Hi Vishal, REST API is the most direct way to get through all metrics as Matthias pointed out. Additionally, you could also add a JMX reporter and log to the machines to check.
But in general, I think you are on the right track. You need to reduce the metrics that are sent to DD by configuring the scope / excluding variables. Furthermore, I think it would be a good idea to make the timeout configurable. Could you open a ticket for that? Best, Arvid On Wed, Mar 24, 2021 at 9:02 AM Matthias Pohl <matth...@ververica.com> wrote: > Hi Vishal, > what about the TM metrics' REST endpoint [1]. Is this something you could > use to get all the metrics for a specific TaskManager? Or are you looking > for something else? > > Best, > Matthias > > [1] > https://ci.apache.org/projects/flink/flink-docs-release-1.12/ops/rest_api.html#taskmanagers-metrics > > On Tue, Mar 23, 2021 at 10:59 PM Vishal Santoshi < > vishal.santo...@gmail.com> wrote: > >> That said, is there a way to get a dump of all metrics exposed by TM. I >> was searching for it and I bet we could get it for ServieMonitor on k8s ( >> scrape ) but am missing a way to het a TM and dump all metrics that are >> pushed. >> >> Thanks and regards. >> >> On Tue, Mar 23, 2021 at 5:56 PM Vishal Santoshi < >> vishal.santo...@gmail.com> wrote: >> >>> I guess there is a bigger issue here. We dropped the property to 500. We >>> also realized that this failure happened on a TM that had one specific job >>> running on it. What was good ( but surprising ) that the exception was the >>> more protocol specific 413 ( as in the chunk is greater then some size >>> limit DD has on a request. >>> >>> Failed to send request to Datadog (response was Response{protocol=h2, >>> code=413, message=, url= >>> https://app.datadoghq.com/api/v1/series?api_key=**********} >>> <https://app.datadoghq.com/api/v1/series?api_key=0ffa36e48f5042465635b5843fa3f2a6%7D> >>> ) >>> >>> which implies that the Socket timeout was masking this issue. The 2000 >>> was just a huge payload that DD was unable to parse in time ( or was slow >>> to upload etc ). Now we could go lower but that makes less sense. We could >>> play with >>> https://ci.apache.org/projects/flink/flink-docs-stable/ops/metrics.html#system-scope >>> to reduce the size of the tags ( or keys ). >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> On Tue, Mar 23, 2021 at 11:33 AM Vishal Santoshi < >>> vishal.santo...@gmail.com> wrote: >>> >>>> If we look at this >>>> <https://github.com/apache/flink/blob/97bfd049951f8d52a2e0aed14265074c4255ead0/flink-metrics/flink-metrics-datadog/src/main/java/org/apache/flink/metrics/datadog/DatadogHttpReporter.java#L159> >>>> code , the metrics are divided into chunks up-to a max size. and >>>> enqueued >>>> <https://github.com/apache/flink/blob/97bfd049951f8d52a2e0aed14265074c4255ead0/flink-metrics/flink-metrics-datadog/src/main/java/org/apache/flink/metrics/datadog/DatadogHttpClient.java#L110>. >>>> The Request >>>> <https://github.com/apache/flink/blob/97bfd049951f8d52a2e0aed14265074c4255ead0/flink-metrics/flink-metrics-datadog/src/main/java/org/apache/flink/metrics/datadog/DatadogHttpClient.java#L75> >>>> has a 3 second read/connect/write timeout which IMHO should have been >>>> configurable ( or is it ) . While the number metrics ( all metrics ) >>>> exposed by flink cluster is pretty high ( and the names of the metrics >>>> along with tags ) , it may make sense to limit the number of metrics in a >>>> single chunk ( to ultimately limit the size of a single chunk ). There is >>>> this configuration which allows for reducing the metrics in a single chunk >>>> >>>> metrics.reporter.dghttp.maxMetricsPerRequest: 2000 >>>> >>>> We could decrease this to 1500 ( 1500 is pretty, not based on any >>>> empirical reasoning ) and see if that stabilizes the dispatch. It is >>>> inevitable that the number of requests will grow and we may hit the >>>> throttle but then we know the exception rather than the timeouts that are >>>> generally less intuitive. >>>> >>>> Any thoughts? >>>> >>>> >>>> >>>> On Mon, Mar 22, 2021 at 10:37 AM Arvid Heise <ar...@apache.org> wrote: >>>> >>>>> Hi Vishal, >>>>> >>>>> I have no experience in the Flink+DataDog setup but worked a bit with >>>>> DataDog before. >>>>> I'd agree that the timeout does not seem like a rate limit. It would >>>>> also be odd that the other TMs with a similar rate still pass. So I'd >>>>> suspect n/w issues. >>>>> Can you log into the TM's machine and try out manually how the system >>>>> behaves? >>>>> >>>>> On Sat, Mar 20, 2021 at 1:44 PM Vishal Santoshi < >>>>> vishal.santo...@gmail.com> wrote: >>>>> >>>>>> Hello folks, >>>>>> This is quite strange. We see a TM stop reporting >>>>>> metrics to DataDog .The logs from that specific TM for every >>>>>> DataDog dispatch time out with* java.net.SocketTimeoutException: >>>>>> timeout *and that seems to repeat over every dispatch to DataDog. It >>>>>> seems it is on a 10 seconds cadence per container. The TM remains >>>>>> humming, >>>>>> so does not seem to be under memory/CPU distress. And the exception is >>>>>> *not* transient. It just stops dead and from there on timeout. >>>>>> >>>>>> Looking at SLA provided by DataDog any throttling exception should >>>>>> pretty much not be a SocketTimeOut, till of course the reporting the >>>>>> specific issue is off. This thus appears very much a n/w issue which >>>>>> appears weird as other TMs with the same n/w just hum along, sending >>>>>> their >>>>>> metrics successfully. The other issue could be just the amount of metrics >>>>>> and the current volume for the TM is prohibitive. That said the exception >>>>>> is still not helpful. >>>>>> >>>>>> Any ideas from folks who have used DataDog reporter with Flink. I >>>>>> guess even best practices may be a sufficient beginning. >>>>>> >>>>>> Regards. >>>>>> >>>>>>
