Operations | Monitoring | ITSM | DevOps | Cloud

GigaOm’s latest Radar for AIOps solutions has just been released and it makes for compelling reading for anyone trying to maximize organizational performance in our digital world. Particularly if you’re down with DevOps.

This has been quite the summer to remember as we continue to witness our customers achieve remarkable efficiencies through automation such as deep integrations with change pipelines to suppress alerts during maintenance windows and correlating alerts to create incidents with dynamic and evolving descriptions that dramatically improve Incident management processes.

People’s involvement has been inevitable with log management despite advancements in ITOps. Log management at a high level collects and indexes all your application and system log files so that you can search through them quickly. It also lets you define rules based on log patterns so that you can get alerts when an anomaly occurs. Log management analytics solution leveraging RDA has been able to detect anomalies and aid predictive models over a machine learning layer.

On this day in 1955, the first edition of the “Guinness Book of Records” was published in London.

Historically, enterprise IT organizations have turned to application performance management (APM) systems to monitor and manage critical applications. However, throughout the world, enterprise organizations are suffering massive and systemic failures at an increasing rate. One of the main reasons these failures are increasing is that organizations aggressively seek to execute digital transformation initiatives.

High performance automobiles are built to be driven on the open road, at high speeds, hugging each curve and accelerating on the straightaways—they’re not for trips to the grocery store.

This is the twelfth chapter in The Observability Odyssey, a book exploring the role that intelligent observability plays in the day-to-day life of smart teams. In this chapter, our SRE, Dinesh, brings together his colleagues with an interest in AI.

You’ve seen the movie. You know the scene. There’s a diabolical criminal on the loose, a city in fear—and one obsessed investigator in dogged pursuit of justice. Her eyes are bloodshot from too many sleepless nights, too much caffeine, and too many cigarettes. She paces frantically in a windowless room. On the wall is a corkboard festooned with maps, notes, and pictures, and a web of red string is woven haphazardly across a clutter of seemingly unrelated clues.