Tech News

Tuesday, 1 May 2018

ScienceLogic release gives IT view across entire stack

It’s tough being part of IT Ops these days. Your company could be operating across public and private clouds, and in many cases, an internal datacenter too. Meanwhile your developers are generating more code ever faster. ScienceLogic wants to help with it latest release, ScienceLogic SL1.

As company CEO Dave Link sees, we are seeing this vast confluence of technology influences coming together very quickly. He says the goal with this release is nothing less than a comprehensive, full-stack view of how an application is behaving, and how the different pieces that make up and connect to that application could be affecting its performance.

“Every CIO wants to know the health of their mission critical business services and only way to see that is to see through the entire stack,” Link said.

Part of the problem of course is the sheer volume of information. As that increases, it becomes nearly impossible for humans, even the most highly skilled among us, to keep up and understand what particular element may be causing an application to misbehave.  That problem is exacerbated further by the speed at which developers are generating new code.

Murali Nemani, CMO at ScienceLogic, says that’s where artificial intelligence and machine learning come into play. “Part of the problem is that if businesses are moving at machine speed in terms of their capability to innovate, the big challenge is how do you get operations to keep up with what developers are creating,” Nemani asked.

The machine learning aspect of the platform enables companies to begin automating solutions for some of the more common problems, while directing the more unusual ones to humans on the operations team. They rely on the AI tools produced by others, rather than trying to develop that part of the solution themselves. “If an application is performing poorly, we can diagnose which part is the problem child, then feed this information to AI/ML engines like Google TensorFlow or IBM Watson and see pattern recognition. That’s the way we achieve machine speed,” Nemani explained.

Link says they do this by looking at the problem holistically and giving operations a full view of the application to track down the problem behavior and fix it. “We look at all the layers when we think of a service view: security, systems, network, OS, infrastructure then the application layer (database and application tier). We then contextualize all of those elements into one service view, so [the customer has] the most efficient view of what’s happening in real time,” Link said.

The product being announced publicly today has been early Beta up to now and will be generally available on July 25th.



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