Rick Fitz, senior vice president of IT Markets for Splunk, said the provider of widely used operational analytics software in the enterprise sees a significant opportunity to expand its presence across a range of DevOps processes.
Incident management is a natural extension of operational analytics, said Fitz, noting Splunk chose to acquire VictorOps because the investments the company has made in applying machine learning algorithms to monitoring IT events. That approach significantly reduces the number of irrelevant alerts being generated and provides actionable intelligence into potential events that could adversely impact IT operations.
Most IT operations teams suffer from alert fatigue, Fitz noted, and most alerts are ignored because of a lack of context. The combination of Splunk and VictorOps will result in alerts that more precisely identify the root cause of any IT issue, he said, and a better overall “systems of engagement” for IT operations teams in keeping with DevOps principles.
Splunk has been steadily expanding its focus on DevOps. Earlier this year the company announced Splunk Insights for Infrastructure , which IT organizations can host on an Amazon Web Services (AWS) public cloud to monitor IT infrastructure deployed anywhere. The latest versions of Splunk Cloud and Splunk Enterprise also make use of machine learning algorithms on top of a revamped metrics engine that enables IT administrators to monitor everything from CPU speeds and available hard disk space to temperature readings in internet of things (IoT) devices and sensors. Splunk recently also added connectors for Docker and Kubernetes, as well as the Apache Kafka messaging platform for streaming data in real time.
IT operations and cybersecurity teams already rely on Splunk operational analytics software extensively to identify anomalies. By investing in machine learning algorithms and acquiring incident management software, Splunk is moving to turn all the data it analyzes into actionable intelligence, which then could be shared in real time with developers to ensure application availability and optimize application performance.
While adoption of DevOps processes in traditional enterprise IT organizations remains spotty, IT vendors that focus on IT operations such as Splunk have clearly seen the writing on the wall. Fitz noted that investments made in machine learning algorithms, for example, will enable IT operations teams to more respond to changing application requirements with greater agility at a time when the IT environment has become exceedingly complex. That agility is critical for any organization engaged in digital business transformation, Fitz said, because invariably those efforts lead to more applications being deployed.
It’s not clear the degree to which incumbent providers of IT operations software will be able to remain relevant in the age of DevOps. But most of them certainly have the financial resources to at the very least acquire a portfolio of DevOps tools that will enable them to exert a lot more influence than many of them have to date.
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