The page goes off at 3:14am. You are not the person who wrote the code that broke, because on-call rarely works out that way. You have a terse alert, a service name, and a metric that crossed a line. What you do not have is the one thing you need: why.
Where the minutes go
If you time a typical incident, the fix is often the short part. The long part is everything before it. You open the logs, then the traces, then the deploy feed, then the runbook, then last month's incident, then the alert again. Six tabs before the first real clue. Each one holds a sliver of the picture, and none of them holds the whole thing.
That is the work Ketl set out to remove. Not the judgment, and not the fix, but the reading and the correlating that stand between the page and the first real hypothesis.
The cost is not only time
- The engineer paged is least able to reason, because it is the middle of the night and the context is not theirs.
- The signal is scattered across tools that were never designed to be read together.
- The clock is the customer's, and every minute of digging is a minute of the outage.
The fix is rarely the hard part. Finding out what to fix is.
A first read, in seconds
When an alert fires, Ketl reads the same six places you would, at once, and comes back with a ranked cause, the exact lines behind it, and a proposed fix or rollback. It is not an oracle. It is a fast, senior first opinion that you can check against the evidence and trust or overrule in seconds.
That changes the shape of the night. Instead of forty minutes of digging and four minutes of fixing, you start at the hypothesis, with the evidence already in front of you. The page still wakes you. It just does not keep you.