21 articles
Most postmortems identify symptoms, not causes. This post explains why traditional root cause analysis fails in modern systems (especially microservices) and introduces a faster, data-driven approach using dependency mapping and event timelines to find root causes in minutes instead of hours.
Jasmine Decker
Your system doesn’t fail randomly; failures are connected. A deployment triggers an error, which triggers alerts, which escalates into an incident. This guide explains how event correlation works, why most teams don’t implement it properly, and how correlating signals across tools reduces diagnosis time by 70%.
Jake Davids
When a major incident hits, someone has to be in charge. Not "in charge" in the sense of knowing the most about the systems - in charge in the sense of coordinating the response, making decisions under pressure, and keeping the team moving toward resolution. That's the incident commander. It's one of the most impactful roles in incident management and one of the least understood by engineers who haven't had to do it.
Andrea Brown
These two terms get used interchangeably in most engineering conversations - but they describe different things, and conflating them creates real gaps. Incident response is the real-time process of detecting and resolving a production problem. Incident management is the broader discipline that governs how your organization handles incidents before, during, and after they happen. The investments that improve each one are different.
Janelle McCombs
Your status page shows 99.9% uptime. Your customers are still complaining. That's the reliability vs. availability gap - and it trips up a lot of engineering teams. Availability is a number you can put on a status page. Reliability is whether your system actually does what users need it to do, consistently, over time. The two are related but not the same.
Andrea Brown
At 2am with three engineers and five things going wrong, which do you fix first? If the answer depends on who's on call, you have a prioritization problem. An incident priority matrix takes that decision out of the individual's head and puts it into a shared framework - so the right incidents get the right attention, every time.
Alexander Eric
Atlassian is sunsetting Opsgenie as a standalone product. Thousands of teams need a migration path. This is an honest breakdown of the real alternatives - what each does well, where each falls short, and how to pick the right one based on what your team actually needs, not what sounds best in a demo.
Janelle McCombs
Your on-call engineer's phone goes off six times before 3am. By night three, they stop reaching for it with urgency. That's alert fatigue - and it's not a people problem, it's a systems problem. Here's what actually causes it, what it costs in MTTR and retention, and how to fix it structurally.
Andrea Brown
99.999% availability sounds like the gold standard. In practice it means your system can be down for 5 minutes per year - total. One deployment rollback and you've already missed it. Here's what five nines actually requires, what each level of the nines costs, and how to set the right target for your system.
Rosemary Samuel
Three acronyms used interchangeably, rarely defined precisely. SLIs are measurements. SLOs are targets. SLAs are contracts with consequences. Getting the hierarchy right changes how your team talks about reliability - and how you make deployment decisions at 2am.
Jake Davids
Google invented SRE in 2003 because hiring more sysadmins wasn't working. Twenty years later it's one of the most sought-after disciplines in engineering. Here's what it actually means, what SREs do day-to-day, and how to know whether your organization is ready for it.
Alexander Eric
Learn how to write incident response runbooks that actually work. Includes templates, examples, common mistakes, and how to make runbooks your team will actually use.
Andrea Brown
Track these 8 incident response metrics to measure and improve your IR program. Includes benchmarks, calculation methods, and improvement roadmaps.
Rosemary Samuel
Traditional incident response fails in microservices. Learn why, and discover the framework for incident response in microservices architecture with real-world examples.
Janelle McCombs
AI-powered incident extraction catches 50-70% more incidents than static alerts. Learn how ML anomaly detection works and how to implement it in your infrastructure.
Andrea Brown
Learn why consolidating operations data into a single pane of glass is critical. Discover how teams reduce incident response time and improve visibility by 80%.
Jake Davids
Learn how to prevent on-call burnout and protect your engineering team. Discover warning signs, proven strategies, and how to reduce burnout by 40%.
Rosemary Samuel
Master incident response with this complete framework. Learn best practices for faster resolution, better communication, and preventing future incidents.
Jake Davids
Discover how one engineering team reduced incident diagnosis time by 82% by aggregating operational signals across tools. Learn the strategies you can implement today.
Rosemary Samuel
Most teams spend 15-30 minutes just finding incidents in Slack, Teams, GitHub, Discord, and Pagerduty instead of responding to them. Centralized event monitoring reduces detection latency by 80-85% and MTTR by 40-50%. Learn how companies achieve these improvements and implement centralized monitoring in 4 weeks.
Jake Davids
Traditional rule-based monitoring has fundamental limitations: it's binary, context-blind, and misses edge cases. AI-powered incident extraction uses machine learning to understand context, correlate signals, and catch anomalies that rule-based systems overlook. Learn how ML models trained on your data improve detection accuracy and reduce alert fatigue.
Alexander Eric