AI handles incidents, engineers lose touch with their systems
Ranked #1 on Hacker News with 135 points and 110 comments.
When I was an SRE at LinkedIn, back in 2012, I designed a system that could heal itself and learn from previous incidents. AI capabilities were nowhere near what we have today, and that remained a prototype, but this is now a reality.
These tools do it all: inspect alerts, form hypotheses, query telemetry, correlate recent deployments, and even implement the fix themselves. As much as I love to see it, I have a major concern: we are losing touch with our systems.
The better these tools become at resolving routine incidents, the less practice human responders will get. And when an ambiguous, high-severity incident comes in that automation cannot solve, responding engineers will be in trouble.
Automation leaves humans with the hardest incidents #
These AI-assisted incident response tools, more commonly called “AI SREs” – a term I don’t particularly like – are fantastic in many ways. They feel especially magical when they handle a routine incident at night and you don’t have to wake up for a capacity issue.
The problem is that routine incidents are also how responders “safely” develop an intuition for how their systems behave and fail. When AI runs into a hard, never-seen-before incident it cannot solve, engineers will have to take over with less practice than they would have had before.