Report: Data Done Right for AIOps with RDA
Most of the AIOps companies are doing the process right, some use AI and ML properly, but most fail on how to automate data processing, or DataOps, on how to get the right data to AIOps tools at the right time. In this eBook "Data Done Right for AIOps," I discuss this in detail and offer some possible solutions including Robotic Data Automation (RDA).
Edge visibility & architecture chat with Mark Thiele, CEO, Edgevana.
I am very honored to be part of the Edgevana podcast series talking to the legendary Mark Thiele on various edge, AI, AIOps, total observability at edge, and other related topics.
AIOps Has a Data(Ops) Problem
Modern complex systems are easy to develop and deploy but extremely difficult to observe. Their IT Ops data gets very messy. If you have ever worked with modern Ops teams, you will know this. There are multiple issues with data, from collection to processing to storage to getting proper insights at the right time.
Report: Observability deep dive report for Zebrium
Summary I did a deep dive vendor research report on Zebrium which specializes in automatic root cause analysis using machine leaning. Quick summary from the report: Zebrium is an Observability/AIOps platform that uses unsupervised machine learning to auto-detect software problems and automatically find root causes, reducing manual labor and speeding […]
Achieving Reliable Observability Part 1 – Making Cloud-Native Observability More Robust
I was having a conversation with a CxO level customer as part of an AIOps/Observability workshop, and from what I could tell, most are confused about how to properly operationalize cloud-native production environments – especially the monitoring/observability portion. Here is how the conversation went.
What is AIOps? – AI for IT operations explained
Every business now depends on IT. Efficient IT Operations is mandatory for all businesses, especially those operating in a hybrid mode – a mix of existing data centers and multi-cloud locations. As with any business process, IT operations can be augmented with machine learning-based solutions. IT is particularly fertile ground for AI as it is mostly digital, has seemingly endless processes requiring automation and there are gigantic amounts of data to process.
Comprehensive observability is core to future-proofing your IT infrastructure
Observability is an emerging set of practices, platforms, and tools that goes beyond monitoring to provide insight into the internal state of systems by analyzing external outputs. Monitoring has been a core function of IT for decades, but old approaches have become inadequate for a variety of reasons—cloud deployments, agile development methodology, continuous deployments, and new DevOps practices among them.
Report: GigaOm Radar for Cloud Observability
Summary Observability is an emerging set of practices, platforms, and tools that goes beyond monitoring to provide insight into the internal state of systems by analyzing external outputs. It’s a concept that has its roots in 19th century control theory concepts and is rapidly gaining traction today. Of course, monitoring has been […]
AIOps vs Observability vs Monitoring – What Is The Difference? Are You Using The Right One For Your Enterprise?
This article was originally published in Forbes on Feb 2, 2021 In the last few months, I have been analyzing and writing a research report for GigaOm in this space, which is due to be released soon. I looked at about 30+ vendors in this space as part of that […]
