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Provide APIs to monitor pipeline #2611
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This is certainly something I would like to improve, I was bite to debug an issue on a cluster and the tools aren't that great. I am pretty sure @abonuccelli-es would give us some awesome input :) |
@suyograo @ph sorry a bit late here
any other info at runtime via API of course great to have |
I would definetely prefer to have logstash have the same kind of API that mysql, varnish and many more have.. where you connect to a management port - and get numbers out. An ability to have logstash simply just send performance counters to api's such as graphite etc. - would also be super cool. |
To expose those numbers via JMX would be perfect! |
+1 on improving this capabilities of logstash. Monitoring it's things to be improved a lot nowadays. Using jmx might be a nice option that will enable other java components get data out of LS naturally. |
+1 ;) |
We need better introspection into what a filter worker is actually doing, we should be able to output which plugin and which configuration is actually running. see #3294 for a usecase that metrics and stats should help to solve. |
Another cool feature would be able to turn on a flag and be able to know which event is currently in transit in a specific plugin, this will help people to debug problems with blocking plugins. |
JVM metrics would be nice |
Implementation details are in #3908 |
+1 |
Fixed in 5.0 |
Today, most Logstash monitoring functions are accomplished by tailing logs or outputting debug messages. Users typically send specially tagged tracer events to check the health of the system. These special events are also used to measure the latency of the pipeline. This is definitely not straightforward and it becomes hard to administer a large-scale Logstash cluster.
We plan to introduce a Logstash monitoring API endpoint, which will provide visibility into the pipeline. Some important metrics are:
Medium term, we should provide plugin level granularity. For example, it would be great to know how long (on average) an event spends on grok filters, geo ip filters etc. This would help users drill in to the expensive parts of the pipeline.
Care should be taken to make sure metrics collection do not add additional stress on the pipeline and affect the latency and throughput of the events.
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