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How did you deploy Kubeflow Pipelines (KFP)?
manifests
KFP version:
2.3.0
KFP SDK version:
2.11.0
Steps to reproduce
I write a simple python code as below:
@dsl.component()
def sleep_task(metrics: Output[Metrics]):
import time
time.sleep(1200)
metrics.log_metric("total", 1)
Environment
manifests
2.3.0
2.11.0
Steps to reproduce
I write a simple python code as below:
@dsl.component()
def sleep_task(metrics: Output[Metrics]):
import time
time.sleep(1200)
metrics.log_metric("total", 1)
@dsl.pipeline(name='A2')
def my_pipeline():
sleep_op = sleep_task()
The kfp always output : F0221 07:45:04.241460 18 main.go:49] failed to execute component: unable to produce MLMD artifact for output "metrics": rpc error: code = Unavailable desc = error reading from server: read tcp 10.197.0.233:37640->10.198.43.0:8080: read: connection reset by peer
time="2025-02-21T07:45:04.328Z" level=info msg="sub-process exited" argo=true error=""
Error: exit status 1
Are there any parameters related to idletimeout that I need to set ???
Expected result
exit with code 0
Materials and Reference
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