Hi Kostas, Yes, I want them as metrics, as they are purely for monitoring purpose. There's no need of fault tolerance.
If I use side-output, for example for that metric no.1, I would need a tumbling AllWindowFunction, which, as I understand, would introduce some delay to both the normal processing flow, and to the checkpoint process. I already tried to follow the referencing web page that you sent. However, I could not know how to have what I want. For example, with metrics no.1 - meter: org.apache.flink.metrics.Meter only provides markEvent(), which marks an event to that Meter. There is no option to provide the event_time, and processing_time is always used. So my graph is spread over time like the one below. <http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/file/t1586/Meter2.png> For metrics no.2 - histogram: What I can see at Prometheus is the calculated percentile values (0.5, 0.75, 0.9, 0.99, 0.999), which tells me, for example: 99% the total number of records had ts1-ts2 <= 350s (which looks more like a rolling average). But it doesn't tell me roughly how many % of record have diff of 250ms, how many of 260ms, etc... <http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/file/t1586/Histo2.png> Thanks and regards, Averell -- Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/
