Ask HN: How do you handle logging?
1) Log to local disk (most people will tell you this is bad practice and that you should directly log to socket or whatever, but it's more likely for your network to be down than for your disk to fail).<p>In Python, use the RotatingFileHandler to avoid running out of space.<p>2) Incrementally forward your log files to a server using something like fluentd that can pre-aggregate and/or filter  messages.<p>Big advantage of logging to disk: if logging server is unreachable, forwarder can resume once it's up again. If you log directly over network, if things fail the very log messages you need to troubleshoot the failure are potentially gone.<p>3) Visualize. Create alerts.<p>I've evaluated a bunch of logging solutions. Splunk is the best, and affordable at low data volumes (they have a pricing calculator, you can check for yourself). It's medium hard to setup.<p>Sumo Logic is the easiest to set up, and at low data volumes, prices are similar to Splunk. You can get something working within an hour or less.<p>ELK stack is free only in bits but not in engineering time.<p>I've not actually tried Sentry.io but I saw it at PyCon and it looks pretty impressive. If you only care about tracking errors/events and not about general-purpose logging functionality per se, I would take a serious look at it.