For native K8s integration, the Flink ResourceManager will delete the
JobManager K8s deployment as well as the HA data once the job reached a
globally terminal state.
However, it is indeed a problem for standalone mode since the JobManager
will be restarted again even the job has finished. I think
Hey Gil,
I'm referring to when a pod exits on its own, not when being deleted.
Deployments only support the "Always" restart policy [1].
In my understanding, the JM only cleans up HA data when it is shutdown[2],
after which the process will exit which leads to the problem with k8s
Deployment rest
Hello Austin,
I'm not aware of any limitations of deployement not letting pod exit
(correctly or incorrectly). What do you mean by that exactly? Would it be
possible for you to point out to piece of documentation that make you think
that ?
A pod, if correctly setup will be exited when receiving i
Cool, thanks! How does it clean up the HA data, if the cluster is never
able to shut down (due to the k8s Deployment restriction)?
Best,
Austin
On Mon, Sep 5, 2022 at 6:51 PM Gyula Fóra wrote:
> Hi!
>
> The operator supports both Flink native and standalone deployment modes
> and in both cases
Hi!
The operator supports both Flink native and standalone deployment modes and
in both cases the JM is deployed as k8s Deployment.
During upgrade Flink/operator deletes the deployment after savepoint and
waits for termination before it creates a new one with the updated spec.
Cheers,
Gyula
On
Hey Marco,
Unfortunately there is no built in k8s API that models an application mode
JM exactly but Deployments should be fine, in general. As Gyula notes,
where they can be difficult is during application upgrades as Deployments
never let their pods exit, even if successful, so there is no way t
You can use deployments of course , the operator and native k8s integration
does exactly that.
Even then job updates can be tricky so I believe you are much better off
with the operator.
Gyula
On Sun, 4 Sep 2022 at 11:11, marco andreas
wrote:
> Hello,
>
> Thanks for the response, I will take a
Hello,
Thanks for the response, I will take a look at it.
But if we aren't able to use the flink operator due to technical
constraints is it possible to deploy the JM as deployment without any
consequences that I am not aware of?
Sincerely,
Le sam. 3 sept. 2022 à 23:27, Gyula Fóra a écrit :
>
Hi!
You should check out the Flink Kubernetes Operator. I think that covers all
your needs .
https://nightlies.apache.org/flink/flink-kubernetes-operator-docs-main/
Cheers,
Gyula
On Sat, 3 Sep 2022 at 13:45, marco andreas
wrote:
>
> We are deploying a flink application cluster on k8S. Followin
We are deploying a flink application cluster on k8S. Following the official
documentation the JM is deployed As a job resource , however we are
deploying a long running flink job that is not supposed to be terminated
and also we need to update the image of the flink job.
The problem is that the j
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