Operations | Monitoring | ITSM | DevOps | Cloud

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.

A summary of our third Moogsoft engineering Twitch Stream chatting about all things DevOps

Digital transformations can entail significant shifts in technology, such as migrating from on-site architecture to cloud services, and these complex transformations generate massive amounts of data. Data transparency is a must-have, and observability with AIOps delivers the solution. Through a unified view of data, AIOps guides DevOps and SRE teams through the swamp of information

Robotic data automation (RDA) is designed to optimize IT functions for a broad spectrum. It is the next generation data automation technology that is specifically designed to bring efficiencies to multiple IT functions including CXO/IT leaders decision making, IT Ops, Helpdesk, Salesforce.com, ServiceNow and other applications used by enterprises.