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Home » Blogs » DevOps Practice » Splunk Aims to Trigger DevOps Processes

Splunk Aims to Trigger DevOps Processes

Avatar photoBy: Mike Vizard on October 4, 2018 1 Comment

Splunk this week at its .conf18 conference continued a campaign to extend the reach of its operational analytics platform into the realm of DevOps through a partnership with Puppet.

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Spunk also announced the 4.0 release of Splunk IT Service Intelligence (ITSI), which extends a platform for managing IT using machine learning algorithms by integrating it with incident management software Splunk gained via its acquisition of VictorOps. Other new capabilities include support for a set of key performance indicators (KPIs) for tracking metrics such as application workloads and the ability to do root cause analysis on any event the machine learning algorithms predict.

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Andi Mann, chief technology advocate for Splunk, said the alliance with Puppet furthers Splunk’s ambitions to be a primary source of data used to inform automation frameworks that are at the heart of any set of DevOps processes. Over time, Splunk will continue to expand its DevOps partnerships with an eye toward being the analytics platform used to trigger automated processes using frameworks developed by Puppet and others, he said.

At the same time, Splunk continues to develop orchestration capabilities of its own based on technologies it gained via its acquisition of Phantom. While that orchestration software primarily is used today in a security management application, Mann said Splunk is now looking at applying that software more broadly, as it encouraged developers to build applications using a Splunk Developer Cloud now in beta.

Mann said that when it comes to machine learning in IT operations, otherwise known as AIOps, the most challenging task ahead is establishing trust. IT professionals are not going to sanction a “black box” approach that doesn’t enable them to see how a machine learning framework is determining what to automate. Because of that issue, Mann said, providing a root cause analysis capability in ITSI is critical.

The next big issue facing organizations, he noted, is improving the quality of the data being used to inform a machine learning framework. One of the benefits of the DevOps movement is that, as developers take responsibility for both building and running applications, more of them are paying attention to how log data is being created. Mann said the notes developers leave within an application on how to resolve issues are becoming more detailed, a process that Splunk refers to as “semantic logging.”

Mann noted the goal is to create a closed-loop system where every IT issue eventually creates a ticket in a DevOps system for developers to address. The bridge between those processes will be the chat capabilities provided by the VictorOps incident management platform. In fact, Mann said Splunk is moving from being a provider of log analytics software to being a provider of a continuous monitoring solution that analyzes data both stored in logs and in near real-time using a Splunk Data Stream Processor, which is currently in beta.

It may take a while for that loop to be completely closed. But it’s clear that many of the tools that IT operations teams rely on today are becoming increasingly DevOps-friendly.

— Mike Vizard

Filed Under: AI, Application Performance Management/Monitoring, Blogs, DevOps Practice, News Tagged With: devops, machine learning, monitoring, orchestration, Puppet, Splunk

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