>>from around the globe. It's the queue with digital coverage of Docker Con Live 2020 brought to you by Docker and its ecosystem partners. Welcome to the Special Cube coverage of Docker Con 2020. It's a virtual digital event co produced by Docker and the Cube. Thanks for joining us. We have great segment here. Precision cancer medicine really is evolving where the personalization of the data are really going to be important to personalize those treatments based upon unique characteristics of the tumors. This is something that's been a really hot topic, talking point and focus area in the industry. And technology is here to help with two great guests who are using technology. Docker Docker containers a variety of other things to help the process go further along. And we got here spring and who's the bioinformatics research assistant and Camille took Who's a student and in turn, you guys done some compelling work. Thanks for joining this docker con virtualized. Thanks for coming on. >>Thanks for having me. >>So first tell us about yourself and what you guys doing at the Children's Cancer Institute? That's where you're located. What's going on there? Tell us what you guys are doing there? >>Sure, So I built into Cancer Institute. As it sounds, we do a lot of research when it comes to specifically the Children's cancer, though Children a unique in the sense that a lot of the typical treatment we use for adult may or may not work or will have adverse side effects. So what we do is we do all kinds of research. But what lab and I love, which we call a dry love What we do research in silica, using computers at the develop pipelines in order to improve outcomes for Children. >>And what are some of the things you get some to deal with us on the tech side, but also there's the workflow of the patients survival rates, capacity, those constraints that you guys are dealing with. And what are some of the some of the things going on there that you have to deal with and you're trying to improve the outcomes? What specific outcomes were you trying to work through? >>Well, at the moment off of the past decade and all the work you've done in the past decade, we've made a substantial impact on the supply of ability off several high risk cancers in Pediatrics on and we've Got a certain Program, which spent I'll talk about in more depth called the Zero Childhood Cancer Program and essentially that aims to reduce childhood cancer in Children uh, zero. So that, in other words, with the previous five ability 100% on hopefully, no lives will be lost. But that's >>and what do you guys doing specifically? What's your your job? What's your focus? >>Yes, so part of our lab Old computational biology. Uh, we run a processing pipeline, the whole genome and our next guest that, given the sequencing information for the kids, though, we sequence the healthy cells and we sequence there. Two missiles. We analyze them together, and what we do is we find mutations that are causing the cancel that help us determine what treatment. So what? Clinical trials might be most effective for the kids and so specifically Allah books on that pipeline where we run a whole bunch of bioinformatics tools, that area buying thematic basically biology, informatics, and we use the data generated sequel thing in order to extract those mutations that will be the cancer driving mutations that hopefully we can target in order to treat the kids. >>You know, you hear about an attack and you hear Facebook personalization recommendation engines. What the click on you guys are really doing Really? Mawr personalization around treatment recommendations. These kinds of things come into it. Can you share a little bit about what goes on there and and tell us what's happening? >>Well, as you mentioned when you first, some brought us into this, which we're looking at, the the profile of the team itself and that allows us to specialize the medication on the young treatment for that patient on. Essentially, that lets us improve the efficiency and the effectiveness off the treatment, which in turn has an impact on this probability off. >>What are some of the technical things? How did you guys get involved with Docker with Docker fit into all this? >>Yeah, I'm sure Camille will have plenty to bring up on this as well. But, um, yes, it's been quite a project to the the pipeline that we have. Um, we have built on a specific platforms and is looking great. But as with most tools in a lot of things that you develop when your engineers eyes pretty easy for them to become platform specific. And then that kind of stuck there. And you have to re engineer the whole thing kind of of a black hole. That's such a pain to there. So, um, the project that Mikhail in my field working on was actually taking it to the individual's pools we used in the pipeline and Docker rising them individually containing them with the dependencies they need so that we could hook them up anyway. We want So we can configure the pipeline, not just customized based off of the data like we're on the same pipeline and every it even being able to change the pipeline of different things to different kids. Be able to do that easily, um, to be able to run it on different platforms. You know, the fact that we have the choice not only means that we could save money, but if there's a cloud instance that will run an app costal. If there's a platform that you know wanted to collaborate with us and they say, Oh, we have this wholesome data we'd love for you to analyze. It's over hell, like a lot of you know, >>use my tool. It's really great. >>Yeah. And so having portability is a big thing as well. And so I'm sure people can go on about, uh, some of the pain point you having to do authorize all of the different, But, you know, even though they Austin challenges associated with doing it, I think the payoff is massive. >>Dig into this because this is one of the things where you've got a problem statement. You got a real world example. Cancer patients, life or death gets a serious things going on here. You're a tech. You get in here. What's going on? You're like, Okay, this is going to be easy. Just wrangle the data. I throw some compute at it. It's over, right? You know what? How did you take us through the life? They're, you know, living >>right. So a supreme I mentioned before, first and foremost well, in the scale of several 100 terabytes worth of data for every single patient. So obviously we can start to understand just how beneficial it is to move the pipeline to the data, rather the other way around. Um, so much time would be saved. The money costs as well, in terms of actually Docker rising the but the programs that analyze the data, it was quite difficult. And I think Sabrina would agree mate would agree with me on this point. The primary issue was that almost all of the apps we encountered within the pipeline we're very, very heavily dependent on very specific versions off some dependencies, but that they were just build upon so many other different APS on and they were very heavily fined tuned. So docker rising. It was quite difficult because we have to preserve every single version of every single dependency in one instance just to ensure that that was working. And these apps get updated quite Simpson my regularly. So we have to ensure that our doctors would survive. >>So what does it really take? The doc arise your pipeline. >>I mean, it was a whole project. Well, um, myself, Camille, we had a whole bunch of, um, automatic guns doing us over the summer, which was fantastic as well. And we basically have a whole team of lost words like, Okay, here's another automatic pull in the pipeline. You get enterprise, you get to go for a special you get enterprise, they each who individually and then you've been days awake on it, depending on the app. Easier than others. Um, but particularly when it comes to things a lot by a dramatic pools, some of them are very memory hungry. Some of them are very finicky. Some of the, um ah, little stable than others. And so you could spend one day characterizing a tool. And it's done, you know, in a handful of Allah's old. Sometimes it could make a week, and he's just getting this one tool done. And the idea behind the whole team working on it was eventually use. Look through this process, and then you have, um, a docker file set up. Well, anyone to run it on any system. And we know we have an identical set up, which was not sure before, because I remember when I started and I was trying to get the pipeline running on my own machine. Ah, lot of things just didn't look like Oh, you don't have the very specific version of ah that this developer has. 00 that's not working because you don't have this specific girl file that actually has a bug fixes in it. Just for us like, Well, >>he had a lot of limitations before the doctor and doctor analyzing docker container izing it. It was tough. What was it like before and after? >>And we'll probably speak more people full. It was basically, uh, yeah, days or weeks trying to set up on in. Stole everything needed around the whole pipeline. Yeah, it took a long time. And even then, a lot of things, But how you got to set up this? You know, I think speculation of pipeline, all the units, these are the three of the different programs. Will you need this version of obligation? This new upgrade of the tools that work with that version of Oz The old, all kinds of issues that you run into when they schools depend on entirely different things and to install, like, four different versions of python. Three different versions of our or different versions of job on the one machine, you know, just to run it is a bit of >>what has. It's a hassle. Basically, it's a nightmare. And now, after you're >>probably familiar with that, >>Yeah. So what's it like after >>it's a zoo? It supports ridiculously efficient. Like it. It's It's incredible what Michael mentioned before, as soon as we did in stone. Those at the versions of the dependencies. Dhaka keeps them naturally, and we can specify the versions within a docker container. So we can. We can absolutely guarantee that that application will run successfully and effectively every single time. >>Share with me how complicated these pipelines are. Sounds like that's a key piece here for you guys. And you had all the hassles that you do. Your get Docker rised up and things work smoothly. Got that? But tell >>me about >>the pipelines. What's what's so complicated about them? >>Honestly, the biggest complication is all of the connection. It's not a simple as, um, run a from the sea, and then you don't That would be nice, but that know how these things work if you have a network of programs with the output of this, input for another, and you have to run this program before this little this one. But some of the output become input for multiple programs, and by the time you hook the whole thing up, it looks like a gigantic web of applications. The way all the connections, so it's a massive Well, it almost looks like a massive met when you look at it. But having each of the individual tools contained and working means that we can look them all up. And even though it looks complicated, it would be far more complicated if we had that entire pipeline. You know, in a single program like having to code, that whole thing in a single group would be an absolute nightmare. Where is being able to have each of the tools as individual doctors means we just have the link, the input on that book, which is the top. But once you've done that, it means that you know each of the individual pools will run. And if an individual fails, or whatever raised in memory or other issues run into, you can rerun that one individual school re hooks the output into whatever the next program is going without having one massive you know, program will file what it fails midway through, and there's nothing you can do. >>Yeah, you unpack. It really says, Basically, you get the goodness to the work up front, and a lot of goodness come out of it. So this lets comes to the future of health. What are the key takeaways that you guys have from this process? And how does it apply to things that might be helpful to you right around the corner? Or today, like deep learning as you get more tools out there with machine learning and deep learning? Um, we hope there's gonna be some cool things coming out. What do you guys see here? And the insights? >>Well, we have a section of how the computational biologist team that is looking into doing more predictive talks working out, um, basically the risk of people developing can't the risks of kids developing cancel. And that's something you can do when you have all of this data. But that requires a lot of analysis as well. And so one of the benefits of you know being able to have these very moveable pipelines and tools makes it easier to run them on. The cloud makes it easier to shale. You're processing with about researches to the hospitals, just making collaboration easier. Mainz that data sharing becomes a possibility or is before if you have three different organizations. But the daughter in three different places. Um, how do you share that with moving the daughter really feasible. Pascal, can you analyze it in a way that practical and so I don't want one of the benefits of Docker? Is all of these advanced tools coming out? You know, if there's some amazing predicted that comes out that uses some kind of regression little deep learning, whatever. If we wanted to add that being able to dock arise a complex school into a single docker ice makes it less complicated that highlighted the pipeline in the future, if that's something we'd like to do, >>Camille, any thoughts on your end on this? >>Actually, I was Sabrina in my mind for the last point. I was just thinking about scalability definitely is very. It's a huge point because the part about the girls as a technology does any kind of technology that we've got to inspect into the pipeline. As of now, it be significantly easier with the use of Docker. You could just docker rise that technology and then implant that straight into the pipeline. Minimal stress. >>So productivity agility doesn't come home for you guys. Is that resonate? >>Yeah, definitely. >>And you got the collaboration. So there's business benefits, the outcomes. Are there any proof points you could share on some results that you guys are seeing some fruit from the tree, if you will, from all this Goodness. >>Well, one of the things we've been working on is actually a collaboration with those Bio Commons and Katica. They built a platform, specifically the development pipelines. We wanted to go out, and they have support for Docker containers built into the platform, which makes it very easy to push a lot of containers of the platform, look them up and be able to collaborate with them not only to try a new platform without that, but also help them look like a platform to be able to shoot action access data that's been uploaded there as well. But a lot of people we wouldn't have been able to do that if we hadn't. Guys, they're up. It just wouldn't have. Actually, it wouldn't be possible. And now that we have, we've been able to collaborate with them in terms of improving the platform. But also to be able to share and run our pipelines on other data will just pretty good, >>awesome. Well, It's great to have you on the Cube here on Docker Con 2020 from down under. Great Internet connections get great Internet down. They're keeping us remote were sheltering in place here. Stay safe and you guys final question. Could you eat? Share in your own words from a developer? From a tech standpoint, as you're in this core role, super important role, the outcomes are significant and have real impact. What has the technology? What is docker ization done for you guys and for your work environment and for the business share in your own words what it means. A lot of other developers are watching What's your opinion? >>But yeah, I mean, the really practical point is we've massively increased capacity of the pipeline. One thing that been quite fantastic years. We've got a lot of increased. The Port zero child who can program, which means going into the schedule will actually be able to open a program. Every child in Australia that, uh, has cancel will be ableto add them to the program. Where is currently we're only able to enroll kids who are low survivability, right? So about 30% the lowest 30% of the viability we're able to roll over program currently, but having a pipeline where we can just double the memory like that double the amount of battle. Uh, and the fact that we can change the instance is really to just double the capacity trip. The capacity means that now that we have the support to be able to enroll potentially every kid, Mr Leo, um, once we've upgraded the whole pipeline, it means will actually be a code with the amount of Children being enrolled, whereas on the existing pipeline, we're currently that capacity. So doing the upgrade in a really practical way means that we're actually going to be a triple the number of kids in Australia. We can add onto the program which wouldn't have been possible otherwise >>unleashing the limitations and making it totally scalable. Your thoughts as developers watching you're in there, Your hand in your hands, dirty. You built it. It's showing some traction. What's what's your what's your take? What's your view? >>Well, I mean first and foremost locks events. It just feels fantastic knowing that what we're doing is as a substantial and quantify who impact on the on a subset of the population and we're literally saving lives. Analyze with the work that we're doing in terms off developing with With that technology, such a breeze especially compared Teoh I've had minimal contact with what it was like without docker and from the horror stories I've heard, it's It's It's a godsend. It's It's it's really improved The quality of developing. >>Well, you guys have a great mission. And congratulations on the success. Really impact right there. You guys are doing great work and it must feel great. I'm happy for you and great to connect with you guys and continue, you know, using technology to get the outcomes, not just using technology. So Fantastic story. Thank you for sharing. Appreciate >>you having me. >>Thank you. >>Okay, I'm John for we here for Docker Con 2020 Docker con virtual docker con digital. It's a digital event This year we were all shale three in place that we're in the Palo Alto studios for Docker con 2020. I'm John furrier. Stay with us for more coverage digitally go to docker con dot com from or check out all these different sessions And of course, stay with us for this feat. Thank you very much. Yeah, yeah, yeah, yeah, yeah, yeah