James Hutchison created BEAM-7975:
-------------------------------------

             Summary: error syncing pod - failed to start container artifact 
(python SDK)
                 Key: BEAM-7975
                 URL: https://issues.apache.org/jira/browse/BEAM-7975
             Project: Beam
          Issue Type: Bug
          Components: sdk-py-harness
    Affects Versions: 2.13.0
            Reporter: James Hutchison


{code:java}
Error syncing pod 5966....e59c ("<container 
name>-08131110-7hcg-harness-fbm2_default(5966....e59c)"), skipping: failed to 
"StartContainer" for "artifact" with CrashLoopBackOff: "Back-off 5m0s 
restarting failed container=artifact pod=<container 
name>-08131110-7hcg-harness-fbm2_default(5966.....e59c)"{code}
Seeing these in streaming pipeline. Running pipeline in batch mode I'm not 
seeing anything. Messages appear about every 0.5 - 5 seconds

I've been trying to efficiently scale my streaming pipeline and found that 
adding more workers / dividing into more groups seems to have minimal 
improvement. Perhaps this is part of the problem?

One pipeline which never completed (got to one of the last steps and then log 
messages simply ceased without error on the workers) had this going on in the 
kubelet logs. I checked some of my other streaming pipelines and found the same 
thing going on, even though they would complete.

In a couple of my streaming pipelines, I've gotten the following error message, 
despite the pipeline eventually finishing:
{code:java}
Processing stuck in step s01 for at least 05m00s without outputting or 
completing in state process{code}
Perhaps they are related?

This is running with 7 workers in streaming mode. I haven't checked to see if 
number of workers is a factor.

The pipeline uses requirements.txt and setup.py, as well as using an extra 
package and using save_main_session.



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