly, maybe two years later, 2013, 2014, that's when, once we put a catalog of services together, with a portal for people to request what they need, that's when we actually started really realizing that you know what, this is not just technology for technology. There's now all these business people. And we've done the job as technologists trying to do this, and then we realized, you know what, user experience is really, really, really important, right? And it really mirrors what John was saying in the keynotes. Again, that experience, how do you focus on experience, and make it easy for our consumers, which internally, to help our customers. >> So that was, what, '14 time frame? >> Roughly '14. >> Start bringing it to the business, as what, customer service management, or HR, or? >> As a place, a central place, a single portal for them to actually request services from IT. And it has grown to maybe beyond that as well. So over the years, you find other areas to say, "You've got a really good thing going down in here, "and everybody knows it, can you add this? "Can you add that?" >> And have you avoided custom modifications, pretty much or? >> I would say, because we were really early on the platform, I'd be lying if we say we avoid it. But I think after a couple of years, we really, I would say around 2014, this is when we actually realized the rate of innovation and how we need to make sure that the customization aren't a minimum. And it's something that, again, we had to communicate and drive in the organization. Obviously everyone feels that their business is special. But a lot of communication about what is the impact of customization, and how do you, if you customize, you will build it, we call it Tech-Debt, that you'll carry over, year over year. And that's when the business actually really listens around efficiency and the cost of that Tech-Debt. >> And what version are you at now? >> We are on Jakarta. >> You're on Jakarta, okay. So you're pretty current. >> Absolutely. And the custom mods make it a little bit harder for you to keep up, but it sounds like you're working through that. >> Absolutely. Every year, when we upgrade, we actually remove pieces of the customizations. Try to be, as much as possible, out of the box. >> Dave: And single CMDB? >> Absolutely, it's the single CMDB on all our environments, for sure. >> And have you written apps, are you taking advantage of the platform? >> We have, we have. And we found, we started, again, being technology, we started with some of the apps that actually helps technology. Things like our runbook being moved internally into ServiceNow. Moving our disaster recovery tools into ServiceNow. And again, John was talking about this this morning about how Fred said it's one data model. And it is, really. It's the heart and core of ServiceNow. Anything we move in really makes use of that data model. Is the data better together, if you like, right? I mean, it's really, I would say it's interesting because as we move things inside ServiceNow, you start seeing more and more potential. Why can't we do this? Why can't we automate this? Why can't we, just by the virtue of having the data reside together. So we've done a good number of that. What this led to is we also figured out well, we can do some of this to the business as well. So we actually start using ServiceNow for some of our business applications as well, for our back-office. >> Last word on the show, you had 18,000 peers here. How's the show going for you? What are you learning? What are your takeaways? >> It's excellent, I think it's great. I'm really happy to see that we're focused on the end user experience. Again, I keep saying the customer experience will never exceed the employee experience. So it's really important that we get this great experience for our own internal staff. And I'm really happy to see that this is the focus for John, so it's great. >> Rebecca: Great, well Walid, thank you so much for coming on the show. >> Thank you for having me. >> I'm Rebecca Knight for Dave Vallante, we will have more from Las Vegas at ServiceNow Knowledge '18 just after this.

(upbeat techno music) >> Announcer: Live, from Orlando, Florida. It's The Cube. Covering ServiceNow Knowledge17. Brought to you by ServiceNow. (upbeat techno music) >> We're back at Knowledge17. Dave Vellante with Jeff Frick. Josh Gluck is here, he's the deputy CIO of Weill Cornell Medical College in the big apple. Thanks for coming to The Cube. >> Thanks very much for having me. >> Tell us about Weill Cornell, It's a collaboration with Sloan Kettering, originally, and ... >> Yeah, we're a three part, mission-oriented institution. Patient care, being first. Our physician organization delivers patient care in New York City. We're partnered with New York Presbyterian Hospital, Memorial Sloan Kettering Cancer Center, and also the hospital for special surgery. >> So, let's get right into it. CIO, you were probably doing some of the CIO activities here, this week. Love to hear about that. But let's get right into how you're, you know, using automation, how you're using the ServiceNow platform. Let's talk in the context of IT transformation. >> Yeah. So we've been a ServiceNow customer since 2012. We actually went live on 12/12/12. Everybody thought that was a joke, but it turned out to be the real "go live" date. You know, and as the platform's matured, and as our organization's matured, you know, we started focused on ITSM, strictly. Over the last few years though, we've found that, you know, our focus for ServiceNow should be the equivalent of building a 3-1-1 platform for the administrative departments. So we've onboarded folks in HR. We're doing case management now with ServiceNow. Obviously all the ITSM, ITIL-based processes. We've worked with our Department of Environmental Health and Safety. To help them with some of the regulatory compliance, about workflows that they need to have in place. We've also built out Project and Portfolio Management in ServiceNow, and we've been doing it, actually, since the beginning. We worked with ServiceNow pretty intimately to build out those functions. And now, we're actually at the point where, the platform has surpassed what we custom developed back in the early days. And we're really focused on understanding where we can unwrap some of those customizations, and just go to the native portfolio. >> Yeah, I wanted to ask you about that. >> Yeah. >> So, that's not an uncommon story and how complicated is it to unwrap that stuff? 'Cause obviously, you don't want the custom mods there if you don't have to have them. >> Yeah, well you know we spent, what, five, six years now, focused on developing the platform to meet our needs, meet our process. You know, we're academics at heart. Right, being part of Cornell University. So, I think we have a habit of sometimes overthinking solutions. So, our customizations are pretty complex. We also though, understand that it's a heavy lift for us to keep it up. So, we partner with ServiceNow, we've had them come in and help us to an evaluation of what really could be done with a slight change to our process. Or, even just direct support for our process, straight out of the box. We're really excited about the stuff that's coming out of Jakarta. >> Okay, so it's fair to say, I mean, we've all been there. Where you have software development problems, and you go "ah, jeez, I wish I had done it differently." But, when we talk to folks like you, that are unwrapping, unraveling, custom mods, there's no regrets. You got a lot of value >> Josh: Yeah, no. >> out of 'em. And now you're moving forward, right? >> Josh: Yep. Yeah we >> That's interesting. >> Josh: Definitely did the right thing, at the right time. You know, we went through an evolution, in the way that we did Project and Portfolio Management internally at Weill Cornell. And we're focused on some of the high-level problems, high-order problems today, that some organizations may not get to. Right, we're doing resource management, proactive scheduling, and you know, for us to get to the next level, the enhancements that are available in Jakarta are around time-carding and resource management, are really going to help us, I think, not overthink the problem. And come to some standard that the rest of the industry, or other verticals are using, in how they do their resource management. >> And Josh, the 3-1-1 concept is interesting. When did you go from "this is our an ITSM tool, that's going to be pretty cool." >> Yeah. >> To "this is a platform, that we can now take this kind of 3-1-1 approach, and use that as kind of an overarching mission, >> Yeah. >> for that which you're trying to accomplish"? >> I think the concept ... I think when we first went into partnership with ServiceNow, we knew that we wanted it to be more than just a replacement for heat, right? I've actually been with two different organizations. New York Presbyterian Hospital and Weill Cornell, who have come from other ITIL platforms, ITSM platforms, and moved to ServiceNow. I was a BMC Remedy customer for a long time at New York Presbyterian. We were a heat customer at Weill Cornell, prior to going to ServiceNow. So, I think we were all familiar with the fact that it doesn't make sense to buy these point products, to do all of these different workflows. Let's buy a platform. ServiceNow represented that platform. Even in its early stages, we knew that we wanted to do more with it. We had conversations about process users. And I know you guys were talking a little bit before about changes to the license model that are happening. >> Dave: Yep. >> But we really wanted it to be something we could develop further. Our first project just happened to be, in both cases "we have an ITSM platform that isn't working." Remedy at NYP, heat at Weill Cornell. "Let's get off of it, and get onto ServiceNow." But I think, we didn't start calling it the 3-1-1 until maybe a year or two ago. >> Okay. >> And it really started with Case Management. I think that was a big deal. >> It's a good little marketing, CIO selling. >> Josh: Yeah. >> You know, Daniel Pink. How large of an organization ... >> Josh: Is, IT, or Weill Cornell itself? >> Weill Cornell. >> We're between ... We're about five-thousand and change. >> Okay, so not enormous. But, the reason for the question is, at what point does it make sense to bring in a ServiceNow? You know, our little fifty-person company. You know, we're trying ... >> Josh: Yeah. But it's still not there yet. Is it size of company? Is it size of problem? What is your advice there? >> You know, I think it's actually a good idea for most mid-level companies to talk to ServiceNow. And I think there's even a play for some small businesses. It depends on what you want to get out of the tool. Right? I mean, if you're going to use it as just a simple incident-response system, which isn't really the value that ServiceNow provides, it might be a hard sell. But, because it's a hosted system, because there is such a wealth of partners in the community now, and such a following for ServiceNow, I don't know. If you were a ten-person organization and you were customer focused, and you wanted to use it to do ... >> Jeff: Yep, yeah, that makes sense. A couple of different business processes, it could actually make sense for you. >> Josh, really tight schedule today, we'll give you the last word on Knowledge17, some of the things that have excited you, what's the bumper sticker on K17 for you? >> I think the keynotes have been great. I think you guys at The Cube have been doing a great job, of also, >> Dave: Thank you very much, appreciate that. >> you know, getting people up here and asking 'em tough questions and stuff. I appreciate you going easy on me. Than you. But, it's been great. It's been a really good show. >> Well come back again, and we'll really go at it. So, thanks very much Josh, >> Josh: Thank you. appreciate your time. Alright, keep it right there everybody. We'll be back with our next guest, right after this short break. (upbeat techno music)

>> Narrator: Live from Orlando, Florida, it's theCUBE Covering ServiceNow Knowledge 17. Brought to you by ServiceNow. >> We're back. Dave Vellante with Jeff Frick, this is theCUBE. We're live from Orlando ServiceNow Knowledge 17. Our fifth knowledge, Jeff. Abhijit Mitra is here, the general manager of customer service management business unit. ServiceNow. Great to see you. >> Good, you too. >> Loved your keynote this morning. A lot of energy. CJ introduced you as enthusiastic as today as you were 20 years ago when he met you. >> And he said even more enthusiastic, it seems. >> Jumped off the stage, he got a good reason. >> Must be a solution. >> Business is good, you guys are rockin'. You got a hot, new business unit that you're managing. You started off your conversation with essentially saying customer service is broken. I mean, you had us all raise our hands at who's ever had a bad customer service experience. Every hand went up in the audience. Explain that a little bit. What's broken? >> So the thing is that you know, when you think about customer service today companies spend a lot of time and effort on customer service but not necessarily the end customers are seeing the result of that. And you know, when you talk to customers, I talk to a lot of customers asking them like, why is this happening for you. What they're telling us is that all the solutions that are available in the market today. Our solutions are really based on CRM systems and these are very well suited for allowing customers to contact through a multitude of channels we call home channel engagement. And then for support, agents to log their issues as cases. But they don't do anything more and as consumers, as customers, we are looking for solutions. And as customer service departments, customer service agents want to fix customer issues. So that is really where the problem is so the issues don't get fixed and customers keep on calling again and again and again. That's how case volume keeps on growing. >> But they always ask you at the end, are you satisfied with your service and will you hang on for the survey and give me a five please? That's the part that amazes me. That you solved none of the problems that I asked resolving. >> Gave me the NPS. Okay so how are you attacking this problem? >> So the way we're attacking this problem is, this is something that I didn't invent. It's something in which I learned, actually. Again after talking to a lot of customers after joining ServiceNow, what they told us is that they were looking for a service management approach and really the benefit of the service management approach is that it makes customer service a team sport. Because now not just customer service but every other department whether it's engineering or operations or financials, or legal or sales can come together on a common platform and the root cause of the customer issues are then assigned as tasks across enterprise. And once these root causes are fixed, then the issues are permanently resolved. And that reduces case volume. And that also includes customer satisfaction. >> You mentioned CRM based tools, people trying to use CRM based tools for customer service management, which essentially logs something. Logs customer service issues but doesn't give you the whole work flow. What's the difference? Can you give us the, you know CRM, why not CRM, why ServiceNow? >> Yeah like I said, it closes the end to end loop so just give me an example, just giving an example, is that in ServiceNow when customer has issues, these are logged as cases. And now, the customer support agent may be able to give a quick relief to the customer and close the case. And that's what you do with every other CRM system as well. And you do the same thing in ServiceNow. However closing the case is not necessarily the be-all and end-all because the root cause of this customer's issue may still be there. And that's how you assign these as problems to other departments. So that's really the fundamental difference. There is a follow up process that's happening. And follow up process may not just be problem, it may be also require a change of knowledge. It may require technician to go on-site through on-the-ground field service. So basically we close the loop. We allow companies to close the loop so that it's end to end customer service. >> Now I'm just curious, when you're out on the field talking to customers that are doing this, how receptive is kind of that next level of people and departments in terms of now being pulled more directly into a customer's role through you know, taking this service approach. Is it, are they happy? Is this new? Is it just a different way to execute what was inefficiently being done before? Because they don't, you know, I'm not in customer service. I'm in whatever department I'm in. Now you're asking me to help you resolve it because I'm part of the root cause. >> So underlying this is the philosophy that everybody in the company is responsible for customer service. And companies who do well as business actually enforce that philosophy in their different departments. And it is such companies who either have aspirations to transform themselves or who are already along this way that actually have an affinity towards the service management approach. Now in terms of the people who are actually working in the different departments, it's not that they're not working on their own systems anymore. Yeah those systems are there and for example, engineering would work with Gida, and there's nothing stopping them from doing that. But what is interesting here is that the work is getting assigned to them from customer service in the service management system of customer service management. That's really what it is. And that increases visibility. It's all about visibility. And reporting and other things. So that really shows, that okay, here are where the issues are and once you see the benefit of your impact on customer satisfaction, on Netomoto scores, on revenues, then it becomes very, very compelling. >> Abhijit, you guys don't break out the revenues of your customer service management business unit. I understand that. But it's a real business unit. It's growing. You got real customers. You showed some logos today. What can you tell us about the business, the business momentum. Any proof points that you're seeing with customers? >> Well we're been in the market for a little more than a year now. I would say a year because we just launched at this even last year. And in the last year, one year we've seen customers from all over the world at our best solutions. All over the world. We have customers now in 28 countries. Over ten big industrial categories. And many of our customers, early adopters will be live with system for a while. They were here. They are here at this conference. There are eighteen of our customers who are here. They're speaking their own sessions and they're sharing their own experiences with other customers. So it's been a tremendous adoption of the solution so far. >> Okay. And how about the impact that you've seen on their business? Can you share any results? >> Yeah absolutely, some of our customers, without naming names, have had up to 70% production in case volume just because of self service, and case deflection. Another customer had a 40% improvement in their Promoter scores. And these are unbelievable statistics. And a third replaced a 50 different customer service portals. And 15 CRM systems with ServiceNow's customer service management. So these are just unbelievable results that our customers have achieved in the last one year. >> You call them light speed pioneers. >> Abhijit: That's right. >> That's the term you guys are using, light speed. But so you know, your customers don't say hey call you, Abhijit, I need to move at light speed. What are they saying that you guys, of course, translated into that rubric of light speed? >> It's really about business transformations. So most of the, many of our customers, I would say, are looking for a better way to run customer service. They have challenges in either improving customer satisfaction. The customers are telling them that your service is very disconnected. Your SMAs aren't being met. So either it's mostly that or reducing costs because they have too many different systems. Different business units who do, work in different ways. So it's about standardization. It's about increasing efficiency. Do more with less. Automate more. And it's also about the effectivity. So, if you complete the work, you complete it well. It's done. >> Yes, being able to reduce volumes like that is impressive. Especially given the amount of data that we have. The amount of complexity that there is out in the world today. You hear a lot of talk at these conferences about IOT. You know, that's going to create more data, more devices, more problems for customers. What are your thoughts about IOT and the impacts it has on customer service? >> I think IOT is going to force customer service to be proactive. And to some extent, IOT is an opportunity to be proactive because now you have access to data that you've never had before. Now you can analyze the data in real-time. You can find out any anomalies and for which you need to take an action. And if you can predict an outage, then you can essentially take action to avoid that, right? So IOT opens up totally new opportunities for customer service to be proactive now. >> Okay, so we're live. >> They're shutting us down here. >> As always, we shut down the expo hall. It's kind of a CUBE tradition. >> We're going to go way after. The lights will be out but we'll still be going. >> The forklifts will be driving in. >> So hearing a lot today about Jakarta. CJ was explaining sort of, the process that you guys use starts with the customer. You guys try to understand what the needs are and it comes back through the business units into the platform and then you guys take it back and reapply it. What are some of the things in Jakarta that you are going to be applying in your future releases for your customers? >> So one of things that I'm very excited about Jakarta is our communities product. And this is something that were are announced today, we're releasing in Jakarta. Now with communities, it increases the level of engagement that customers have with companies because it allows the companies to provide a totally personalized experience. And think about it. In your own personal lives, when you look for help, you turn to people who you trust the most, right? Your friends and your family. Similarly as customers, they would like to turn to people who they trust which is like, other customers like them, right? So that's why communities is a big step for us. Essentially. And giving that features to our customers to have a better experience for their customers. >> So how would that work? It's a feature within the platform. Your customers will then create communities and cultivate communities? >> Yeah, essentially it's a new product and we just, you just turn it on and then you administer that community. You monitor that community. You rule it out. So our customers would use it to create their own communities for their customers. That's how it would work. >> What are some of the objectives you have for the business unit? What are some of the things we should watching as observers, in terms of indications of success, momentum? >> Really there is only one goal. Which is for our customers to be our most outspoken references. That's really the only goal that I have for this business unit. And 18 of them are here today. They are speaking on our behalf and I hope to see many many more of them in this conference next year. Customer satisfaction as they say is one thing. Customer loyalty is everything. >> Jeff: In public. >> Thanks very much for coming to theCUBE and congratulations on the success you've had. >> Thank you very much. Thank you for having me. >> Alright keep it right there, buddy. We'll be back with our next guest before the lights go out. ServiceNow Knowledge. It's theCUBE. We'll be right back. (upbeat music)

>> Narrator: Live from Orlando, Florida, it's theCUBE covering ServiceNOW Knowledge17, brought to you by ServiceNOW. >> Dave: We're back, this is theCUBE, the leader in live tech coverage. We go out to the events and we extract the signal from the noise. I'm Dave Vellante with Jeff Frick. Farrell Hough is here she's the general manager of the service management business unit at ServiceNOW, great to see you. >> Farrell: Yes, great to see you, thanks for having me. >> Dave: Awesome, you're welcome. Awesome keynote this morning, you have your baby, which is ITSM, we know, but at the financial analyst meeting and you know, you represent today's keynote, you represented, you know, more than just ITSM, which is, you know, good. But let's start there, so, awesome keynote, lot of energy, so much meat (chuckles). >> Farrell: Yes. >> Dave: In Jakarta. >> Farrell: Absolutely. We have been busy, for sure, in our IT portfolio. In ITSM we really spent a lot of time and energy in giving back to our customer base and making sure that critical capabilities and features in ITSM, have a lot of depth behind them as well. So making sure service level management's solid, service catalog, which is 99% adopted across our customer base, servicing over half a million end users, that making sure that that's solid. And then additionally, making it really easy for new customers to join onto ITSM as well by giving out of the box best practices and a guided set up format like a wizard format that they can within just a couple of hours stand up a brand new incident management process prescribed by ServiceNOW and feel confident in what they're getting. >> Dave: Yeah, so I didn't realize the number was that high in terms of adoption of service catalog. What do you see for CMDB, I mean, when you first started following ServiceNOW it was mixed, 'cause it kind of gets political, but now, today, when you talk to customers it's like, oh yeah that's a big initiative of ours, or we're already there, or what do you see? >> Farrell: Absolutely. I don't have the exact percentage in front of me but I believe that it's upwards of 70% adoption in our customer base. And that is a difference from where we were in the past, for sure. >> Dave: Which is like the mainspring of innovation, 'cause once you get there, with service catalog and CMDB-- >> Farrell: Yep, you get all your assets in there, you get all your services defined, it's go time. >> Dave: Then your operating leverage is huge in terms of when you bring out new function and the impact on the organization, the business impact, can be really enormous. >> Farrell: Absolutely. >> Jeff: And best practice out of the box is a huge, huge coo, everyone we've talked to, you know, they're smart enough now to now customization is bad. Keep it to a minimum, keep it to a minimum, do config but not customizations, so that all those upgrades are easier, easier, easier. So to come out of the box with an integrated best practices workflow, great, great solutions for the customers to get up and running quickly. >> Farrell: It is, and you know, they're asking for prescription, and we're going to give it to them. We've got our own services arm, we have a partner community, we know between all of us in this huge ecosystem what's working and what's not, and we're going to put it in the product and make sure our customers, existing and new, get best practice out of the box. >> Dave: So, kind of three areas you talked about today: service management, we just touched on, we didn't talk about the surveys, but that's cool, that's a nice little feature you guys have added. >> Farrell: Oh yes, that's right. >> Dave: So, you have new and improved surveys. Operations managements, so that's ITOM piece right? >> Farrell: Yep. >> Dave: And then business management. So give us the high level on office management. >> Farrell: I will, yeah, sure. So we announced this year that we're putting out the cloud management platform, and the adoption of cloud is long past it's tipping point. We're seeing cloud being adopted everywhere and cloud resources are extremely easy to procure, stand up, and use, and IT may or may not know about it. And that becomes just a huge problem in terms of cost and even in terms of security and compliance and when we're able to-- we made an acquisition roughly a year ago, the ITOM team, and this is basically the next generation cloud management platform, where now you're able to have a cloud portal where a end user can go and consume and, just like a service catalog, they're going to have a service catalog of cloud services that you've already provisioned very easily with the drag and drop interface, that accounts for all your policy already in those services. And so it makes it very very easy for the business to continue to operate at the pace and the skill that they need to, but for IT to make sure that we have the consistency and the compliance that we need to protect the business overall and manage cost, all with a really great user experience at the same time. So we're thrilled to be able to put out a cloud management platform. And then the second major thing that came out in the IT operations management space was around service mapping. When we went to market with service mapping it was for all on prem services and mapping out what that looked like. This time around we're just bookending it and kind of closing the gap and saying okay, let's look at what's off prem, and let's look what's in the cloud. So you get a holistic view and are able to discover resources in the cloud and on prem as well and you get that holistic view of your services mapped going forward. >> Dave: So I have to ask you, so we're always asking, when ServiceNOW gets into HR, it's like oh does ServiceNOW compete with Workday, no. And when ServiceNOW gets into security, it's like does ServiceNOW compete with FireEyes, et cetera, no no. Now when you talk about this multi-cloud, sort of mapping visibility, there's a lot of talk about, we call it sometimes inter-clouding and inter-cloud management, how far to do you go into that, I mean, can I actually orchestrate across clouds? Is it just giving you visibility, well not just, but, how should I think about the positioning of ServiceNOW in that space of cloud management? >> Farrell: We're out there to create flexibility for customers and we'll start to make it happen that you can orchestrate across different clouds regardless of what they look like. We're not totally there yet, but that's the direction it's going. >> Dave: Well nobody's there. >> Farrell: Yep. >> Dave: This is jump all for the industry. And it's got to be a huge market, I mean, everybody's doing multi-clouds. In fact somebody told me, today David Flora told me in Europe there was a mandate in the banking sector that you have to have a second source for cloud. >> Jeff: Oh really? >> Dave: Yeah, I don't know the context, but good news for the cloud vendors, right? Good news for somebody-- >> Farrell: Exactly. >> Dave: --who manages that. So, okay, and now what about, are we done with ops-- >> Farrell: That was operations management, yep done with that. >> Dave: And then how about business management? >> Farrell: Alright, on the business management side, the big news if the software asset management. We're able to deliver another new product this year, and that's really going to put a lot of power back in the hands of IT. You're no longer caught on your heels with a software audit, realizing you're out of compliance. We struggle with visibility and understanding where are all these software assets, who are they allocated to, are they actually using them, how much is it costing us, and when we're able to have visualization to that because it's on the ServiceNOW platform and we understand where all those items exist, we're able to go in and very easily reclaim licenses, or reallocate them, and to me that's found money. And I just love that. I think that's going to be great, and guess what? You want to find your sourcing for your next IT project it's right there. >> Jeff: Right, right, and you're being humble. I mean that was the thing where the biggest roar came up from the crowd, without a doubt. Super, super well received. >> Dave: We were talking to CJ this morning about how it works and you get the platform, the platform comes out with all these features, and then the business units take advantage of those features. Now of course he described it differently, he said you start with the customer, and then you figure out what to put in the platform knowing that the business units are going to take advantage of it. But when you think about intelligent automation you gave an example of predictive maintenance today, so that's a use case for that so called AI or deep learning, machine learning. So talk about that a little bit. And then I want to get into the DX continuum piece as well. >> Farrell: Yeah, absolutely. When we're sitting on this data set that our customers have and they want us to take advantage of it for them, on their behalf, we're able to go back and apply algorithms to those data sets to say what's the norm? And did it have a good outcome? And all that data is in there, we're able to model it now, you're not having to go do that in some--export that into some other system to try to figure out, with some advanced analytics, what's that looking like, you're able to be able to say very clearly, listen, here's what the normal pattern of behavior is, and establish that for everything else going forward. So it becomes really clear where outliers exist and what suspect events or suspect alerts look like in your environment and then you can fire off a process to say look, this looks like a problem, and with certain signposts associated to it, go ahead and automatically open up that incident. You apply it to change management where you're talking about predictive maintenance. Something has enough failures automatically schedule a change window or decommission it, fail it over, back it out, move it out of the way, so that it's not causing a problem anymore. We put so much on humans to do for so long because the technology wasn't there to allow us to do it, well it's time, it's here now. And so we can take some of the burden away. >> Dave: I just had a thought, we talk in this industry so much about consumerization of IT and trying to mimic consumers, Fred Luddy talks about all the time. What you just described, I thought about an experience of an iPhone user, and anytime you do a migration, my wife just migrated from an android to an iPhone, what question was asked, is it backed up? What you just described is proactive. You're way beyond is it backed up, you're at the point of, we're going to just eliminate any possibility of a disruption. So I guess my question there is, is enterprise IT finally, not only catching up, but in some regards surpassing, this consumerization trend? >> Farrell: Hey, I think there's an opportunity to leapfrog, all the way, and I'm behind a 100%. I do, I think exactly that. And why not get way out ahead and over our skis with that and over-deliver and show that yep, we can see what's coming, we're sitting on all this data. When you choose to go to the cloud, and all that data is accessible, and you're on a single platform, it's all intermingled. You're not having to stitch together, create a data lake that's got all these different integrations pulling data and trying to sort it out from there with some data scientists or some business analysts looking at it, you're now able to lean in way more with your operation and really start to take care of it and truly own it. >> Jeff: I was just going to say my favorite part of your keynote today was kind of teeing off what you said, which is using machine learning and artificial intelligence on relatively simple looking processes that are painful, cumbersome, and horrible, like categorization, prioritization, assignment, to take the first swag, let the machine take the first swag at that stuff, and take that burden off the person because it's tedious, it's cumbersome, and it's painful, so it's this really elegant use of machine learning and AI, which is talked about all the time, on a relatively, again, simple looking activity, that just delivers tremendous value. >> Farrell: Yeah, I'm really really excited about that part because there's a lot of mystic and-- ah, I don't know what the right word is, maybe misunderstanding potentially, which can lead to mistrust of AI and machine learning and what's really going to come of it. And when we're able to say using supervised machine learning, which is the model that we're going after with the auto-classification, you can work with customers to be able to to let them tune the level of accuracy that they are comfortable with. And so you're building trust right away with a really simple example of auto-classification or auto-categorization, that is so frustrating for both parties. The person who is filing the incident, and the for the person who's going to be supporting and fulfilling on that incident as well. And I just love that fact that we can start to dip our toe into this pool and wade in and create trust along the way so we don't leave anyone behind or create mistrust in our user-base that we're just trying to get rid of them in some capacity or pull the wool over their eyes, we're not and we're going to be really transparent about in the way we do it and I think that's phenomenal. >> Jeff: And it's dynamic right, so it continues to learn. You have Spotify, you have a playlist, I like this, I don't like this, the playlist hopefully gets better, so. >> Farrell: That's right, because it took your input. >> Jeff: Correct, right. >> Farrell: And so taking input from the end users is going to then help train that system over time, that's correct. >> Dave: I got so many questions for you. (Jeff laughs) >> Farrell: Okay! Give 'em to me. >> Dave: So the auto-classification piece, that comes from the DX continuum acquisition-- >> Farrell: It does, yes. >> Dave: So explain that, I know you guys re-platformed everything, but what did that give you and let's get into auto-classification a little bit. >> Farrell: Okay, well it gave us some incredibly talented smart engineers and some really great intellectual property in terms of algorithms that we are able to now apply. When we re-platform something we're making sure that it works in the ServiceNOW platform stack and that it is going to be available and pervasive for every application that gets built on top of the platform. >> Dave: Okay so, you had said before, we're not just building a data lake, which, I want to talk to you about that too, 'cause a date lake as we know turns into a data swamp and it's just a mess and then you got to really do a lot of heavy lifting. >> Farrell: Smelly, don't like that. >> Dave: Right? Not good. So-- >> Jeff: Scary critters. >> Dave: You're auto-classifying at the point of creation I presume, or use of that data set. So how does that all work? How is it being applied? Where do you see customers getting value out of this? Explain that a little. >> Farrell: Well really I see in the ITSM side and the IT Space and in the ITSM side specifically, anything that you've got to apply a drop down field to, whether you're an end customer doing it through a service portal, or you're an IT worker, too, like let's help those guys out, why not? Anytime you need to fill out a field through a drop down mechanism, it's one discreet set of values, that's a candidate there. Now you want to have a large data set, which is why incidents, incident category, or assignment, assignment group, or what skill set might be required to work that particular incident, works because there's tons and tons and tons of incidents out there so we have lots of examples around what it could possibly be. And then that's what the data model would be built on. This auto-classification is not meant for the obscure or the random or the infrequent. So when we're talking about high volumes that a service desk sees, this is the perfect setup to apply it. >> Dave: So how will it work? I'll have a corpus of data with a bunch of incidents and I'll just sort of tell the machine go classify this? >> Dave: And it'll do some kind of process? >> Farrell: You're going to have a set of data a portion of the records you're going to use for the training model, the other portion you're going to leave behind, almost as the control group. And you're going to go apply the algorithms to that training set of data and it's going to start to learn and you're going to tell it what fields you want it to learn from and pay attention to and spit a model out on the other side on and it's going to crunch through all that data and it's going to give you a model on the other side, and you'll look at it and see if you agree, and then you're going to take that model and you'll apply it to that control set and you're going to look at what level of accuracy came out on the other side and you'll decide with that data set what accuracy level you want to have. For me, 70% accuracy will work for me on password reset. 'Cause, in all likelihood, what's it going to be? But maybe for a VPN issue I want 90%. You'll be able to start applying accuracy by category to then tune in exactly how you want things to work to make sure you get that good user experience. >> Dave: And then you'll continue to train that model and iterate. >> Farrell: Yes, absolutely. And you'll be able to train it and often as you like. I mean on demand, like yep, I want to train it again. And when you have a service desk worker who goes back in and re-categorizes, because yeah, that wasn't quite right, that's just the same thing as clicking the like button, thumbs up, thumbs down, on Spotify. You're right that you've just given it feedback. When you train it again, it takes that feedback into account. >> Dave: And then the subsequent incidents get auto-classified. >> Farrell: They get the learning. They get the learning. There's not magical learning that happens in this particular case, the technology's not evolved to that state, there's no unicorn back there that's doing all the learning for you. It takes feedback and it'll take some tuning, but hopefully in being able to make the feedback mechanism very easy, the tuning happens naturally, therefore the model gets better over time. >> Dave: Well it's a great use case because it's relatively narrow, and you have tons of data, and it can be implemented right away. >> Jeff: And like you said, even if it just helps you partially down the road, it's better than zero down the road, especially these repeatable processes that have to happen over and over and over, it's like oh please shoot me, this is the work that machines are supposed to do because it's mundane and repeatable and-- >> Farrell: Mind-numbing. >> Jeff: Mind-numbing, thank you. Let me get to solving the customer problem. >> Farrell: That's right. >> Dave: Okay so when we first encountered ServiceNOW we did our first Knowledge, it was from 2013, and it was at the height of the big data sort of hype-cycle. And so we would ask, of course we asked, well what about data, what about big data? The response was always well we got a lot of data and we're looking at that. But now we're here. And you mentioned earlier, it's not some data lake that you're processing as offloading your data warehouse, so what are you doing in that space? So it's not a data lake, it's a corpus of data and you're basically applying these AI and intelligent automation models to, can you explain a little bit about how that works? >> Farrell: Sure, well first off we won't do anything, we have to have our customer's permission to be able to use their data, they showed interest in machine learning services then they will give us permission to leverage their data and all customer data is separated too, within their own instance, within their own database, there's no co-mingling of data, so there will be no data lake whatsoever. But what we are able to do, and it's on a personal level, which I just love, because that's who we are as a company, that we're offering personalized supervised machine learning, personalized auto-classification, we're not taking all the data of all of our customers, kind of aggregating it up and then building models against that, and then saying oh I think this model would pertain to you and then it's only 25% accurate or even relevant. We're building a model very specific to you. And working with your data set and we have access to it, with your permission, and we'll go build that model, using the training set as we described, and then go test it out, and then help you go re-deploy it. So we'll pull that data into a central instance, help retrain it, and then move it back into your instance so that model is always constantly tuned and then you get to decide when you retrain it. >> Dave: So who's we in that example? You have a team of data scientists that do this? >> Farrell: This will be in our platform team. It's a platform service. You don't need data scientists to, I would say on the customer side, maybe if they were wanting to interpret some of that data or do something with it maybe they'd have a data scientist. This is just tried and true engineering and having a good service model behind it, it's just a central instance. >> Jeff: Do--I'm sorry, I interrupted. >> Farrell: No, I was just going to say through our acquisition DX Continuum, those engineers are building those training models and will keep them up to date, but they're not literally turning a crank when that data comes in and it'll be-- >> Dave: So it's a model that they apply, it scales, it's part of the service. Now you iterate that over time-- >> Farrell: That's right. >> Dave: But it's the-- >> Farrell: And you can build out other training models. So we just talked about auto-classification for instant, but this can extend in other areas as well. >> Jeff: Well I was going to say, do you think it's an opportunity for the ecosystem that has specialty expertise around, pick your favorite topic area, we're talking to someone about oil and gas earlier today, that they know what the model is way beyond just simple correlation to take in this and it flow and predict that, I think the example was that the well cap's going to break, or whatever. So do you see that potentially as an ecosystem contribution as well around more specific use cases? >> Farrell: Well I think that would be super cool. If we had customers of similar ilk, whatever that looked like, wanting to collaborate and share and crowdsource something for a greater good that wasn't competitive, I think that that would be amazing to be able to do that. And we would be able to facilitate it. We don't have any current plans to do that right now but I could absolutely see it. >> Dave: Well we've talked about the ecosystem through for years, to see it just burgeoning and awesome story. Thank you for coming on theCUBE and doing a brain dump on us and educating us. >> Farrell: Yeah, thank you so much-- >> Jeff: You really had a great opening line, "exciting time to be in IT," that was your opening line, the key night, I know you've got the excitement >> Farrell: It is! This is the best time to be in IT. I mean oh my gosh, it's fabulous. >> Dave: You're exploding. Alright Farrell, thanks very much. >> Farrell: Alright, thank you. >> Dave: Alright, keep it right there buddy, we'll be back with our next guest, theCUBE, we're live from Orlando, be right back. (techno music)

>> Announcer: Live, from Orlando, Florida, it's theCUBE, covering ServiceNow Knowledge17. Brought to you by ServiceNow. >> We're back. This is Dave Vellante with Jeff Frick. Chris Bedi is here, he's the CIO of ServiceNow. Chris, good to see you again. >> Good to see you as well. >> Yeah, so, lot going on this week, obviously. You said you're getting pulled in a million different directions. One of those, of course, is the CIO event, CIO Decisions, it's something you guys host every year. I had the pleasure of attending parts of it last year. Listened to Robert Gates and some other folks, which was great. What's happened this year over there? >> So, CIO Decisions, it's really where we bring together our forward thinking executives. We keep it intimate, about a hundred, because really it's about the dialogue. Us all learning from each other. It really doesn't matter, the industry, I think we're all after the same things, which is driving higher levels of automation, increase the pace of doing business, and innovating at our companies. So we had Andrew McAfee, MIT research scientist, really helping push the boundaries in our imagination on where machine learning and predictive analytics could go. And then we had Daniel Pink talking about his latest book, To Sell is Human. And really as CIOs, we often find ourselves selling new concepts, new business models, new processes, new analytics, new ways of thinking about things. And so, really trying to help, call it exercise, our selling muscle, if you will. Because we have to sell across, up, down, and within our own teams, and that is a big part of the job. Because as we move into this new era, I think the biggest constraint is actually between our own ears. Our inability to imagine a future where machines are making more decisions than humans, platforms are doing more work on behalf of humans. Intellectually, we know we're headed there, but he really helped to bring it home. >> Well, you know, it's interesting, we talk about selling and the CIOs. Typically IT people aren't known as sales people, although a couple years ago I remember at one of the Knowledges, Frank Slootman sort of challenged the CIO to become really more business people, and he predicted that more business people would become CIOs. So, do you consider yourself a sales person? >> I do. Selling people on a vision, a concept, the promise of automation. You know, technology, people fear it, right? You know, when you're automating people's work the fear and the uncertainty endowed, or what I call the organizational anti-bodies, start to come out. So you have to bust through that, and a large part of that is selling people on a promise of a better future. But, it's got to be real. It's got to be tied to real business outcomes with numbers. It can't be just a bunch of PowerPoint slides. >> So we always like to take the messaging from the main tent and then test it with the practitioners, and this year there's this sort of overall theme of working at lightspeed, you and I have talked about this, how does that resonate with CIOs and how do you put meaning behind that? 'Cause, you know, working at lightspeed, it's like, ooh that sounds good, but how do you put meat on that bone? >> So, the way I think about working at lightspeed is three dimensions, velocity, intelligence, and experience. And velocity is how fast is your company operating? I read a study that said 40% of Fortune 500 companies are going to disappear in the next 10 years. That's almost half, right? But I think what's going to separate the winners from the losers is the pace at which they can adapt and transform. And, with every business process being powered by IT platforms, I think CIOs and IT are uniquely positioned to explicitly declare ownership of that metric and drive it forward. So velocity, hugely important. Intelligence. Evolving from the static dashboards we know today, to real time insights delivered in context that actually help the human make decisions. And, BI in analytics as we know it today, needs to evolve into a recommendation engine, 'cause why do we develop BI in analytics? To make decisions, right? So why can't the platform, and it can, is the short answer, with the ability to rapidly correlate variables and recognize complex patterns, give recommendations to the humans, and I would argue, take it a step further, make decisions for the humans. ServiceNow did a study that said 70% of CIOs believe machines will make more accurate decisions than humans, now we just got to get the other 30% there. And then on experience, I think the right experience changes our behavior. I think we in IT need to be in the business of creating insanely great customer and employee experiences. Too often we lead with the goal of cost reduction or efficiency, and I think that's okay, but if we lead with the goal of creating great experiences, the costs and the inefficiencies will naturally drop out. You can't have a great experience and have it be clunky and slow, it's just impossible. >> And it's interesting on the experience because the changing behavior is the hardest part of the whole equation. And I always think back to kind of getting people off an old solution. People used to say, for start ups, you got to be 10x better or 1/10th the cost. 2x, 3x is not enough to get people to make the shift. And so to get the person to engage with the platform as opposed to firing off the text, or firing off an email, or picking up the phone, it's got to be significantly better in terms of the return on their investment. So now they get that positive feedback loop and, ah, this is a much better way to get work done. >> It has to. And we can't, you know, bring down the management hammer and force people to do things. It's just not the way, you know, people work. And very simple example of an experience driving the right behavioral outcome, so ServiceNow is a software company, very important for us to file patents. The process we had was clunky and cumbersome. You know, we're not perfect at ServiceNow either. So we re-imagined that process, made it a mobile first experience built on our platform, of course. But by simply doing that, there was no management edict, you have to, no coercion, if you will, we saw an 83% increase in the number of patent applications filed by the engineers. So the right experience can absolutely give you the right desired economic behavior. >> You talked about 70% of CIOs believe that machines will make better decisions than humans. We also talked about Andrew McAfee, who wrote a book with Eric Brynjolfsson. And in that book, The Second Machine Age, they talked about that the greatest chess player in the world, when the supercomputer beat Garry Kasparov, he actually created this contest and they beat the supercomputer with a combination of man and other supercomputers. So do you see it as machine, sort of, intelligence augmenting human intelligence, or do you actually see it as machines are going to take over most of the decisions. >> So, I actually think they are going to start to take over some basic decision making. The more complex ones, the human brain, plus a machine, is still a more, you know, advanced, right? Where it's better suited to make that decision. But I also think we need to challenge ourselves in what we call a decision. I think a lot of times, what we call a decision, it's not a decision. We're coming to the same conclusion over and over and over again, so if a computer looked at it, it's an algorithm. But in our brains, we think a human has to be involved and touch it. So I think it's a little bit, it'll challenge us to redefine what's actually a decision which is complex and nuanced, versus we're really doing the same thing over and over again. >> Right, and you're saying the algorithm is a pattern that repeats itself and leads to an action that a machine can do. >> Yeah. >> It doesn't require intuition >> And we don't call that a decision anymore. >> Right, right. So, in thinking about you gave us sort of the dimensions of lightspeed, what are some of the new metrics that will emerge as a result of this thinking? >> Yeah, I don't think any of the old metrics go away. I'll talk about a few. You know, in lightspeed, working at lightspeed, we need to start measuring, for one, back on that velocity vector, what is the percentage of processes in your company that have a cycle time of zero, or near zero. Meaning it just happens instantaneously. We can think of loads of examples in our consumer life. Calling a car with Uber, there's no cycle time on that process, right? So looking at what percentage of your processes have a cycle time of zero. How much work are you moving to the machines? What percentage of the work is the platform proactively executing for you? Meaning it just happens. I also think in an IT context of percentage of self healing events, where the service never goes down because it's resilient enough and you have enough automation and intelligence. But there are events, but the infrastructure just heals itself. And I think, you know, IT itself, we've long looked at IT as a percentage of revenue. I think with all of the automation and cost savings and efficiencies we drive throughout the enterprise, we need to be looking at IT as a margin contribution vehicle. And when we change that conversation, and start measuring ourselves in terms of margin, I think it changes the whole investment thesis, in IT. >> So that's interesting. Are you measured on margin contribution? >> We're doing that right now. I don't, if an IT organization is waiting for the CFO or CEO to ask them about their margin contribution, they're playing defense. I think IT needs to proactively measure all of it's contributions and express it in terms of margin. 'Cause that's the language the CEO, and COO, and CFO are talking about, so meet them in a language that they understand better. >> So how do you do, I mean, you certainly can create some kind of conceptual value flow. IT supports this sort of business process and this business process drives this amount of revenue or margin. >> So I stay away from revenue, because I think any time IT stands up and says, we're driving revenue, it's really hard. Because there's so many external and internal factors that contribute to that. So we more focus on automation, in terms of hours saved, expressing and dollarizing that. Hard dollars, that we're able to take out of the organization and then bubbling that into an operating margin number. >> Okay, so you sort of use the income statement below the revenue line to guide you and then you fit into that framework. >> Absolutely. >> When you talk to other CIOs about this, do they say, hey, that sounds really interesting, how do I get started on that, or? >> I think it resonates really well, because, again, IT as percentage of revenue is an incredibly incomplete metric to measure our contribution. With everything going digital, you want to pour more money into technology. I mean, studies have shown, and Andrew McAfee talked about this, over the last 50, 100 years, the companies that have thrived have poured more, disproportionally more, into technology and innovation than their competitors. So, if we only measure the cost side of the equation we're doing ourselves a disservice. >> And so, how do you get started on this path, I mean, let's call this path, sort of, what we generally defined as lightspeed, measured on margin, how do you get started on that? >> First step is the hardest. But, it's declaring that your going to do it. So we've come up with a framework, you know, that maps at a process level, at a department level, and at a company level, where are we on this journey to lightspeed? If lightspeed is the finish line, where are we? And I define three stages, manual, automated, cloud, before you get to lightspeed. And then, using those same three dimensions of velocity, intelligence, and experience, to tell you where you are. And, the very first thing we did was baseline all of our business processes, every single one, and mapped it. But once you have it mapped on that framework then you can say, how do we advance the ball to the next level? And, it's not going to magically happen overnight. This is hard work. It's going to happen one process at a time, right? But pretty soon everything starts to get faster and I think things will start to really accelerate. >> When you think about, sort of, architecting IT, at ServiceNow versus some other company, I mean, you come into ServiceNow as the CIO, everything runs on ServiceNow, that is part of the mandate, right? But that's not the mandate at every company, now increasingly may be coming that way in a lot of companies, but how is your experience at ServiceNow differ from the some of the traditional G2000? >> Probably the unique part about being the CIO at ServiceNow is actually really fun, in that I get to be customer zero in that I implement our products before all of our customers. You know, get to sit down with the product managers, discuss real business problems that all of our customers are facing, and hopefully be their voice inside the four walls of service now, and be the strategic partner to the product organization. Now implementing everything, our goal is to be the best possible implementation of ServiceNow on the planet. And that's not just demonstrated by go lives, it's demonstrated by, again, the economic and business outcomes we're deriving from using the platform. So, that part is fun, challenging, and hard work all at the same time. >> So how's Jakarta lookin'? >> Fantastic. We're super excited about everything that's coming out, whether it's the communities on customer service, or our software asset management. That's been a pain, right, for IT organizations for a long time, which is these inbound software audits, from other companies, and you're responding to them and it's a fire drill. In my mind, our software asset management transforms software audits from a once a year, twice a year event, to always-on monitoring, where you're just fixing it the whole time. And it's not an event anymore. I mean, the intelligence that we're baking into the platform now, super exciting around the machine learning and the predictive analytics concepts, we have more analytics than we had before, I mean there's just so much in there, that's just exciting. We're already using it, I can't wait for our customers to get a hold of it. >> Well, CJ this morning threw out a number of 30-plus percent performance improvement. I had said to myself, your saying that with conviction, that's 'cause you guys got to be running it yourselves. >> Yeah, we are. >> What are you seeing there? >> That's not a trivial number, and I think the product teams have done a great job really digging in and makin' sure our platform operates at lightspeed. >> One of the things that Jeff and I have been talking about this week, and really this is your passion here, is adoption, how do you get people to stop using all these other tools like email, and kind of get them to use the system? >> I think, showing them the promise of what it can bring. I think it's different conversations at different levels. I think, too, an operator, someone who's using the email to manage their work, they're hungry for a different solution. Life, working, and email, and managing your business that way, it's hard, right? To a mid-level manager, I think the conversation is maybe about the experience, how consumers of their service will be happier and more satisfied. At executive level, it gets maybe more into some of the economic outcomes, of doing it. Because implementing our platform, you know, you're going to burn some calories doing it, not a lot. Our time to value is really really quick, but still, it's a project and it's initiative and it's got to have an outcome tied to it. >> You know, Chris, as you're saying that it's always tough to be stuck kind of half way. You know, you're kind of on the tool internally and it's great. >> We don't use the word tool. >> Excuse me, not the tool. The app, the platform, actually. But then you still got external people that are coming at you through text, email, et cetera. I mean, is part of the vision, and maybe it's already there, I'm not as familiar with the parts I should be, in terms of enabling kind of that next layer of engagement with that next layer of people outside the four walls, to get more of them in it as well. Because the half-pregnant stage is almost more difficult because you're going back and forth between the two. >> And our customer service product does a lot of that. If you look at what Abhijit showed today, which is fantastic, Communities is another modality to start to interact with people. Certainly, we have Connect, part of our platform, is a collaboration app within the overall platform, so you can chat, just like you would with any consumer app, in terms of chatting capabilities, and that mobile first experience. We're thinking about other modalities too. Should you be able to talk to ServiceNow, just like you talk to Alexa, and converse with ServiceNow, Farrell touched on this a little bit, through natural language, right? We all know it's coming, and it's there, it's just pushing in that direction. >> How about the security piece? You know, Shawn shared this morning, you guys are well over year in now, and he talked about that infamous number of 200 plus days-- >> Chris: Nine months, yeah. >> Yeah, compressing that. Are you seeing that internally in your own? >> We are. We use Shawn's product, we're a happy customer. The vulnerability management, the security incident response, and very very similar results. And just like the customer who was on stage said, go live in Iterate, and that's exactly what we did. Everyone has a vulnerability management tool, like a Qualys, that's feeding in. Bring in all those Qualys alerts, our platform will help you normalize them and just start to reduce the level of chaos for the SOC and IT operations. Then make it better, then drive the automation, so we're seeing very similar benefits. >> How do you manage the upgrade side, we've been asking a lot of customers this week in the upgrade cycle. Some say, ah, I'll do in minus one just to sort of let the thing bake a little bit. You guys are in plus one. How do you manage that in production, though? >> Sure, so we upgrade before our customers, and that's part of our job, right? To make sure we test it out before our customers. But I'll say something in general about enterprise software upgrades, which is, there is a cost to them and the cost is associated with business risk. You want to make sure you're not going to disrupt your business. There is some level of regression testing you just have to do. Now, strategies I think that would be wise are automating as much of that testing as you can, through a testing framework, which we're helping our customers do now. And I think with some legacy platforms, that was incredibly expensive and hard and you could never quite get there. Us being a modern cloud platform, you can actually get there pretty quickly to the point where the 80, 90% of your regression testing is automated and you're doing that last 10 to 20%. 'Cause at the end of the day, IT needs to make sure the enterprise is up and running, that's job number one. But that's a strategy we employ to make upgrades as painless as possible. >> That's got to be compelling to a lot of the customers that you talk to, that notion of being able to automate the upgrade process. >> For sure, it is. >> You're eliminating a lot of time and they count that as money. >> It is money, and automating regression testing, it's a decision and a strategy but the investment pays off very very quickly. >> Dave: So there's an upfront chunk that you have to do to figure out how to make that work? >> Just like anything worth doing. >> Dave: Yeah, right. >> Right? >> Excellent. What's left for you at the show? >> What's left for me? I love interacting with customers. I got to talk with a lot of CIOs at CIO Decisions. I actually enjoy walking through the partner pavilion and meeting a lot of our partners and seeing some of the innovation that their driving on the platform. And then just non-stop, I get ideas all day from meeting with customers. It's so fun. >> Dave: Chris, thanks very much for coming to theCube. >> Thank you. >> We appreciate seeing you again. >> Chris: Good seeing you. >> Alright, keep it right there everybody. Jeff and I will be back with our next guest. This is theCube, we're live from Knowledge17. We'll be right back.

>> Narrator: Live from Orlando Florida, it's theCUBE! Covering ServiceNow, Knowledge17. Brought to you by ServiceNow. >> Hi everybody, we're back. This is theCUBE and we're live from Knowledge17, I'm Dave Vellante with Jeff Frick. Michael Dippolito, did I say that right? >> D'Ippolito, close enough. >> D'Ippolito, sorry about that. A fellow Italian, I should get that right. D'Ippolito is assistant Vice President of Run Services Delivery, infrastructure and operations for Nationwide Insurance. Nationwide is on your side. >> You got it. It's in our heads right? >> I remember that. >> What a great marketing campaign. Michael, great to see you, thanks for coming on theCUBE. >> Thank you, thanks for having me. >> So how's Knowledge going for ya? >> Very good, very good. I'm really excited about some of the new things coming out with the newest release that was just announced this morning. And as a matter of fact I'm ready to go back and say let's jump to that version right? Because it sounds really exciting. >> So where are you right now? Which version are you on? Are you on the Helsinki? >> We are on the Helsinki release now. We usually like to jump a couple and stay as current as we can, usually you know one release behind maybe but if we find there's good functionality in jumping one we'll do it. >> I want to come back and talk about that, because we like to pick your brains about what's the best practice there, but before we do maybe set up your role at Nationwide. >> Yeah, RunService is a pretty large organization for Nationwide, through acquisitions and through our legacy environments, we have lots of application systems, you know, keeping all those running is a monumental task. So, our group is kind of sitting mainly in the middle of the applications, the infrastructure, the process, and trying to help everything stay running smoothly. >> Okay and you started with IT service management change management, like most customers, is that right? And then, you've been evolving that. Can you talk about that a little bit? >> Yeah we just implemented, about a year ago actually, we installed a year ago. >> Okay. >> We went with the Fuji release that we implemented then we've already jumped to Helsinki, and we pretty much went all processes all at once and kind of a big bang. We actually did ask that management at first does a little bit of a pilot, but then we actually went through all the other ITSM functionality, big bang after that. >> Jeff: So you're all in. >> Michael: Yeah. >> So what was life like, you know, give us a before and after, and maybe take us through the business case and how that all came about. >> I'll give you a perfect example, I just kind of did an after action review for our senior management, on our previous platform, which was an on prem heavily customized platform, to take a release would require a year and a half with a lot of planning and about a million dollars. >> Jeff: To do an upgrade. >> To do an upgrade. (Jeff Laughing) This last release to Helsinki went about six weeks, and about $100,000. So, that's a huge business case right there. Being able to be in the cloud, not having to worry about the infrastructure ourselves, and really we drove a model of zero customization so we wanted to stay out of box as much as possible, just for that reason so we could take releases fast and stay current. >> Wow, I'm sure that benefits. >> In the, you know, was situtation, the cost was predominantly people cost, programming cost, license cost, maintenance, consultants? >> It was mostly hours of effort. >> Yeah. >> The amount of customization we had and then to retrofit and test all those changes back into the release from the vendor was a monumental task and we never want to get into that situation again. >> And so with the ServiceNow upgrade, it's not out of pocket cost as much, you're quantifying time, is that correct? >> Correct. >> Yeah okay. >> It's mostly our internal cost. >> You said the time it took was a year and a half and then, like a typical upgrade in ServiceNow is, >> Michael: Less than two months. >> Okay. >> For us to bring it in test it, exercise it, making sure all our customizations, or configurations actually I should say, are working well. And a lot of it is more just the change management around it, you know, putting out the word, the communications, doing a little bit of training, or whatever it takes to get ready for a smooth launch. >> And some of the upfront planning of that as well. Now, when we talk to customers, there seems to be, we heard today that 90% of customers are adopting service catalog, CMDB, I don't know. It's mixed, right? We hear some yes, some no. Maybe tell us your experiences. >> We have a huge focus on CMDB right now. We think that CMDB is basically the foundation to all your other processes to run more smoothly right? So good trustworthy data enables faster incident resolution, better problem solving, more rigorous change management so you asses your risk of change better. So really when we sold our CMDB project, we didn't sell it based on the CMDB, we sold it based on all those other things, >> All the benefits. >> That get a ramp off of it. You know, from doing that effort. So, we're putting a lot of effort on CMDB maturity. >> So you were talking before about some of the things you saw today in Jakarta that were of interest before we go there, you had mentioned you started with Fuji, and now you're on Helsinki. What was the, you didn't double leapfrog did you? Or did you? What's your upgrade strategy? You said you might be an N minus one, but you like to stay pretty current. What's your strategy in regards to upgrades? >> Right now, we're looking at trying to be N minus one >> Uh huh. >> and taking two per year. So looking at two releases a year. We're trying to plan our schedules around maybe spring and fall. So we organize our work and our patterns around that. But something like that. We haven't really solidified that yet. A lot of it depends on what we see coming up, and what we can take advantage of. Like for example, we're getting ready to implement Work Day. And we want to make sure we have great integration between Work Day and ServiceNow. Some of the things that Jakarta is going to offer us is going to integrate nicely into Work Day. So, we may jump to that version because of that. >> So we heard this morning that the big things, well CJ set up the big things in Jakarta were going to be performance, obviously everybody better performance, maybe some UX stuff in there too, vendor risk management, and then the software asset management, which got the big cheers and the whoohoo! >> Yeah. (Jeff chuckling) >> Yeah, so, what in Jakarta is appealing to you? >> This software as a management I'd say, is very interesting because we're looking at that very closely right now in terms of our strategy around that. The other one I really like is the performance analytics and the predictive analytics that are coming out. I'd really love to be able to benchmark ourselves against other companies in terms of how we're doing. I feel we beat ourselves up a lot internally around things like availability or performance. But then, when I look and talk to others, we're not so bad. (Jeff chuckling) We're actually doing pretty good. So it'd be nice to get that benchmarking. >> Right, right. >> And some of that trend analysis that's offered. And then, finally, how do we get into a more predictive analytics mode where we can prevent incidents from happening before they do? So that's key. >> It was interesting, listening to Farrell Hough this morning talk about sort of the evolution of automation. How do you look at automation? Some shops are afraid of automation, but it seems like the ServiceNow customers we talk to really can't go fast enough. What is your thought, and how are you evolving automation? >> Well, one of our key drivers right now is how do we increase the speed of delivery to the marketplace? But, we also have to stay safe and reliable, right? And the key to speed is through automation. You can't really get that speed if you're not highly automated. And, to be highly automated, you need really high trustworthy data. So that enables fast decision making, and accuracy. >> Jeff: And that ties back to your CMDB commitment. >> Exactly, so, that all entailed enables speed, which we really want because in today's world speed is everything in terms of how you're constantly adapting your systems of engagement out there with your customers. Constantly learning from their patterns and adjusting on the fly. And that requires new mindsets. >> So you start with IT service management, you've got HR as well, is that right? >> We don't have the HR model. Right now we're only IT service management. >> Okay, straight IT services. >> We're looking at other modules, as we speak. >> Okay, so you want to make sure you get the value out of the initial ITSM, and then, how do you see that, you know, evolving? What is the conversation like internally? Do the business lines say, wow, all of a sudden we're getting improved service, and how are you doing that? Or is it more of a push where you go out to the business and say hey, here are some ideas. How does that all work? >> I'll tell you what we're really starting to see is a really change in what's driving innovation. And it's more coming from IT versus, the former models where IT was kind of like the order taker, and the business came up with everything they needed. Now, with the pace of change with technology, new business models are coming from IT to the business. And we're actually almost seeing ourselves more of an IT company than we are an insurance company. And, you starting to see those patterns especially with things like, now we're talking about metered insurance for auto, right? So basically, pay by the mile insurance, versus paying the same rate for six months. With the data we're getting out of vehicles today we can adjust your rates on the fly as you drive. Why should you pay the same rate if your car sits in the garage all weekend, versus you take it out and drive it 200 miles, right? So with the kind of data, big data and analytics that are coming from the vehicles we can do that now. >> So how is that conversation taking place? Is it being initiated by somebody in the IT staff that says hey, did you know that we have this data and we can do this? Let's take it to the business unit. Or does the business unit saying, I just saw Flo, the competitor, sticking the little thing in the dashboard? (Michael chuckling) Can we do that too? You know, there's a lot of talk about IT taking a seat at the business table >> Right. >> But how have you seen it actually been executed inside of Nationwide? >> Actually what we're seeing is, the lines are very blurry now between IT and the business. Almost to where, we're just a team working together versus the silos you used to have, and throwing the ideas over the fence. So we actually have a team that their goal is strategy and innovation. They report up through our CIO, and then business line teams have similar organizations, and they all work in a matrix fashion together. So anybody can bring any type of idea to the table, regardless of who you report up through. And we take those into consideration and we look for partners, we've got partners coming to us all the time that want to join us in innovation. And so it doesn't have to be our own solution. It could just be us on the back end of somebody else's front end, right? So, there's a lot of interesting ideas coming at us. >> What's happening in the business Mike? I mean you've got, obviously you're supporting the big systems or claims, you've got your agents systems, but mobile has exploded onto the scene. >> Yes. >> How has that affected you? What are some of the drivers in the insurance business these days? >> Well, definitely we're in this digital world now so, mobile first is critical. Everything has to be mobile enabled. We have to think of our strategy in a digital way constantly so we have a whole digital strategy that we work on. The traditional models of agency sold insurance won't ever really go away, per se, but they are shrinking. You see the demands and needs of the millennials coming up, very differently and changing. You have to compete on price to get in the door. That's important, so again we're trying to find all those interaction or intercept points with our customers as they need us. People don't really like to think of insurance, it's not on top of mind in their day to day life. But, when certain events happen like oh, I'm going to get married, or I'm going to take a trip, or you know, those kinds of things. >> Jeff: Right, kid turns sixteen. >> Yeah, we have different ways to interact with our customers, and offer some solutions that meet their need at the time. >> Well it seems like you're right, to be competitive, you've got to have the right price for those that say okay, I've got to get insurance, I need to start somewhere, great, but are you able to, as an industry, sell value? I mean, increasingly you're seeing some companies I would say Nationwide is one, where you're selling value. >> Yeah. >> Is that a trend in the business? >> Absolutely, I'll give you an example. One of the things that, normally the insurance model used to be I buy insurance and I'm protected when something bad happens. then when something bad happens, you compensate me. You pay my claim. But what about, if we can help you prevent the bad thing from even happening? So with products like our Smart Home package that you can buy now with internet of things, we can put sensors on those hot water tanks or on those pipes, or connected to your alarm system so that maybe we could alert you when we see your pipe is about to break. >> Right so, we cover, as you know our audience, we cover big data a lot. And the data business, and the insurance business have come mashing together, right? You had mentioned before, Mike, in many regards you're becoming an IT company and digitization is all about data. And the data allows you guys to build new products, to offer new services, to be more competitive and at the end of the day it's all about speed. >> Correct, speed and then that helps drive that value equation, right? So it's not so much being the lowest price, although you have to have a good price to be in the game, but then after that how can you provide that value? >> I'm curious Mike, from an insurance point of view, where before the business was based on, you know you didn't have so much data, right? So you had some big swaths, Age, sex, smoker, not smoker, but now as you're able to get data to the individual level, how that changes the way you look at it? Because it's very different than just kind of aggregating to the bulk, and then the poor unfortunate soul who has a car wreck, you pay the claim. But now, like you said, you know if I'm driving on the weekends, or if I'm parking my car. How is that really shaping the way that you guys look at the marketplace and the opportunities? >> Well you know, in the old days, you used to be able to take basically a subset of data from the past, and make your decisions based on that. >> A subset of data from the past, I love that. >> Now we're taking all the data in real time. >> In real time. >> So that puts more demands on the need for the technologies to provide that. It's critical, like especially if we're going to change your rates daily on how we insure your car, we have to have all the data, all the time. >> I remember Abhi Mehta, one of our early big data CUBE interviews, he made the statement in 2010 he said, "Sampling is dead." And, now, some people will debate that but the point he was making is just the same one you just made Michael is that you've got that data coming in, streaming it in real time. Some consumers, you know, have an issue with sticking that little meter in their car, but ultimately, that's the trend. It's going to happen. >> And you know we're seeing, and you're probably seeing it in other businesses as well, if you can provide that value, customers will give you the access and the data, because they see a value in return. So, it's that value equation. If it's good enough, they'll give you the value, and they'll give you the data. >> Dave: Yeah, you see it every day in mobile apps, right? >> Correct. >> You know, you're in New York City trying to get somewhere and it's like, turn on location services and I can help you. >> When you download any app, there's a big screen that comes up and you say I accept at the bottom, and then it has access to your pictures, access to your location and you're free to hit that accept because you see the value in that application. >> It's a quid pro quo, you know it's interesting we had the author on yesterday, Pink, Daniel Pink? >> Jeff: Pink, Mr. Pink, yes. >> And he was pointing out, he said look there used to be that the brand used to have all the information, and now there's parody in information, but in many regards, this whole digitization is an attempt by the brand to provide, to use more data and to give the consumers more value, and to create differentiation in the marketplace, and that's kind of what you're describing in your business. Last question, what's on ServiceNow's to-do list? What do you want to see a year, year and a half in? >> Well, after we implemented, we partnered with ServiceNow in a project they call Inspire, and basically it's to, what are we going to do next? You know, that very question, how do we leverage now what we've implemented, and take advantage of what the platform has to offer? We see lots of opportunities, as a matter of fact our list is so long we just don't have the bandwidth to do it all (Jeff chuckling) and we have to prioritize, but we see a lot of integration points, we see a lot of APIs coming in, we are in a kind of a really big phase in automation right now, we're trying to automate as much as possible, so for our on prem technology, we really want to go into automated provisioning of our assets, which means being able to connect those into the CMDB as they're provisioned, all automatically, and we want to really shorten those cycle times for when we have to provision infrastructure and support our applications. So ServiceNow is setting us up to do just that. >> Inspire is a great program, it's one of the best freebies in the business, and it leads, it's a win win. The customer gets the best experts, they come in and obviously, the hope is they're going to buy more stuff from ServiceNow, and if the value's there you will. Why not? It's going to drive to the bottom line. >> Using cloud to provision on prem resources, I like that. (all laughing) >> Mike thanks very much for coming to theCUBE, it was really a pleasure having you. >> Thank you, thanks for having me. >> Jeff: Thanks for sharing the insight. >> Alright keep it right there buddy we'll be back with our next guest right after this short break, there's a CUBEr live from Knowledge, be right back. (techno music)