I think the only limitation is the disk size of your kubelet machine. Please remember to set the "sizeLimit" of your empty dir. Otherwise, your pod may be killed due to ephemeral storage is full.
Best, Yang M Singh <mans2si...@yahoo.com> 于2020年2月27日周四 上午8:34写道： > BTW - Is there any limit to the amount of data that can be stored on > emptyDir in K8 ? > > On Wednesday, February 26, 2020, 07:33:54 PM EST, M Singh < > mans2si...@yahoo.com> wrote: > > > Thanks Yang and Arvid for your advice and pointers. Mans > > On Wednesday, February 26, 2020, 09:52:26 AM EST, Arvid Heise < > ar...@ververica.com> wrote: > > > Creds on AWS are typically resolved through roles assigned to K8s pods > (for example with KIAM [1]). > > [1] https://github.com/uswitch/kiam > > On Tue, Feb 25, 2020 at 3:36 AM Yang Wang <danrtsey...@gmail.com> wrote: > > Hi M Singh, > > > Mans - If we use the session based deployment option for K8 - I thought > K8 will automatically restarts any failed TM or JM. > In the case of failed TM - the job will probably recover, but in the case > of failed JM - perhaps we need to resubmit all jobs. > Let me know if I have misunderstood anything. > > > Since you are starting JM/TM with K8s deployment, when they failed new > JM/TM will be created. If you do not set the high > availability configuration, your jobs could recover when TM failed. > However, they could not recover when JM failed. With HA > configured, the jobs could always be recovered and you do not need to > re-submit again. > > > Mans - Is there any safe way of a passing creds ? > > > Yes, you are right, Using configmap to pass the credentials is not safe. > On K8s, i think you could use secrets instead[1]. > > > Mans - Does a task manager failure cause the job to fail ? My > understanding is the JM failure are catastrophic while TM failures are > recoverable. > > > What i mean is the job failed, and it could be restarted by your > configured restart strategy[2]. > > > Mans - So if we are saving checkpoint in S3 then there is no need for > disks - should we use emptyDir ? > > > Yes, if you are saving the checkpoint in S3 and also set the > `high-availability.storageDir` to S3. Then you do not need persistent > volume. Since > the local directory is only used for local cache, so you could directly > use the overlay filesystem or empryDir(better io performance). > > > [1]. > https://kubernetes.io/docs/tasks/inject-data-application/distribute-credentials-secure/ > [2]. > https://ci.apache.org/projects/flink/flink-docs-master/ops/config.html#fault-tolerance > > M Singh <mans2si...@yahoo.com> 于2020年2月25日周二 上午5:53写道： > > Thanks Wang for your detailed answers. > > From what I understand the native_kubernetes also leans towards creating a > session and submitting a job to it. > > Regarding other recommendations, please my inline comments and advice. > > On Sunday, February 23, 2020, 10:01:10 PM EST, Yang Wang < > danrtsey...@gmail.com> wrote: > > > Hi Singh, > > Glad to hear that you are looking to run Flink on the Kubernetes. I am > trying to answer your question based on my limited knowledge and > others could correct me and add some more supplements. > > I think the biggest difference between session cluster and per-job cluster > on Kubernetesis the isolation. Since for per-job, a dedicated Flink cluster > will be started for the only one job and no any other jobs could be > submitted. > Once the job is finished, then the Flink cluster will be > destroyed immediately. > The second point is one-step submission. You do not need to start a Flink > cluster first and then submit a job to the existing session. > > > Are there any benefits with regards to > 1. Configuring the jobs > No matter you are using the per-job cluster or submitting to the existing > session cluster, they share the configuration mechanism. You do not have > to change any codes and configurations. > > 2. Scaling the taskmanager > Since you are using the Standalone cluster on Kubernetes, it do not provide > an active resourcemanager. You need to use external tools to monitor and > scale up the taskmanagers. The active integration is still evolving and you > could have a taste[1]. > > Mans - If we use the session based deployment option for K8 - I thought K8 > will automatically restarts any failed TM or JM. > In the case of failed TM - the job will probably recover, but in the case > of failed JM - perhaps we need to resubmit all jobs. > Let me know if I have misunderstood anything. > > 3. Restarting jobs > For the session cluster, you could directly cancel the job and re-submit. > And > for per-job cluster, when the job is canceled, you need to start a new > per-job > cluster from the latest savepoint. > > 4. Managing the flink jobs > The rest api and flink command line could be used to managing the jobs(e.g. > flink cancel, etc.). I think there is no difference for session and > per-job here. > > 5. Passing credentials (in case of AWS, etc) > I am not sure how do you provide your credentials. If you put them in the > config map and then mount into the jobmanager/taskmanager pod, then both > session and per-job could support this way. > > Mans - Is there any safe way of a passing creds ? > > 6. Fault tolerence and recovery of jobs from failure > For session cluster, if one taskmanager crashed, then all the jobs which > have tasks > on this taskmanager will failed. > Both session and per-job could be configured with high availability and > recover > from the latest checkpoint. > > Mans - Does a task manager failure cause the job to fail ? My > understanding is the JM failure are catastrophic while TM failures are > recoverable. > > > Is there any need for specifying volume for the pods? > No, you do not need to specify a volume for pod. All the data in the pod > local directory is temporary. When a pod crashed and relaunched, the > taskmanager will retrieve the checkpoint from zookeeper + S3 and resume > from the latest checkpoint. > > Mans - So if we are saving checkpoint in S3 then there is no need for > disks - should we use emptyDir ? > > > [1]. > https://ci.apache.org/projects/flink/flink-docs-master/ops/deployment/native_kubernetes.html > > M Singh <mans2si...@yahoo.com> 于2020年2月23日周日 上午2:28写道： > > Hey Folks: > > I am trying to figure out the options for running Flink on Kubernetes and > am trying to find out the pros and cons of running in Flink Session vs > Flink Cluster mode ( > https://ci.apache.org/projects/flink/flink-docs-stable/ops/deployment/kubernetes.html#flink-session-cluster-on-kubernetes > ). > > I understand that in job mode there is no need to submit the job since it > is part of the job image. But what are other the pros and cons of this > approach vs session mode where a job manager is deployed and flink jobs can > be submitted it ? Are there any benefits with regards to: > > 1. Configuring the jobs > 2. Scaling the taskmanager > 3. Restarting jobs > 4. Managing the flink jobs > 5. Passing credentials (in case of AWS, etc) > 6. Fault tolerence and recovery of jobs from failure > > Also, we will be keeping the checkpoints for the jobs on S3. Is there any > need for specifying volume for the pods ? If volume is required do we need > provisioned volume and what are the recommended alternatives/considerations > especially with AWS. > > If there are any other considerations, please let me know. > > Thanks for your advice. > > > > >
