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Rahul Pathak & Shawn Bice, AWS | AWS re:Invent 2018


 

(futuristic electronic music) >> Live from Las Vegas, its theCUBE covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Hey welcome back everyone. Live here in Las Vegas with AWS, Amazon Web Services, re:Invent 2018's CUBE coverage. Two sets, wall-to-wall coverage here on the ground floor. I'm here with Dave Vellante. Dave, six years we've been coming to re:Invent. Every year except for the first year. What a progression. We got great news. Always raising the bar, as they say at Amazon. This year, big announcements. One of them is blockchain. Really kind of laying out early formation of how they're going to roll out, thinking about blockchain. We're here to talk about here, with Rahul Pathak, who's the GM of analytics, and data lakes, and blockchain. Managing that. And Shawn Bice who's the vice president of non-relational databases. Guys, welcome to theCUBE. >> Thank you. >> Thank you, it's great to be here. >> I wish my voice was a little bit stronger. I love this segment. You know, we've been doing blockchain. We've been following one of the big events in the industry. If you separate out the whole token ICO scam situation, token economics is actually a great business model opportunity. Blockchain is an infrastructure, a decentralized infrastructure, that's great. But it's early. Day one really for you guys in a literal sense. How are you guys doing blockchain? Take a minute to explain the announcement because there are use cases, low-hanging use cases, that look a lot like IoT and supply chain that people are interested in. So take a minute to explain the announcements and what it means. >> Absolutely, so when we began looking at blockchain and blockchain use cases, we really realized there are two things that customers are trying to do. One case is really keep an immutable record of transactions and in a scenario where centralized trust is okay. And for that we have Amazon QLDB, which is an immutable cryptographically verifiable ledger. And then in scenarios where customers really wanted the decentralized trust and the smart contracts, that's where blockchain frameworks like Hyperledger Fabric and Ethereum play a role. But they're just super complicated to use and that's why we built Managed Blockchain, to make it easy to stand up, scale, and monitor these networks, so customers can focus on building applications. And in terms of use cases on the decentralized side, it's really quite diverse. I mean, we've got a customer, Guardian Life Insurance, so they're looking at Managed Blockchain 'cause they have this distributed network of partners, providers, patients, and customers, and they want to provide decentralized verifiable records of what's taking place. And it's just a broad set of use cases. >> And then we saw in the video this morning, I think it was Indonesian farmers, right? Wasn't that before the keynote? Did you see that? It was good. >> I missed that one. >> Yeah, so they don't have bank accounts. >> Oh, got it. >> And they got a reward system, so they're using the blockchain to reward farmers to participate. >> So a lot of people ask the question is, why do I need blockchain? Why don't you just put in database? So there are unique, which is true by the way, 'cause latency's an issue. (chuckles) Certainly, you might want to avoid blockchain in the short term, until that gets fixed. Assume that every one will get fixed over time, but what are some of the use cases where blockchain actually is relevant? Can you be specific because that's really people starting to make their selection criteria on. Look, I still use a database. I'm going to have all kinds of token and models around, but in a database. Where is the blockchain specifically resonating right now? >> I'll take a shot at this or we can do it together, but when you think of QLDB, it's not that customers are asking us for a ledger database. What they were really saying is, hey, we'd like to have this complete immutable, cryptographically verifiable trail of data. And it wasn't necessarily a blockchain conversation, wasn't necessarily a database conversation, it was like, I really would like to have this complete cyrptographic verifiable trail of data. And it turns out, as you sort of look at the use cases, in particular, the centralized trust scenario, QLDB does exactly that. It's not about decentralized trust. It's really about simply being able to have a database that when you write to that database, you write a transaction to the database, you can't change it. You know, a typical database people are like, well, hey, wait a second, what does immutable really mean? And once you get people to understand that once that transaction is written to a journal, it cannot be changed at all and attached, then all of a sudden there's that breakthrough moment of it being immutable and having that cryptographic trail. >> And the advantage relative to a distributive blockchain is performance, scale, and all the challenges that people always say. >> Yeah, exactly. Like with QLDB, you can find it's going to be two to three times faster cause you're not doing that distributing consensus. >> How about data lakes? Let's talk about data lakes. What problem were you guys trying to solve with the data lakes? There's a lot of them, but. (chuckles) >> That's a great question. So, essentially it's been hard for customers to set up data lakes 'cause you have to figure out where to get data from, you have to land it in S3, you've got to secure it, you've then got to secure every analytic service that you've got, you might have to clean your data. So with lake formation, what we're trying to do is make it super easy to set up data lakes. So we have blueprints for common databases and data sources. We bring that data into an S3 data lake and we've created a central catalog for that data where customers can define granular access policies with the table, and the column, and the row level. We've also got ML-based data cleansing and data deduplication. And so now customers can just use lake formation, set up data lakes, curate their data, protect it in a single place, and have those policies that enforce across all of the analytic services that they might use. >> So does it help solve the data swamp problem, get more value out of the data lake? And if so, how? >> Absolutely, so the way it does that is by automatically cataloging all datas that comes in. So we can recognize what the data is and then we allow customers to add business metadata to that so they can tag this as customer data, or PII data, or this is my table of sales history. And that then becomes searchable. So we automatically generate a catalog as data comes in and that addresses the, what do I have in my data lake problem. >> Okay, so-- >> Go ahead. >> So, Rahul, you're the general manager. Shawn, what's your job, what do you do? >> So our team builds all the non-relational databases at Amazon. So DynamoDB, Neptune, ElastiCache, Timestream, which you'll hear about today, QLDB, et cetera. So all those things-- >> Beanstalk too, Elastic Beanstalk? >> No we do not build Beanstalk. >> Okay, we're a customer of DynamoDB, by the way. >> Great! >> We're happy customers. >> That's great! >> And we use ElastiCache, right? >> Yup, the elastic >> There you go! >> surge still has it. >> So-- >> Haven't used Neptune yet. >> What's the biggest problem stigmas that you guys are trying to raise the bar on? What's the key focus as you get this new worlds and use cases coming together? These are new use cases. How are you guys evaluating it? How are you guys raising the bar? >> You know, that's a really good question you ask. What I've found in my experience is developers that have been building apps for a long time, most people are familiar with relational databases. For years we've been building apps in that context, but when you kind of look at how people are building apps today, it's very different than how they did in the past. Today developer do what they do best. They take an application, a big application, break it down into smaller parts, and they pick the right tool for the right job. >> I think the game developer mark is going to be a canary in the coal mine for developers, and it's a good spot for data formation in these kind of unstructured, non-relational scenarios. Okay, now all this engagement data, could be first person shooter, whatever it is, just throw it, I need to throw it somewhere, and I'll get to it and let it be ready to be worked on by analytics. >> Well, yeah, if you think about that gamer scenario, think about if you and I are building a game, who knows if there's going to be one user, ten players, or 10 million, or 100 million. And if we had 100 million, it's all about the performance being steady. At 100 million or ten. >> You need a fleet of servers. (John laughing) >> And a fleet of servers! >> Have you guys played Fortnite? Or do you have kids that play? >> I look over my kid's shoulder. I might play it. >> I've played, but-- >> They run all their analytics on us. They've got about 14 petabytes in S3 using S3 as their data lake, with EMR and Athena for analytics. >> We got a season-- >> I mean, think about that F1 example on keynotes today. Great example of insights. We apply that kind of concept to Fortnite, by the way, Fortnite has theCUBE in there. It's always a popular term. We noticed that, the hastag, #wherestheCUBEtoday. (Rahul chuckling) I couldn't resist. But the analytics you could get out of all that data, every interaction, all that gesture data. I mean, what are some of the things they're doing? Can you share how they're using the new tech to scale up and get these insights? >> Yeah, absolutely. So they're doing a bunch of things. I mean, one is just the health of the systems when you've got hundreds of millions of players. You need to know if you're up and it's working. The second is around engagement. What games, what collection of people work well together. And then it's what incentives they create in the game, what power ups people buy that lead to continued engagement, 'cause that defines success over the long term. What gets people coming back? And then they have an offline analytics process where they're looking at reporting, and history, and telemetry, so it's very comprehensive. So you're exactly right about gaming and analytics being a huge consumer of databases. >> Now, Shawn, didn't you guys have hard news today on DynamoDB, or? >> Yeah today we announce DynamoDB On-Demand, so customers that basically have workloads that could spike up and then all of a sudden drop off, a lot of these customers basically don't even want to think about capacity planning. They don't want to guess. They just want to basically pay only for what they're using. So we announced DynamoDB On-Demand. The developer experience is simple. You create a table and you putyour read/write capacity in the on-demand mode, and you literally only pay for the request that your workload puts through system. >> It's a great service actually. Again, making life easier for customers. Lower the bill, manage capacity, make things go better, faster, enables value. >> It's all about improving the customer experience. >> Alright, guys, I really appreciate you coming in. I'm really interested in following what you guys do in the future. I'm sure a lot of people watching will be as well, as analytics and AI become a real part of, as you guys move the stack and create that API model for, what you did for infrastructure, for apps. A total game changer, we believe. We're interested in following you guys, I'm sure others are. Where are you going to be this year? What's your focus? Where can people find out more besides going to Amazon site? Is there certain events you're going to be at? How do people get more information and what's the plans? >> There's actually some sessions on lake formation, blockchain that we're doing here. We'll have a continuous stream of summits, so as the AWS Summit calendar for 2019 gets published that's a great place to go for more information. And then just engage with us either on social media or through the web and we'll be happy to follow up. >> Alright, well, we'll do a good job on amplifying. A lot of people are interested, certainly blockchain, super hot. But people want better, stronger, more stable, but they want the decentralized immutable database model. >> Cryptographically verifiable! >> And see as everyone knows. >> Scalable! >> Anyone who wants to keep those, they talk about CUBE coins but I haven't said CUBE coin once on this episode. Wait for those tokens to be released soon. More coverage after this short break, stay with us. I'm John Furrier, and Dave Vellante, we'll be right back. (futuristic buzzing) (futuristic electronic music)

Published Date : Nov 29 2018

SUMMARY :

Brought to you by Amazon Web Services, of how they're going to roll out, thinking about blockchain. it's great to be here. How are you guys doing blockchain? And for that we have Amazon QLDB, which is an immutable Wasn't that before the keynote? And they got So a lot of people ask the question is, that when you write to that database, And the advantage relative Like with QLDB, you can find it's going to be two What problem were you guys trying where to get data from, you have to land it in S3, And that then becomes searchable. Shawn, what's your job, what do you do? So our team builds all the non-relational that you guys are trying to raise the bar on? You know, that's a really good question you ask. and I'll get to it and let it be ready think about if you and I are building a game, You need a fleet of servers. I might play it. as their data lake, with EMR and Athena for analytics. But the analytics you could get out of all that data, 'cause that defines success over the long term. and you literally only pay for the request Lower the bill, manage capacity, improving the customer experience. I'm really interested in following what you guys And then just engage with us either on social media A lot of people are interested, I'm John Furrier, and Dave Vellante, we'll be right back.

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