Data Points

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

Data Points
19. What's New in Version 2021.1 of InterSystems IRIS?
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In this episode, Product Manager Benjamin De Boe helps us break down all of the new and exciting features and improvements in the 2021.1 release of InterSystems IRIS® data platform. Benjamin tells us about exciting new developments in analytics, business intelligence, machine learning, development gateways, FHIR capabilities, and more.

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EPISODE TRANSCRIPT

Derek Robinson 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 found at datapoints.intersystems.com. I'm Derek Robinson. And on today's episode, I'll chat with Product Manager Benjamin De Boe about what's new and noteworthy in the 2021.1 release of InterSystems IRIS.

Derek Robinson 00:00:39 Welcome 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 De Boe. Benjamin will talk to us about the 2021.1 release of InterSystems IRIS. From analytics to business intelligence, to machine learning, to development gateways into FHIR improvements, Benjamin will walk us through all of the latest and greatest from the most recent release of InterSystems IRIS.

Derek Robinson 00:01:12 All right, and welcome to the podcast, Benjamin De Boe, making what I think is your third podcast appearance now. So Benjamin, thanks for joining us.

Benjamin De Boe 00:01:19 Pleasure, Derek. Thanks for having this.

Derek Robinson 00:01:22 So today we're going to talk about the 2021.1 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, 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?

Benjamin De Boe 00:01:40 That's unfair, you're on one of the highest floors of the building (laughs), but anyway. So I think the most important thing, or the most important leap forward that we made in this release is what we did in analytics. We've made really a lot of investments. We've introduced InterSystems IRIS Adaptive Analytics, which is a new add-on capability in this release. We've made IntegratedML, 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 analytical queries.

Derek Robinson 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; in one of our recent episodes, we talked about analytics and AI. 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 ten-second description.

Benjamin De Boe 00:02:30 Yeah, absolutely, and it's probably worth its own dedicated podcast in a while, but essentially it enables customer to define their logical data model on top of data that's in their IRIS database, in business terms: so business measures, business dimensions, but it makes sense to business users and analysts. And then the technology in Adaptive Analytics takes care of mapping those business measures and business dimensions to whichever native format, their preferred tool of the day, for end-user data visualization or BI, prefers, but that could be Tableau, Power BI, even Excel, but also, many, many other BI tools. So because Adaptive Analytics takes care of that mapping of the business model to what those tools can represent and can show to them natively, time to insight for those end users.

Benjamin De Boe 00:03:24 And then the best part for me as a techie, is why we're calling it adaptive. So Adaptive Analytics will not just 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 s, it will start looking for frequent patterns and it will pre-aggregate interim results for those; it will cache query results for those in a very smart way so that it can serve futureoff those prebuilt structure, so that it can support many more users, much more data, much more effectively. That's all going totally autonomous; it's a really cool piece of technology.

Derek Robinson 00:04:10 Right. Nice. And, you know, I think, when we had Carmen on a few episodes ago, we talked a little bit about, the differences between like a partnership and a homegrown technology in 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, talk a little bit about how that relates between Adaptive Analytics and InterSystems IRIS BI.

Benjamin De Boe 00:04:33 Yeah. That's a very appropriate question because it sounds very similar 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 under its older name DeepSee, is entirely embedded in InterSystems IRIS, from the low-level interaction with sourcethrough our own custom-built , all the way up to the data visualization part, analyzer dashboards. That's all embedded inside InterSystems IRIS. And that embedded model enables us to do a couple of really cool things, so we can make sure that your IRIS BI cubes always show you real-time data because we keep them automatically in sync with the low-level data structure . We can make sure that if you're building an application on InterSystems IRIS, that in that application, you can also render a couple of charts or entire dashboards that are also customized according to your application…and just constantly, so that 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 archived or put on the mail. That model is really applicable to application partners that want to keep their deployments simple, and just have powerful analytics embedded into those applications. Now with Adaptive Analytics, we're targeting a slightly different audience. So I already mentioned that we're catering to business users that may use a variety of other third-party tools: Tableau, Power BI, Excel, et cetera. So you may be working in a big organization that has a really large data warehouse that needs to support those different user groups, each with their own preferred tool. So that's where Adaptive Analytics can provide exactly that capability. 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 of InterSystems IRIS BI. Actually, if you are an IRIS BI user, you'll see that we made a couple of really nice performance enhancements 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.

Derek Robinson 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 fitting different use cases for different customers. So going back kind of to the, the rundown you gave before, you mentioned a little bit about IntegratedML, so tell us what's new in that area.

Benjamin De Boe 00:07:16 Yeah. Last fall we did release IntegratedML on a 2020.3-based kit. And now, we're making it part of the main release, of our .1 release, which is the extended maintenance release, without really making it a standard part of the kit. What IntegratedML offers, Tom Dyar and our team already had a podcast specifically devoted to this project. But in a nutshell, the idea of IntegratedML is that it offers a simple SQL interface .

Derek Robinson 00:07:54 Right. Nice. And 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. So that sounds like a lot of analytic stuff and a lot of stuff, and between you, Carmen, and Tom, the product managers that we talked to last time, a lot in your area. So, tell us a little bit about what else might have happened in other areas of the product.

Benjamin De Boe 00:08:16 What do you mean, what else? (laughs) It would be a little unfair to monopolize everything with analytics. But one of the other main highlights of this release is our support for Kubernetes. If you're a system administrator and 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 gotten complex to configure and 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 Kubernetes services. So what Kubernetes does is it facilitates the declarative configuration and automation of containerized workloads. That's a mouthful, but what it means is that 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 buttons each. So how do we support Kubernetes? We've released the InterSystems Kubernetes Operator, which is available with InterSystems IRIS 2021.1. And it extends Kubernetes with best practices with Operator that can help automate the management of an InterSystems IRIS cluster. So it embeds best practices, it embeds boilerplate stuff to make everything smoother and really work well, so that you don't even have to do all of that piping of that very simple text file.

Derek Robinson 00:09:47 Right, right. Nice. Yeah. And I think over a year ago, we did a podcast episode about Kubernetes the technology, but not so much about the InterSystems Kubernetes Operator. So good to know 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 all be using Kubernetes as part of their technology stack within IRIS?  

Benjamin De Boe 00:10:10 I think it's worth a look for every system administrator, but it's absolutely not enough. With prior products, such as InterSystems Cloud Manager, we offered this as an add-on to make your life easier. Now with IKO, we actually had to make some of the configuration effort (remember those 20,000 buttons in a configuration interface). We've had to make our own a little more straightforward for IKO to just 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 with.

Derek Robinson 00:11:00 Cool. So it sounds like a lot of good stuff for analysts, system admins. How about developers? What in this release really jumps out at them and can be beneficial for them?

Benjamin De Boe 00:11:09 It's definitely one of our favorite audiences with InterSystems IRIS. 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've done a lot of small things such as .Net Core support, .Net Core 2.1 support, which may be very big. We've added connection pooling for JDBC and have some really good feedback from early adopters on that. And also some completeness work on the native APIs, 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 implement business logic in Java or business logic in .Net, and then call it from ObjectScript, or call it from your business processes.

Benjamin De Boe 00:12:00 So we've added Python and R to that list, and we've significantly improved the manageability of those gateways. So we've turned them now into an external language server that will start automatically; they are declaratively configured, so it sounds a little bit like the Kubernetes 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-entrance connection—a bit of a tricky term, but what it means is that if you're invoking formal text scripts in 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 security context privileges, without you having to do anything. So that makes that interplay between your IRIS native codes and then the code running on your external language server, much, much smoother, and it just enables you to build nicer hybrid applications.

Derek Robinson 00:13:03 Nice, nice. So it sounds like we're kind of all in here on a modern app development with these improvements and kind of enhancements.

Benjamin De Boe 00:13:10 Yep, absolutely. And not just for the app development itself, but also for managing the APIs to which you expose them. So we've also released a new version of InterSystems API Manager, Version 2.3, which now has hybrid mode, which helps you deploy highly scalable and highly available environments. We've also added Ksupport and made some general enhancements to the overall user experience.

Derek Robinson 00:13:38 Right, right. Nice. So it sounds like, you just listed off a bunch of stuff that we could do future episodes on. So, that's also good to hear. So, shifting gears a little bit, we've talked mostly about really the data platform side of things. What is notable in the healthcare space for this release?

Benjamin De Boe 00:13:55 As usual, we've also invested a lot in our healthcare support, specifically in FHIR support. So in prior releases, we already supported FHIR and Smart on FHIR applications, both in the client and server mode, but now for IRIS for Health and HealthShare Health Connect, which were also part of this release, we've really added a lot of new FHIR-related capabilities, especially if you get the continuous delivery releases for the 2020.2, .3, and .4 that we've released in the meantime. So if you hadn't tuned into those, make sure to look for their launch webinars and release notes as well. But now if you want to skip all of that, so we've got support for So that's really upping our game for FHIR. Also, to help customers migrate to our platform, we've extended the HL7 migration toolkit to automatically convert confirmation logic that was developed on third-party platforms, Cloverleaf, Delegate, or eGate. So anything you did on those interface engines can now be migrated automatically to HealthShare Health Connect or IRIS for Health.

Derek Robinson 00:15:15 Right, right. Nice. That's great stuff. So last question here, you know, one of the things that I feel like comes up with every new release really is the question, what does this mean for existing Caché and Ensemble customers that might be out there?

Benjamin De Boe 00:15:29 It's just a ton of new reasons to switch over to InterSystems IRIS. We think many of our customers that are still on Caché 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 live on InterSystems IRIS for a while now. So we offer tools to convert existing instances to IRIS, and to help you through this migration, we also have staff on hand to advise as appropriate. And at the other end of the migration, there's a faster, more robust, more secure, and more scalable platform waiting for you. So your mileage may vary, but we've seen customers' throughput increase by 10% up to a hundred percent just from upgrading from Caché and Ensemble 2018.1 to the latest IRIS releases. And then they even have to start looking at all of the new stuff that we added in the meantime into IRIS.

Derek Robinson 00:16:29 Right. Right. So, yeah. 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, 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.

Benjamin De Boe 00:16:47  My pleasure. Thanks, Derek!

Derek Robinson 00:16:54 Thanks again to Benjamin for joining us. If you enjoy hearing Benjamin break down 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've 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.


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