I see, for example, docs on how to log from Python: https://www.datadoghq.com/blog/python-logging-best-practices...
> but they seem clear that there's both a logging and metrics (apm) side to their product.
yes they have those two sides. what they do not have is an error tracking side; something like sentry[1]. errorship exists to bring the error tracking side into datadog.
The logging side of datadog is like splunk or elasticsearch, and their APM side is like newrelic. errorship is bringing the error tracking side.
some of the analogies may not apply 100%, but I hope I'm making sense.
But also, errorship will still capture(and send to datadog) any exceptions that you may have forgot to capture or log.
> although not sure how DD would feel about that
The datadog documentation[1] says; "An event represents any record of activity noteworthy for engineers"[1]. We certainly believe that exceptions that occur in engineer's applications are noteworthy activities and as such belong to the eventstream.
Yep, noted that, and I like how you preserve syntax highlighting in the stack traces :)
Out of curiosity, I've only ever dabbled in Datadog, is there any limit on event stream size or retention? I couldn't find anything mentioned in the docs.
Seems like a big loophole.