That's harder problem than I originally realized. It's easy to write noisy alerts, super easy to not have them (or not catching some issues). It's hard to tune them so signal to noise ratio will be high.
Yep. Extracting meaningfull information out of logs automatically is probably an AI-complete problem... Correct me if I wrong, but AFAIK the current state of the art solution to the alerts/log-filtering problem is: "log everything & feed these logs into a real time search engine that produces dashboard/alerts". Like elasticsearch/kibana . No? Curious, is that the approach that is being used internally at Google right…
Generally speaking, it works out pretty well for us. If you're a Splunk query guru you can also correlate and/or combine multiple disparate logs in elaborate ways to create more complex alert conditions.
The same can presumably be done with Elasticsearch/Logstash/Kibana.
We're actually security incident response, not reliability incident response, so our goals and methods differ a bit but the core concepts are all the same.