A typical solution to your issue is to use an ELK stack to collect the logs
and define some filters on log events.

If it's specific to input data issues, I also found side-outputs useful to
store invalid data points. Then, you can simply monitor the side topic
(assuming Kafka) and already have the data points at hand to improve your
software/investigate the root cause.

On Mon, Dec 28, 2020 at 12:14 PM Chesnay Schepler <ches...@apache.org>
wrote:

> There is no way to have an exception appear in the REST API without
> restarting the job; that field is exactly defined as the exception causing
> the job to fail.
>
> Using asynchronous by itself is fine, so long as you don't wait for any
> confirmation. In any case you could remedy the issue by writing the alerts
> into a side-output and having a dedicated sink for submitting these alerts.
>
> On 12/28/2020 5:24 AM, Chirag Dewan wrote:
>
> Hi,
>
> I am building an alerting system where based on some input events I need
> to raise an alert from the user defined aggregate function.
>
> My first approach was to use an asynchronous REST API to send alerts
> outside the task slot. But this obviously involves IO from within the task
> and if I understand correctly, should be avoided.
>
> Another way is to use the Job Manager's *exceptions *REST API to pull the
> alerts from the Flink cluster. This however requires me to throw an
> exception from the operator which results in a job failure/restart.
>
> Is there any way I can throw exceptions that appear in the REST API but
> don't restart the job? This might be similar to how some of the internal
> exceptions like checkpointing related appear in the REST output.
>
> I plan on exploring the Queryable state for such use cases as well, but
> the evolving state might be a blocker.
>
> Thanks
> Chirag
>
>
>

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