I am on a project where I have to debug stuff in logs like Android's logcat: https://pastebin.com/cjh67DZm Problem with this is that files can be huge,... up to 200MB. Sometimes I don't get the correct timestamp of issue. Sometimes I don't get a timestamp at-all. So I can have 24hours sometimes even 48hours of logs in one file and I have to look for something... Now I was thinking of some
sort of AI debugging stuff. Like writing a story of what was happening with device without looking at logs. For example user opened app at 20:20 and then used that app for 10 minutes. Then user closed app and something bad happened: system would detect errors based on tag. In android this is presented with E. and or/just information text <- would have to train it. What shards do you suggest
So I could apply some filters based on timestamp, logLevel tag line and message
<moe:busyloop.net> hmm. can you influence how/what the apps log? ⏎ ⏎ this should be a lot easier if they include a session-id/client-id with each line.
<moe:busyloop.net> i don't know of any NLS/AI shards for crystal, but feel like this is something that should rather be addressed with structured logging anyway
What do you mean client-id? In logs there is thread id and pid id. So I know "lifetime" of specific id
logcat includes logs of "everyting" from sytsem apps to user apps....
<moe:busyloop.net> hmm ah. so if you can already differentiate apps from one another, isn't it just a matter of parsing? ("used app-id X from A until B", "exception E happened while apps A, B, C where open")
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<naqvis> frojnd write a parser to parse logcat logs and then use one of my shard like CrysDA (https://github.com/naqvis/CrysDA) for quick data analysis.
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@moe:busyloop.net yeah parser and maybe what @naqvis suggest for quick data analysis
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