Site reliability engineering (SRE) is what you get when you treat operations as if it’s a software problem. The mission of an SRE practice is to protect, provide for and progress the software and systems offered and managed by an organization with an ever-watchful eye on their availability, latency, performance and capacity.1.
What is AIOps? How does an AIOps platform help your observability practice? AIOps platforms analyze telemetry and events, and identify meaningful patterns that provide insights to support proactive responses. AIOps platforms have five characteristics:1 The above is Gartner’s definition and is part of the Gartner® “Market Guide for AIOps Platforms.” The Gartner definition is also aligned with our view.
A few episodes ago, we talked with fellow podcaster and tech evangelist Dotan Horovits. During that episode, Dotan shared that he wrote a blog post with Jujhar Singh called “How Much Observability Is Enough?” which is definitely a recommended read if you’re implementing observability and feeling overwhelmed. After reading this article, we were eager to invite Jujhar to the StackPod as well, to dive into this topic a bit more.
As more companies adopt SaaS services over on-premise delivery models, there is a natural concern around data security and platform availability. Words on a vendor’s website can provide insights to prospective customers on the process and policies that companies have in place to alleviate these concerns. However, the old adage of “actions speak louder than words” does apply. Trust in a website’s words only goes so far.
A while ago, we asked our customers to write reviews about their experiences working with us. With an average rating of 4.6 out of 5 and ten reviews submitted and published within two weeks, we were humbled by the responses. As our CEO, Toffer Winslow wrote, “Perhaps the thing I was most proud of…was just how frequently our customers commented on the high quality of StackState employees they interact with and the caliber of service we deliver.”
Recently I heard one of our prospects talk about a competitor who was promoting their data lake and ask, how are we different than that? His question got me thinking about why a data lake alone does not provide the depth of observability you really need. The goal of observability is to help SREs, IT Ops and DevOps teams run their IT systems with close-to-zero downtime. Consolidating data from across your environment into a data lake is certainly a good step.
As a gold sponsor for DevOps Institute’s fourth annual Upskilling IT report, we compiled some key takeaways. However, there is so much more to get from this report – so download and read the full report today. In this technology-driven world, skills have a very limited shelf life. The knowledge, tools and resources we rely on in the moment rarely stay relevant or useful forever – especially with rapidly changing demands.
This week we released v5.0 of StackState’s observability and AIOps platform, which introduces a rich set of new capabilities. Our latest release contains a little something for everyone responsible for reliably running business critical workloads in dynamic environments – SREs, DevOps, central platform teams, even business teams – and for new and existing users alike.
Until I came to StackState seven years ago, I was selling for Splunk. Everyone that has big data knows Splunk – big data, big data lakes, observability data, data analysis. Anything to do with data, Splunk is there! While at Splunk, I had the good fortune to sign up a reseller by the name of UMBRiO. Together, with Erik Witte and his team, we sold a multi-million dollar deal to a large, multi-national bank in the Netherlands that put our partnership on the map.
When we came across Dotan’s article “Observability Is a Data Analytics Problem” on LinkedIn, he got our full attention. We totally agree with his views on observability and data analytics.
