Hi

I'm trying to understand what it means to run a Flink cluster inside the Google 
Cloud Platform and whether it can act in an "elastic" way; if the cluster needs 
more resources to accommodate a sudden demand or increase in Flink jobs, will 
GCP automatically detect this and spool up more Task Managers to provide extra 
task slots?

If we consider the following two simple use cases, how would GCP address them?


1)     No free task slots to run new flink jobs

2)     A slow flink job needs an increased parallelism to improve throughput

Currently, we'd handle the above use cases by:


1)     knowing that the job failed due to "no free slots", check the exception 
text, schedule to add a new task manager and rerun the job, knowing that there 
are now available task slots.

2)     We'd monitor the speed of the job ourselves, stop the job, specify which 
components (operators) in the stream reqd an increase in parallelism (for 
example via job properties), then relaunch the job; if not enough slots were 
available, we'd have to consider adding extra task managers.


So my question is...can Google Cloud Platform (GCP) automatically launch extra 
TMs to handle the above?

If we proposed to run a Flink cluster in a GCP container, can GCP make Flink 
behave dynamically elastic in the same way that Google DataFlow apparently can?

Regards


Alex


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