In the world of enterprise major incident management, integrating partial or full automation across each stage of the incident response and management lifecycle makes a big difference to the speed incidents are addressed and the data you have to understand them afterward. Gartner coined the term “Incident Response Automation” in its 2020 report Automate Incident Response to Enhance Incident Management.

Working with technology means dealing with incidents or outages from time-to-time, so staying on top of problems is essential. Back in the spring of 2022, Clearco, the world’s largest e-commerce investor, had an alerting system set up to catch issues, except they had one problem: Clearco’s Customer Success team would learn of a problem before a notification even went off.

The outages span the giants of the Internet and some of the biggest failures of IT resilience we were subject to – from AWS’s trifecta of outages in December 2021 to the October ‘21 outage that took down Facebook, Instagram, WhatsApp, and interrelated services. We also look at some more intermittent outages that you may have missed.

You’ve probably heard the phrase “transparency is key” more than you can bear at this point—so let’s get this out of the way. Transparency is key. The phrase suddenly became that much more unbearable. But before you drop off, let me also communicate something else: transparency is often not enough. Often, companies make the mistake of leaning on transparency as a catchall solution to many of their internal comms issues.

Users have been generating increasing amounts of data in the past few years, partly due to rapid digitalization since the pandemic. As a result, increasing numbers of analytics applications are capitalizing on these data assets. However, building scalable systems is no trivial task and incidents are inevitable. Complex systems generate data in the form of logs, traces, metrics, and more, which organizations often find themselves sprinting through. Such logs are a powerhouse of valuable information.