“The primary use case of AIOps is to ingest multiple monitoring data feeds”
We spoke with Eric Cook, Director of EMEA Solutions Consulting at OpsRamp about a new report from OpsRamp and how UK-based IT operations professionals feel about the tools that they use. Do IT professionals use too many tools and how satisfied are they with their infrastructure?
JAXenter: Today OpsRamp published a study on how UK-based IT operations professionals feel about the tools they’re using and the extent to which those tools support the needs of the IT department and business going forward. A key takeaway from the study is that IT Ops pros have too many tools, and only 27% of respondents said they are highly satisfied with their current IT infrastructure monitoring solutions. Why is that?
Eric Cook: In many cases, it’s because the tools ITOps teams are using just haven’t kept pace with the technology. If you’re just monitoring bare-metal servers and networks in your own data center the same way you did 15-20 years ago, you can probably keep on using your legacy monitoring tools.
But once you have to manage virtualized and hyperconverged infrastructure in-house and cloud infrastructure outside the firewall, you need a new set of monitoring tools to make sense of it all.
Legacy tools can’t keep up and ops teams then find themselves with multiple tools producing multiple monitoring data feeds to analyze, correlate and make sense of. It’s not hard to see why ITOps would get frustrated with their current tools.
JAXenter: The survey also talks about areas for improvement in IT infrastructure monitoring, such as the ability to monitor hybrid, multi-cloud and cloud-native infrastructure, integrate data and automate incident response for efficient and timely operations, and support business goals with accurate and relevant insights. Apparently AIOps has become a focal point for this “tool rationalisation.” What do you see as the role of AIOps in IT infrastructure management platforms going forward?
Eric Cook: AIOps has emerged as a term to describe any algorithmic-driven unsupervised process automation. Gartner defines it as the application of machine learning and data science to any IT operations problem.
To us, the primary use case of AIOps is to ingest multiple monitoring data feeds, algorithmically organize this data according to different data models, and extract the insights for alert management, event and incident identification, and escalation of incidents for rapid resolution.
It’s ideal for performance management and general service availability, and can ultimately reduce operational cost for IT teams through the savings realized in operator hours and point tool sprawl.
JAXenter: According to the OpsRamp study, IT ops leaders see huge value in deploying a digital operations management platform that offers capabilities for hybrid, multi-cloud and cloud-native monitoring, intelligent incident management and automated remediation. Per the study, 56% of respondents said they expect to roll out a digital operations management platform this year. Can you explain the difference between a legacy IT infrastructure management platform and a digital operations management platform, and why you think the latter will be the preferred solution going forward?
Eric Cook: It gets back to what I said above. Legacy IT infrastructure management platforms are great at monitoring legacy IT systems–one app per server running in your own data center.
But what happens when you start to virtualize those servers or replace your traditional server architecture with HCI? What happens if you need to spin up new workloads in the cloud–AWS, GCP, Microsoft Azure, etc.–and monitor their performance, integrated with everything you’re managing internally? Digital transformation has made this hybrid infrastructure a reality and the Covid pandemic has accelerated digital transformation.
A true digital operations management platform that can monitor these environments and provide you the answers you’re looking for without a lot of data integration heavy lifting is the answer.