19. What's New in Version 2021.1 of InterSystems IRIS?

Speaker 0 00:00:02 Welcome to data points, a podcast by InterSystems learning services. Make sure to subscribe to the podcast on your favorite podcast. App links can be [email protected]. I'm Derek Robinson and today's episode. I'll chat with product manager, Benjamin devote about what's new and noteworthy in the 2020 one.one release of InterSystems Iris. <inaudible> Speaker 1 00:00:39 Welcome Speaker 0 00:00:39 To the data points podcast by InterSystems learning services. On today's episode, I'm welcoming back a familiar guest if you're a regular listener of the podcast, and that is Benjamin Debelle, Benjamin will talk to us about the 2020 one.one release of InterSystems, Iris from analytics to business intelligence, to machine learning, to development gateways into fire improvements. Benjamin will walk us through all of the latest and greatest from the most recent release of InterSystems, Iris. All right, and welcome to the podcast Benjamin Dubbo making what I think is your third podcast appearance now. So Benjamin, thanks for joining us. Speaker 2 00:01:19 Uh, pleasure, Derek. Thanks for having us. Speaker 0 00:01:22 Um, so today we're going to talk about the 20, 21.1 release of InterSystems, Iris, and kind of talk about what's in that, and what's exciting and what should be, you know, getting people's attention with this release. So, um, let's say I see you today in the elevator. You have 10 seconds to give me the rundown of what's new in this release of InterSystems. Iris, what would you say? Speaker 2 00:01:40 That's unfair, you're on one of the highest floors of the building anyway. So I think the most important thing, or the most importantly forward that we made in this week is what we did in analytics. We've made really a lot of investments. Um, we've introduced the Irish adaptive analytics, which is a new add on capability in this release. We've made integrators ML, which we've talked about before now, a core part of the standard release. And we've also significantly upped our game in SQL to support a little Clarice. Speaker 0 00:02:09 Nice, nice. So you clocked in just in time there, but let's say now we're getting off at the same floor and you have a few more seconds to talk about some of this in more detail. So tell us a little bit about adaptive analytics. I know this has been mentioned, uh, in one of our recent episodes, we talked about analytics and AI. Um, give us a little bit more of a breakdown of adaptive analytics cause that's one of the big new things that pops out at me in that, in that ten second description. Speaker 2 00:02:30 Yeah, absolutely. Uh, and it's probably worth its own dedicated podcast in a, in a, in a while, but essentially it enabled customer could find their logical data model on top of data. That's in their, uh, Irish database, uh, in, in, in business terms. So business measures, business dimensions, but it makes sense to business users and analysts. And then the technology in adaptive analytics makes it takes care of mapping. Those business measures ambitions. I mentioned to whichever native format, their preferred tool of the day for, uh, end-user data visualization or BI, uh, preferred, but that could be Tableau power BI. You can Excel, but also, uh, many, many other BI tools. So because adaptive analytics takes care of that mapping of the business model to what those tools and represent and can, can show to them natively it's significantly important, the time to insight for those end user. Speaker 2 00:03:24 And then the best part for me as a technique, why we're calling it adaptive. So adaptive analytics will not yet make sure that it all looks splendid from a business perspective, but under the hood, it will automatically monitor the queries that go through this business model. And while initially it will map those queries directly to the source labels in the source data, it will start looking for frequent patterns and it will aggregate, um, interim results for those, they will cash for results for those in a very smart way so that it can serve for queries off those prebuilt structure. It so that it can, it can support many more users, much more data, much more effectively. That's all, that's all going totally autonomous it's, it's a really cool piece of technology. Speaker 0 00:04:10 Right. Nice. And, you know, I think, um, when we had Carmen on a few episodes ago, we talked a little bit about, um, the differences between like a partnership and a homegrown technology and some of these areas. And so a lot of what you mentioned there also reminds me of kind of the business intelligence area where we have InterSystems Iris BI. So, um, talk a little bit about how that relates between adaptive analytics and InterSystems Iris. Speaker 2 00:04:33 Yeah. That's a very appropriate question because it sounds very similar to indeed. And indeed what you would do with adaptive analytics is also business intelligence. Our pre-existing BI engine, which many will probably still know on the red solar and DC, it's entirely embedded in intersystem sideways from the low level interaction with birth table through our own custom built and the X query engine all the way up to the data visualization part, analyze her dashboards. That's all embedded inside InterSystems Iris. And that embedded model enables us to do a couple of really cool things that we can make sure that you're I was BI cute, always. So you real-time data because we keep them Multimatic in sync with the low level data structured tables. We can make sure that if you're building an application or InterSystems Iris, that in that application, you can also render a couple of a couple of charts or entire dock boards that are also customized according to your, um, you were replicated in link back and forth. Speaker 2 00:05:34 So that if you're, if you're drilling down in a BI view to particular lists of order, you can add a button that immediately goes through your order processing system to make sure that those orders are put on the, on the mail, right? That model is really applicable to application partners that want to keep their deployments simple, um, and just have analytics embedded into those applications. Now with adaptive analytics, we're targeting a slightly different audience. So I already mentioned that, um, we're catering to business user that may use a variety of other third party tools, Abloh power, BI Excel, et cetera. Um, so you may be working in a, in a big organization that has a read a large data warehouse that needs to support those different user groups each with their own preferred tool. So that's where adaptive analytics can, can provide exactly that capabilities. So making sure that those business users, their business models and the tools that they prefer to work with, again, they serve different use cases. So having introduced adaptive analytics doesn't mean that we're letting go so interested in is always BI actually learn an Iris BI user. You'll see that we made a couple of really nice performance enhancements in this, in this release, but they're just two separate use cases in the next release. We'll also be looking for more interplay between the two. Speaker 0 00:06:58 Nice. Yeah. And that, that is another kind of theme of what we talked about a couple episodes ago about these different technologies working together and, and fitting different use cases for different customers. Um, so going back kind of to the, the rundown you gave before, uh, you mentioned a little bit about integrated ML. So tell us what's new in that, in that area. Speaker 2 00:07:16 Yeah. Last fall we did release, uh, integrated the mill, uh, Alma 20, 23 based kit. And now, um, we're making it part of the, of the main release if I were points one release, which is always, which is the extended maintenance release without really making it a standard part of the kit, um, what inter integrated them they'll offer, uh, Tom Dyer and our team already, uh, had a post-op specifically devoted to this project. But in a nutshell, the, the idea of integrating the melody, that it offers a simple SQL interface or at bomb, ultimately that machine learning so that your application developers can start taking it's officer of the mill right. In their applications. Right, Speaker 0 00:07:54 Right. Nice. And, uh, so I think kind of packaging those together and, you know, making it streamlined for people to be able to take advantage of all those features. Um, so that sounds like a lot of analytic stuff and a lot of stuff in with, uh, between you Carmen and Tom, the product managers that we talked to last time, um, a lot in your area. So, uh, tell us a little bit about what else might have happened in, in other areas of the product. Speaker 2 00:08:16 You mean what else? It would be a little unfair and localize everything on with other, uh, one of the other main highlights of this release is hours and ports. Where could we need us? Um, if you're an administrator you managed to get your work done in less than 80 hours a week, you're probably using it. You're probably using Kubernetes because software environments really have, have gotten complex to configure a manage. And Kubernetes is a tool, an open-source tool that helps you with that. And it's got a huge ecosystem and support by all major cloud vendors through dedicated have services. But what Kubernetes does is it facilitates the configuration and automation of containerized workloads. That's so that's a mouthful, but what it means is that it, it helps you to dynamically scale and make your environments highly available by writing simple configuration files rather than operating five different interfaces with 20,000 bucks each. So how do we support Kubernetes? We've, we've released the intercept and Kubernetes operator, um, which is available with instant virus, 2101. And it extends Kubernedes with, um, best practices operate are that can help automate the management of an interstice and Cyrus collector. So it embedded best practices embedded in a boiler plate stuff to make everything smooth and really work well, so that you don't have to do, you don't even have to do all of that piping of that very simple text file. Speaker 0 00:09:47 Right, right. Nice. Yeah. And I think, uh, over a year ago we did a podcast episode about Kubernetes the technology, but not so much about the Kubernetes, the InterSystems Kubernetes operator. So good to know, um, that that's one of the things that people can look for in this release. So kind of along that topic, does that mean, would you say that customers should now pretty much be, I'll be using Kubernetes as part of their technology stack with, within Iris? Speaker 2 00:10:10 I think it's worth and looked for every system administrator, but it's absolutely not enough. Um, we like prior, uh, products or tests, uh, cloud manager, we, we offered this as an add on to make your life easier. Um, now w IKO, we actually had to make some of the configuration effort, remember those 20,000 buttons in a configuration interface, we've got to make our own, um, population a little more straightforward for AKI IKO to work. So you've probably noticed the CPF merge pilot, some of the things that we've done in the past year to make it easier to configure InterSystems Iris. So administrators can leverage those features in their own environments, in their own scripts and their own other configuration utilities that they prefer to work. Cool. Speaker 0 00:11:00 Cool. So it sounds like a lot of good stuff for analyst system admins. Um, how about developers? What, what in this release really jumps out at them and can be beneficial for them? Speaker 2 00:11:09 It's definitely one of our favorite audiences as usual. We've made a lot of enhancements for them, both of the client side libraries, as well as on the server side, on the client side, we spend a lot of, uh, small things such as, uh, net core support, uh, net core, 2.1 stubble work, which may be very big, uh, to you. Uh, we've added a connection pooling for JDBC and have some really good feedback from early adopters on that. Um, and also that some completeness work on the native API, but then on the server side is probably where the biggest changes and biggest enhancements are. So many of you will probably be familiar with our gateway technology, which allows you to, um, implement business in Java or business logic in, in dotnet, and then call it from, uh, objects crits, or call it from your business prostitutes. Speaker 2 00:12:00 So we've added pipe and an art to that list, and we've significantly improved the manageability of those gateways. So we've turned them now into the external language server. I will start automatically, um, they are declaratively configured. So it sounds a little bit like a, the Kubernedes story that we just came off. And we've also made it very easy for those gateways to call back into InterSystems Iris using re-insurance connection, a bit of a tricky term, but what it means is that if you're invoking formal scripts and Java code, that is doing some fancy stuff that now the Java code can just open up a connection back to Iris, that's using the exact same credentials, exact same, uh, security context privileges, um, without you having to do anything that makes that interplay between your Irish native codes and then the quote running on your external language server, and it's enabled, it's just, it's just, um, enables you to build nicer hybrid application. Right. Speaker 0 00:13:03 Nice, nice. So it sounds like we're kind of all in here on a modern app development with these improvements in kind of enhancements. Speaker 2 00:13:10 Yep, absolutely. And not for the app development itself, but also for managing the API to which you expose them. So we both are released the new version of InterSystems API manager, uh, first since 2.3, which now have a hybrid mode, which helps you deploy highly scalable and highly available environments. We've also added CAFCA support and make some general enhancements studio for all user expert experience. Speaker 0 00:13:38 Right, right. Nice. So it sounds like, uh, you just listed off a bunch of stuff that we could do future episodes on. So, uh, that, that's also good to hear. So, uh, shifting gears a little bit, um, we've talked mostly about really the data platform side of things. What, uh, is notable in the healthcare space for this release Speaker 2 00:13:55 As usual. We both think that the Lord in our, uh, in our healthcare, uh, support and, uh, specifically in fire support. So in the, in, in priority system, we already support it, um, fire and smart on fire applications, both in the client and server mode, but now for Irish, for health and healthcare health connect, which were also part of this release, um, was really added a lot of new fire related capabilities. Especially if you get the continuous delivery releases for the 2020 0.2 0.3 and 0.4 that we released in the meantime. So if you, if you hadn't tuned into dose, uh, make sure to look for their launch webinars and release notes as well. But now if you, if you want to skip all of that, um, so we've got support for fire, our forecast for the poor for fire profiles and also for the firepower, uh, mitigation expect and landlords. So that's really upping our game for fire. Also, if to help customers migrate to our platform, we've extended the HL seven migration toolkit to automatically convert to confirmation log that was developed on third party platforms, Cloverleaf, delegate, or IGA. So anything you did on those interface engines can now be migrated a little medically to Elstree health connect or Iris for health. Speaker 0 00:15:15 Right, right. Nice. That's great stuff. Um, so last question here, um, kind of, you know, one of the things that I feel like comes up with every new release really is a question, what does this mean for existing cache and ensemble customers that might be out there? Speaker 2 00:15:29 It's just a ton of new reasons to switch over to, uh, to InterSystems Iris. We think many of our customers that are still, uh, on cacti or ensemble will be migrating to this release. So we've been on the market with InterSystems Iris for about three years now. And many customers and partners have already made a jump, including our biggest partner, epic who has their first customers running life, all interested from Cyrus for a while now. Um, so we, we offer tools to convert existing instances to Iris, and to help you through that migration, we also have staff on hand to advice as appropriate. And at the other ends of the migration, there are more robust, more secure and more scalable platform waiting for you. So your mileage may vary, but we've seen customers, throughput increased by 10% up to a hundred percent from upgrading from Cashin ensemble, 20 eighteen.one, two, the latest virus releases. And then they even have to start looking at all of the new stuff that we added into being tied to Iris. Speaker 0 00:16:29 Right. Right. So, yeah. So, you know, with each release, it feels like there's just more and more, that adds up and more reasons for people to move to the Iris platform and to be able to take advantage of all these features. So, um, Benjamin, thanks so much for joining us again, and I'm sure we'll have you on soon about some of these topics that you mentioned as well. Speaker 0 00:16:54 Thanks again to Benjamin for joining us. If you enjoy hearing Benjamin breakdown, our product stack definitely check out episode 17 from this spring when he helped us to dive into the analytics and AI part of the InterSystems technology stack, keep an eye out for more materials around this most recent release and as always check out learning.intersystems.com as well. One notable change we made recently on the learning site has been the addition of a learn the latest button on the homepage. This will show you items in the learning catalog that have been released within the last 90 days. So it's a great way to know if we published a new video or course or any other online materials, that'll do it for episode 19. We'll see you next time on data points.