My Informatica jobs from taskflow are getting queued even when no other jobs are running. I restarted secure agent and it worked fine for few days. But the problem persists again. Can anyone help?
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i will be using helm charts to deploy my application in GCP.i want to make my springboot shutdown after completing its process and then on next day start on its own at a particular time -complete the process and shut down .Is this possible in GCP?
You can use Cloud Run Jobs or Batches to complete that and by paying ONLY when you process consume ressources. (Not the case with Kubernetes and GKE where you pay for your cluster (and your node pools) even if nothing runs on it)
I have an ECS Fargate app up and running on AWS, and I was deploying a newer version of my code through CodeDeploy blue-green deployment. I have been using this method for quite some time, and I have never encountered any problems before unless there was actually a problem with the app itself. As always, I initiated the deployment and waited until all the tasks were running, and checked that the traffic has been rerouted to the newer version of task sets. I tested the app on a couple of devices and made sure that it was working correctly. However, after around 20 minutes or so, my service was down for a few minutes and I get an error message like this on CodeDeploy : CodeDeploy detected that the replacement task set is unhealthy. I expected codedeploy to automatically roll-back the deployment, but it was still the newer version of task set that was receiving traffic, and it was working fine! I did see a couple of stopped tasks but I do not have access to their logs anymore since stopped tasks somehow evaporate and are not accessible after some time. I re-ran the deployment with the exact same task definition, and that worked fine too. Does anyone have any idea what might cause a task set to be in an unhealthy state? Thanks so much!
below is the image of the error
deployment status
I am running a complex flow in apache airflow and using local executor with postgres db. It is running for tasks and scheduler goes down after some time. In airlfow console cant see any logs
using airflow - puckel/docker-airflow:1.10.9 deployed in openshift environment
Error in airflow UI:
The scheduler does not appear to be running. Last heartbeat was received 3 hours ago.
The DAGs list may not update, and new tasks will not be scheduled.
We are using Celery for asynchronous tasks that keep a connection open to a remote server. These Celery jobs can run for up to 10 minutes.
When we deploy a new version of our code, AWS ECS won't wait for these jobs to be ready, so it kills the instances with the Celery workers before they are ready.
One solution is to tell Celery to retry it if it failed, but that could potentially cause other problems.
Is there a way to avoid this? Can we instruct AWS ECS to wait for completion of outgoing connections? Any other way to approach this?
I have a number of google cloud dataflows marked as "Running" in the Dataflow console, but there are no GCE instances running. I manually terminated the instances to avoid being billed. The dataflows seem to be permanently stuck in "running" state. If I try to cancel them from the console or gcloud utility, I receive a warning that the flow is already in "finishing state" so the request was ignored.
I am now at the running quota of 10, so I am stuck. Is there any solution to this other than creating a new project?
There was an issue in the Dataflow service that caused cancel requests to become stuck. It has since been resolved.