IBM has stepped up its bets on the hybrid cloud. With several acquisitions in the past few months, the company has added depth to its AI-powered application automation services for hybrid cloud customers to help them increase efficiency, cut costs and make operations easier to use.
The acquisition of the startup Instana Inc., which is expected to be combined with the recently acquired Turbonomic platform, is responsible for the piece of automated observability in this infrastructure. Instana helps organizations to track the health of their workloads to identify technical issues that may interfere with the user experience.
“Observability is basically the next generation of monitoring, which means [that] it provides data from a system, from an application to the outside, so that people from the outside can basically judge what’s happening inside of an application,” said Mirko Novakovic (pictured, left), chief executive officer of Instana – an IBM Company. “Observability gives you the ability to really deep dive and see all the relevant metrics, logs and application flows to understand why something is not working as you would expect.”
Novakovic spoke with John Walls, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during IBM Think. At the same event, but in a separate interview, Pavlo Baron (pictured, right), founder and chief technology officer of Instana, spoke with theCUBE host Dave Vellante. In both interviews, they discussed Instana’s key differentiators, how these features will complement IBM’s hybrid cloud strategy, and the prospects and challenges of that environment. (* Disclosure below.)
Here’s the full video interview with Mirko Novakovic:
Getting context for breaking data silos
Instana has three fundamental characteristics that set it apart in the market and that take application performance management to a higher level, according to Novakovic. The number one feature is automation.
“The way we gather this information is fully automated, so you don’t have to configure anything,” he explained. “We get inside of your code, we analyze the flow up the application, we get the errors, the logs and the metrics fully automatic.”
The second is getting context that aims to overcome one of the biggest problems with monitoring, which is working with many data silos. The context ties those data automatically together so that it is possible to get real information out of all the data.
“And the third is that we provide actions,” Novakovic said. “So, basically, we use AI to figure out what the problem is and then automate things. Is it a problem resolution restarting a container or resizing your cloud? That’s what we suggest automatically out of all the contexts and data that we’ve gathered.”
Bringing these functions together, instead of keeping them separate, makes using the product much simpler for businesses. And solving issues gets faster.
“The time from a problem to resolve … gets significantly reduced because normally you have to do that correlation of data manually, and now, with that context, you get this automated by a machine and we even suggest to you these intelligent actions to fix the problem,” he added.
The combination of Instana with IBM’s Watson AIOps is a perfect match, according to Novakovic “because we are suggesting an action, and the next step is really fully automating this action with something like … the AIOps and the automation functionality that IBM has so that the end users not only get the information about what to do, the machine even does and fixes the problem automatically.”
Automating everything possible
Instana started about five years ago with the idea that classic APM solutions no longer worked in a technology environment with many changes, such as the growing use of Kubernetes, migrations to the cloud native and the move toward microservices. To accommodate rapid changes in the market, Instana has developed an approach to automate everything possible.
“Our idea was: ‘Hey, just get rid of the unnecessary work because you keep people busy with stuff that they should not be doing, like manually watching dashboards, setting up agents with every single software change, like adopting configuration, etc.,” Baron said. “All of these things can be done automatically to a very, very, very large extent.”
This strategy is pretty different from the classic APM world, which is typically “very expert heavy,” according to Baron.
“We try to automate the expert,” he explained. “We have this guy called Stan, [and] this is your kind of virtual DevOps engineer. It has AI in there, it has some artificial brain, it never sleeps and it observes all of the problems.”
Another differential of Instana is that its platform was created to adapt to continuous changes.
“Container comes up, you need to know … what kind of workload this thing is, how it is connected to all the others, and then, at some point, probably it’s going to go through a change and get a new version,” Baron said. “You need to capture this whole life cycle without really changing your monitoring system.”
Technically, Instana’s work involves all the data structure, as it breaks down the entire “IT geography” to make connections in multiple directions and from different nodes.
“We’re decomposing this from the beginning of the product, which allows us to have a very deep and hierarchical understanding of the problem when it appears, so we can nail it not down to a metric that probably doesn’t make sense to any user, but really name the cause,” Baron concluded.
Watch the full video interview with Pavlo Baron below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of IBM Think. (* Disclosure: TheCUBE is a paid media partner for IBM Think. Neither IBM, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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