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Published
20 hours ago •
Netflix
Netflix
Underscore in template name of argo-workflows not allowed
Argo-Workflows UI rejects Metaflow generated Workflows if step name contains "_" Although _sanitize method exists in _dag_templates, a step name with underscore is not sanitized. Example:
class HelloArgoFlow(FlowSpec):
@step
def start(self):
print("HelloFlow is starting.")
self.next(self.hello_a)
@step
def hello_a(self):
print("HelloFlow says HELLO.")
self.next(self.end)
@step
def end(self):
print("HelloFlow is all done.")\
if __name__ == '__main__':
HelloArgoFlow()
I was unable to reproduce the error using Metaflow 2.6.0
Click to expand!
{
"apiVersion": "argoproj.io/v1alpha1",
"kind": "WorkflowTemplate",
"metadata": {
"name": "helloargoflow",
"namespace": "default",
"labels": {
"app.kubernetes.io/name": "metaflow-flow",
"app.kubernetes.io/part-of": "metaflow"
},
"annotations": {
"metaflow/production_token": "helloargoflow-0-symt",
"metaflow/owner": "savin",
"metaflow/user": "argo-workflows",
"metaflow/flow_name": "HelloArgoFlow"
}
},
"spec": {
"parallelism": 100,
"workflowMetadata": {
"labels": {
"app.kubernetes.io/name": "metaflow-run",
"app.kubernetes.io/part-of": "metaflow"
},
"annotations": {
"metaflow/production_token": "helloargoflow-0-symt",
"metaflow/owner": "savin",
"metaflow/user": "argo-workflows",
"metaflow/flow_name": "HelloArgoFlow",
"metaflow/run_id": "argo-{{workflow.name}}"
}
},
"arguments": {
"parameters": []
},
"podMetadata": {
"labels": {
"app.kubernetes.io/name": "metaflow-task",
"app.kubernetes.io/part-of": "metaflow"
},
"annotations": {
"metaflow/production_token": "helloargoflow-0-symt",
"metaflow/owner": "savin",
"metaflow/user": "argo-workflows",
"metaflow/flow_name": "HelloArgoFlow"
}
},
"entrypoint": "HelloArgoFlow",
"templates": [
{
"name": "HelloArgoFlow",
"dag": {
"failFast": true,
"tasks": [
{
"name": "start",
"template": "start"
},
{
"name": "hello-a",
"dependencies": [
"start"
],
"template": "hello_a",
"arguments": {
"parameters": [
{
"name": "input-paths",
"value": "argo-{{workflow.name}}/start/{{tasks.start.outputs.parameters.task-id}}"
}
]
}
},
{
"name": "end",
"dependencies": [
"hello-a"
],
"template": "end",
"arguments": {
"parameters": [
{
"name": "input-paths",
"value": "argo-{{workflow.name}}/hello_a/{{tasks.hello-a.outputs.parameters.task-id}}"
}
]
}
}
]
}
},
{
"name": "start",
"activeDeadlineSeconds": 432000,
"serviceAccountName": "s3-full-access",
"inputs": {
"parameters": []
},
"outputs": {
"parameters": [
{
"name": "task-id",
"valueFrom": {
"path": "/mnt/out/task_id"
}
}
]
},
"failFast": true,
"metadata": {
"annotations": {
"metaflow/step_name": "start",
"metaflow/attempt": "0"
}
},
"volumes": [
{
"name": "out",
"emptyDir": {}
}
],
"labels": {},
"nodeSelector": {},
"container": {
"args": null,
"command": [
"bash",
"-c",
"mkdir -p $PWD/.logs && export METAFLOW_TASK_ID=(t-$(echo start-{{workflow.creationTimestamp}} | md5sum | cut -d ' ' -f 1 | tail -c 9)) && export PYTHONUNBUFFERED=x MF_PATHSPEC=HelloArgoFlow/argo-{{workflow.name}}/start/$METAFLOW_TASK_ID MF_DATASTORE=s3 MF_ATTEMPT=0 MFLOG_STDOUT=$PWD/.logs/mflog_stdout MFLOG_STDERR=$PWD/.logs/mflog_stderr && mflog(){ T=$(date -u -Ins|tr , .); echo \"[MFLOG|0|${T:0:26}Z|task|$T]$1\" >> $MFLOG_STDOUT; echo $1; } && mflog 'Setting up task environment.' && python -m pip install awscli requests boto3 -qqq && mkdir metaflow && cd metaflow && mkdir .metaflow && i=0; while [ $i -le 5 ]; do mflog 'Downloading code package...'; python -m awscli s3 cp s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158 job.tar >/dev/null && mflog 'Code package downloaded.' && break; sleep 10; i=$((i+1)); done && if [ $i -gt 5 ]; then mflog 'Failed to download code package from s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158 after 6 tries. Exiting...' && exit 1; fi && TAR_OPTIONS='--warning=no-timestamp' tar xf job.tar && mflog 'Task is starting.' && (if ! python hello.py dump --max-value-size=0 argo-{{workflow.name}}/_parameters/$METAFLOW_TASK_ID-params >/dev/null 2>/dev/null; then python hello.py --with kubernetes:cpu=1,memory=4096,disk=10240,image=python:3.9,service_account=s3-full-access,namespace=default,gpu_vendor=nvidia --with 'environment:vars={}' --quiet --metadata=service --environment=local --datastore=s3 --datastore-root=s3://valay-k8s-testing/metaflow --event-logger=nullSidecarLogger --monitor=nullSidecarMonitor --no-pylint --with=argo_workflows_internal init --run-id argo-{{workflow.name}} --task-id $METAFLOW_TASK_ID-params; fi && python hello.py --with kubernetes:cpu=1,memory=4096,disk=10240,image=python:3.9,service_account=s3-full-access,namespace=default,gpu_vendor=nvidia --with 'environment:vars={}' --quiet --metadata=service --environment=local --datastore=s3 --datastore-root=s3://valay-k8s-testing/metaflow --event-logger=nullSidecarLogger --monitor=nullSidecarMonitor --no-pylint --with=argo_workflows_internal step start --run-id argo-{{workflow.name}} --task-id $METAFLOW_TASK_ID --retry-count 0 --max-user-code-retries 0 --input-paths argo-{{workflow.name}}/_parameters/$METAFLOW_TASK_ID-params) 1>> >(python -m metaflow.mflog.tee task $MFLOG_STDOUT) 2>> >(python -m metaflow.mflog.tee task $MFLOG_STDERR >&2); c=$?; python -m metaflow.mflog.save_logs; exit $c"
],
"env": [
{
"name": "METAFLOW_CODE_URL",
"value": "s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158",
"valueFrom": null
},
{
"name": "METAFLOW_CODE_SHA",
"value": "f882d08568f6290d783027b6aa617bb6c336a158",
"valueFrom": null
},
{
"name": "METAFLOW_CODE_DS",
"value": "s3",
"valueFrom": null
},
{
"name": "METAFLOW_SERVICE_URL",
"value": "https://x3kwb6qyc6.execute-api.us-west-2.amazonaws.com/api/",
"valueFrom": null
},
{
"name": "METAFLOW_USER",
"value": "argo-workflows",
"valueFrom": null
},
{
"name": "METAFLOW_DATASTORE_SYSROOT_S3",
"value": "s3://valay-k8s-testing/metaflow",
"valueFrom": null
},
{
"name": "METAFLOW_DATATOOLS_S3ROOT",
"value": "s3://oleg-stepfn-test-metaflows3bucket-1s3wkux8ddr1/data",
"valueFrom": null
},
{
"name": "METAFLOW_DEFAULT_DATASTORE",
"value": "s3",
"valueFrom": null
},
{
"name": "METAFLOW_DEFAULT_METADATA",
"value": "service",
"valueFrom": null
},
{
"name": "METAFLOW_CARD_S3ROOT",
"value": "s3://valay-k8s-testing/metaflow/mf.cards",
"valueFrom": null
},
{
"name": "METAFLOW_KUBERNETES_WORKLOAD",
"value": "1",
"valueFrom": null
},
{
"name": "METAFLOW_RUNTIME_ENVIRONMENT",
"value": "kubernetes",
"valueFrom": null
},
{
"name": "METAFLOW_OWNER",
"value": "savin",
"valueFrom": null
},
{
"name": "METAFLOW_FLOW_NAME",
"value": "HelloArgoFlow",
"valueFrom": null
},
{
"name": "METAFLOW_STEP_NAME",
"value": "start",
"valueFrom": null
},
{
"name": "METAFLOW_RUN_ID",
"value": "argo-{{workflow.name}}",
"valueFrom": null
},
{
"name": "METAFLOW_RETRY_COUNT",
"value": "0",
"valueFrom": null
},
{
"name": "METAFLOW_PRODUCTION_TOKEN",
"value": "helloargoflow-0-symt",
"valueFrom": null
},
{
"name": "ARGO_WORKFLOW_TEMPLATE",
"value": "helloargoflow",
"valueFrom": null
},
{
"name": "ARGO_WORKFLOW_NAME",
"value": "{{workflow.name}}",
"valueFrom": null
},
{
"name": "ARGO_WORKFLOW_NAMESPACE",
"value": "default",
"valueFrom": null
},
{
"name": "METAFLOW_RUNTIME_NAME",
"value": "argo-workflows",
"valueFrom": null
},
{
"name": "USER",
"value": "savin",
"valueFrom": null
},
{
"name": "METAFLOW_VERSION",
"value": "{\"platform\": \"Darwin\", \"username\": \"savin\", \"production_token\": \"helloargoflow-0-symt\", \"runtime\": \"dev\", \"app\": null, \"environment_type\": \"local\", \"use_r\": false, \"python_version\": \"3.9.1 (default, Dec 11 2020, 06:28:49) \\n[Clang 10.0.0 ]\", \"python_version_code\": \"3.9.1\", \"metaflow_version\": \"2.6.0\", \"script\": \"hello.py\", \"ext_info\": [{}, {}], \"flow_name\": \"HelloArgoFlow\"}",
"valueFrom": null
},
{
"name": "METAFLOW_KUBERNETES_POD_NAMESPACE",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "metadata.namespace"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_POD_NAME",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "metadata.name"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_POD_ID",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "metadata.uid"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_SERVICE_ACCOUNT_NAME",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "spec.serviceAccountName"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
}
],
"envFrom": [],
"image": "python:3.9",
"imagePullPolicy": null,
"lifecycle": null,
"livenessProbe": null,
"name": "start",
"ports": null,
"readinessProbe": null,
"resources": {
"limits": {},
"requests": {
"cpu": "1",
"memory": "4096M",
"ephemeral-storage": "10240M"
}
},
"securityContext": null,
"startupProbe": null,
"stdin": null,
"stdinOnce": null,
"terminationMessagePath": null,
"terminationMessagePolicy": null,
"tty": null,
"volumeDevices": null,
"volumeMounts": [
{
"mountPath": "/mnt/out",
"mountPropagation": null,
"name": "out",
"readOnly": null,
"subPath": null,
"subPathExpr": null
}
],
"workingDir": null
}
},
{
"name": "hello_a",
"activeDeadlineSeconds": 432000,
"serviceAccountName": "s3-full-access",
"inputs": {
"parameters": [
{
"name": "input-paths"
}
]
},
"outputs": {
"parameters": [
{
"name": "task-id",
"valueFrom": {
"path": "/mnt/out/task_id"
}
}
]
},
"failFast": true,
"metadata": {
"annotations": {
"metaflow/step_name": "hello_a",
"metaflow/attempt": "0"
}
},
"volumes": [
{
"name": "out",
"emptyDir": {}
}
],
"labels": {},
"nodeSelector": {},
"container": {
"args": null,
"command": [
"bash",
"-c",
"mkdir -p $PWD/.logs && export METAFLOW_TASK_ID=(t-$(echo hello_a-{{workflow.creationTimestamp}}-{{inputs.parameters.input-paths}} | md5sum | cut -d ' ' -f 1 | tail -c 9)) && export PYTHONUNBUFFERED=x MF_PATHSPEC=HelloArgoFlow/argo-{{workflow.name}}/hello_a/$METAFLOW_TASK_ID MF_DATASTORE=s3 MF_ATTEMPT=0 MFLOG_STDOUT=$PWD/.logs/mflog_stdout MFLOG_STDERR=$PWD/.logs/mflog_stderr && mflog(){ T=$(date -u -Ins|tr , .); echo \"[MFLOG|0|${T:0:26}Z|task|$T]$1\" >> $MFLOG_STDOUT; echo $1; } && mflog 'Setting up task environment.' && python -m pip install awscli requests boto3 -qqq && mkdir metaflow && cd metaflow && mkdir .metaflow && i=0; while [ $i -le 5 ]; do mflog 'Downloading code package...'; python -m awscli s3 cp s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158 job.tar >/dev/null && mflog 'Code package downloaded.' && break; sleep 10; i=$((i+1)); done && if [ $i -gt 5 ]; then mflog 'Failed to download code package from s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158 after 6 tries. Exiting...' && exit 1; fi && TAR_OPTIONS='--warning=no-timestamp' tar xf job.tar && mflog 'Task is starting.' && (python hello.py --with kubernetes:cpu=1,memory=4096,disk=10240,image=python:3.9,service_account=s3-full-access,namespace=default,gpu_vendor=nvidia --with 'environment:vars={}' --quiet --metadata=service --environment=local --datastore=s3 --datastore-root=s3://valay-k8s-testing/metaflow --event-logger=nullSidecarLogger --monitor=nullSidecarMonitor --no-pylint --with=argo_workflows_internal step hello_a --run-id argo-{{workflow.name}} --task-id $METAFLOW_TASK_ID --retry-count 0 --max-user-code-retries 0 --input-paths {{inputs.parameters.input-paths}}) 1>> >(python -m metaflow.mflog.tee task $MFLOG_STDOUT) 2>> >(python -m metaflow.mflog.tee task $MFLOG_STDERR >&2); c=$?; python -m metaflow.mflog.save_logs; exit $c"
],
"env": [
{
"name": "METAFLOW_CODE_URL",
"value": "s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158",
"valueFrom": null
},
{
"name": "METAFLOW_CODE_SHA",
"value": "f882d08568f6290d783027b6aa617bb6c336a158",
"valueFrom": null
},
{
"name": "METAFLOW_CODE_DS",
"value": "s3",
"valueFrom": null
},
{
"name": "METAFLOW_SERVICE_URL",
"value": "https://x3kwb6qyc6.execute-api.us-west-2.amazonaws.com/api/",
"valueFrom": null
},
{
"name": "METAFLOW_USER",
"value": "argo-workflows",
"valueFrom": null
},
{
"name": "METAFLOW_DATASTORE_SYSROOT_S3",
"value": "s3://valay-k8s-testing/metaflow",
"valueFrom": null
},
{
"name": "METAFLOW_DATATOOLS_S3ROOT",
"value": "s3://oleg-stepfn-test-metaflows3bucket-1s3wkux8ddr1/data",
"valueFrom": null
},
{
"name": "METAFLOW_DEFAULT_DATASTORE",
"value": "s3",
"valueFrom": null
},
{
"name": "METAFLOW_DEFAULT_METADATA",
"value": "service",
"valueFrom": null
},
{
"name": "METAFLOW_CARD_S3ROOT",
"value": "s3://valay-k8s-testing/metaflow/mf.cards",
"valueFrom": null
},
{
"name": "METAFLOW_KUBERNETES_WORKLOAD",
"value": "1",
"valueFrom": null
},
{
"name": "METAFLOW_RUNTIME_ENVIRONMENT",
"value": "kubernetes",
"valueFrom": null
},
{
"name": "METAFLOW_OWNER",
"value": "savin",
"valueFrom": null
},
{
"name": "METAFLOW_FLOW_NAME",
"value": "HelloArgoFlow",
"valueFrom": null
},
{
"name": "METAFLOW_STEP_NAME",
"value": "hello_a",
"valueFrom": null
},
{
"name": "METAFLOW_RUN_ID",
"value": "argo-{{workflow.name}}",
"valueFrom": null
},
{
"name": "METAFLOW_RETRY_COUNT",
"value": "0",
"valueFrom": null
},
{
"name": "METAFLOW_PRODUCTION_TOKEN",
"value": "helloargoflow-0-symt",
"valueFrom": null
},
{
"name": "ARGO_WORKFLOW_TEMPLATE",
"value": "helloargoflow",
"valueFrom": null
},
{
"name": "ARGO_WORKFLOW_NAME",
"value": "{{workflow.name}}",
"valueFrom": null
},
{
"name": "ARGO_WORKFLOW_NAMESPACE",
"value": "default",
"valueFrom": null
},
{
"name": "METAFLOW_RUNTIME_NAME",
"value": "argo-workflows",
"valueFrom": null
},
{
"name": "USER",
"value": "savin",
"valueFrom": null
},
{
"name": "METAFLOW_VERSION",
"value": "{\"platform\": \"Darwin\", \"username\": \"savin\", \"production_token\": \"helloargoflow-0-symt\", \"runtime\": \"dev\", \"app\": null, \"environment_type\": \"local\", \"use_r\": false, \"python_version\": \"3.9.1 (default, Dec 11 2020, 06:28:49) \\n[Clang 10.0.0 ]\", \"python_version_code\": \"3.9.1\", \"metaflow_version\": \"2.6.0\", \"script\": \"hello.py\", \"ext_info\": [{}, {}], \"flow_name\": \"HelloArgoFlow\"}",
"valueFrom": null
},
{
"name": "METAFLOW_KUBERNETES_POD_NAMESPACE",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "metadata.namespace"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_POD_NAME",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "metadata.name"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_POD_ID",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "metadata.uid"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_SERVICE_ACCOUNT_NAME",
"value": null,
"valueFrom": {
"configMapKeyRef": null,
"fieldRef": {
"apiVersion": null,
"fieldPath": "spec.serviceAccountName"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
}
],
"envFrom": [],
"image": "python:3.9",
"imagePullPolicy": null,
"lifecycle": null,
"livenessProbe": null,
"name": "hello_a",
"ports": null,
"readinessProbe": null,
"resources": {
"limits": {},
"requests": {
"cpu": "1",
"memory": "4096M",
"ephemeral-storage": "10240M"
}
},
"securityContext": null,
"startupProbe": null,
"stdin": null,
"stdinOnce": null,
"terminationMessagePath": null,
"terminationMessagePolicy": null,
"tty": null,
"volumeDevices": null,
"volumeMounts": [
{
"mountPath": "/mnt/out",
"mountPropagation": null,
"name": "out",
"readOnly": null,
"subPath": null,
"subPathExpr": null
}
],
"workingDir": null
}
},
{
"name": "end",
"activeDeadlineSeconds": 432000,
"serviceAccountName": "s3-full-access",
"inputs": {
"parameters": [
{
"name": "input-paths"
}
]
},
"outputs": {
"parameters": []
},
"failFast": true,
"metadata": {
"annotations": {
"metaflow/step_name": "end",
"metaflow/attempt": "0"
}
},
"volumes": [
{
"name": "out",
"emptyDir": {}
}
],
"labels": {},
"nodeSelector": {},
"container": {
"args": null,
"command": [
"bash",
"-c",
"mkdir -p $PWD/.logs && export METAFLOW_TASK_ID=(t-$(echo end-{{workflow.creationTimestamp}}-{{inputs.parameters.input-paths}} | md5sum | cut -d ' ' -f 1 | tail -c 9)) && export PYTHONUNBUFFERED=x MF_PATHSPEC=HelloArgoFlow/argo-{{workflow.name}}/end/$METAFLOW_TASK_ID MF_DATASTORE=s3 MF_ATTEMPT=0 MFLOG_STDOUT=$PWD/.logs/mflog_stdout MFLOG_STDERR=$PWD/.logs/mflog_stderr && mflog(){ T=$(date -u -Ins|tr , .); echo \"[MFLOG|0|${T:0:26}Z|task|$T]$1\" >> $MFLOG_STDOUT; echo $1; } && mflog 'Setting up task environment.' && python -m pip install awscli requests boto3 -qqq && mkdir metaflow && cd metaflow && mkdir .metaflow && i=0; while [ $i -le 5 ]; do mflog 'Downloading code package...'; python -m awscli s3 cp s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158 job.tar >/dev/null && mflog 'Code package downloaded.' && break; sleep 10; i=$((i+1)); done && if [ $i -gt 5 ]; then mflog 'Failed to download code package from s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158 after 6 tries. Exiting...' && exit 1; fi && TAR_OPTIONS='--warning=no-timestamp' tar xf job.tar && mflog 'Task is starting.' && (python hello.py --with kubernetes:cpu=1,memory=4096,disk=10240,image=python:3.9,service_account=s3-full-access,namespace=default,gpu_vendor=nvidia --with 'environment:vars={}' --quiet --metadata=service --environment=local --datastore=s3 --datastore-root=s3://valay-k8s-testing/metaflow --event-logger=nullSidecarLogger --monitor=nullSidecarMonitor --no-pylint --with=argo_workflows_internal step end --run-id argo-{{workflow.name}} --task-id $METAFLOW_TASK_ID --retry-count 0 --max-user-code-retries 0 --input-paths {{inputs.parameters.input-paths}}) 1>> >(python -m metaflow.mflog.tee task $MFLOG_STDOUT) 2>> >(python -m metaflow.mflog.tee task $MFLOG_STDERR >&2); c=$?; python -m metaflow.mflog.save_logs; exit $c"
],
"env": [
{
"name": "METAFLOW_CODE_URL",
"value": "s3://valay-k8s-testing/metaflow/HelloArgoFlow/data/f8/f882d08568f6290d783027b6aa617bb6c336a158",
"valueFrom": null
},
{
"name": "METAFLOW_CODE_SHA",
"value": "f882d08568f6290d783027b6aa617bb6c336a158",
"valueFrom": null
},
{
"name": "METAFLOW_CODE_DS",
"value": "s3",
"valueFrom": null
},
{
"name": "METAFLOW_SERVICE_URL",
"value": "https://x3kwb6qyc6.execute-api.us-west-2.amazonaws.com/api/",
"valueFrom": null
},
{
"name": "METAFLOW_USER",
"value": "argo-workflows",
"valueFrom": null
},
{
"name": "METAFLOW_DATASTORE_SYSROOT_S3",
"value": "s3://valay-k8s-testing/metaflow",
"valueFrom": null
},
{
"name": "METAFLOW_DATATOOLS_S3ROOT",
"value": "s3://oleg-stepfn-test-metaflows3bucket-1s3wkux8ddr1/data",
"valueFrom": null
},
{
"name": "METAFLOW_DEFAULT_DATASTORE",
"value": "s3",
"valueFrom": null
},
{
"name": "METAFLOW_DEFAULT_METADATA",
"value": "service",
"valueFrom": null
},
{
"name": "METAFLOW_CARD_S3ROOT",
"value": "s3://valay-k8s-testing/metaflow/mf.cards",
"valueFrom": null
},
{
"name": "METAFLOW_KUBERNETES_WORKLOAD",
"value": "1",
"valueFrom": null
},
{
"name": "METAFLOW_RUNTIME_ENVIRONMENT",
"value": "kubernetes",
"valueFrom": null
},
{
"name": "METAFLOW_OWNER",
"value": "savin",
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},
{
"name": "METAFLOW_FLOW_NAME",
"value": "HelloArgoFlow",
"valueFrom": null
},
{
"name": "METAFLOW_STEP_NAME",
"value": "end",
"valueFrom": null
},
{
"name": "METAFLOW_RUN_ID",
"value": "argo-{{workflow.name}}",
"valueFrom": null
},
{
"name": "METAFLOW_RETRY_COUNT",
"value": "0",
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},
{
"name": "METAFLOW_PRODUCTION_TOKEN",
"value": "helloargoflow-0-symt",
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},
{
"name": "ARGO_WORKFLOW_TEMPLATE",
"value": "helloargoflow",
"valueFrom": null
},
{
"name": "ARGO_WORKFLOW_NAME",
"value": "{{workflow.name}}",
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},
{
"name": "ARGO_WORKFLOW_NAMESPACE",
"value": "default",
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},
{
"name": "METAFLOW_RUNTIME_NAME",
"value": "argo-workflows",
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},
{
"name": "USER",
"value": "savin",
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},
{
"name": "METAFLOW_VERSION",
"value": "{\"platform\": \"Darwin\", \"username\": \"savin\", \"production_token\": \"helloargoflow-0-symt\", \"runtime\": \"dev\", \"app\": null, \"environment_type\": \"local\", \"use_r\": false, \"python_version\": \"3.9.1 (default, Dec 11 2020, 06:28:49) \\n[Clang 10.0.0 ]\", \"python_version_code\": \"3.9.1\", \"metaflow_version\": \"2.6.0\", \"script\": \"hello.py\", \"ext_info\": [{}, {}], \"flow_name\": \"HelloArgoFlow\"}",
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},
{
"name": "METAFLOW_KUBERNETES_POD_NAMESPACE",
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"fieldRef": {
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"fieldPath": "metadata.namespace"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_POD_NAME",
"value": null,
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"fieldRef": {
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"fieldPath": "metadata.name"
},
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"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_POD_ID",
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"valueFrom": {
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"fieldRef": {
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"fieldPath": "metadata.uid"
},
"resourceFieldRef": null,
"secretKeyRef": null
}
},
{
"name": "METAFLOW_KUBERNETES_SERVICE_ACCOUNT_NAME",
"value": null,
"valueFrom": {
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"fieldRef": {
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"fieldPath": "spec.serviceAccountName"
},
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"secretKeyRef": null
}
}
],
"envFrom": [],
"image": "python:3.9",
"imagePullPolicy": null,
"lifecycle": null,
"livenessProbe": null,
"name": "end",
"ports": null,
"readinessProbe": null,
"resources": {
"limits": {},
"requests": {
"cpu": "1",
"memory": "4096M",
"ephemeral-storage": "10240M"
}
},
"securityContext": null,
"startupProbe": null,
"stdin": null,
"stdinOnce": null,
"terminationMessagePath": null,
"terminationMessagePolicy": null,
"tty": null,
"volumeDevices": null,
"volumeMounts": [
{
"mountPath": "/mnt/out",
"mountPropagation": null,
"name": "out",
"readOnly": null,
"subPath": null,
"subPathExpr": null
}
],
"workingDir": null
}
}
]
}
}
Aha - the UI has an additional check that prevents uploading the JSON by hand.
I have started a thread in CNCF slack to ensure that this isn't a regression within Argo Workflows UI.
thnx for your quick reply Savin! Metaflow 2.6.0.post4+gitd977cd4 I created the argo template using this command: helloworld.py argo-workflows --name=h5 create --only-json > h5.json
Aha - the UI has an additional check that prevents uploading the JSON by hand.
I've seen this a while ago. Argo UI does the validation according to the schema. Funny, that executing this via argo api, does the sanitization under the hood :)
Is this issue solved? @savingoyal @karimmohraz
I also have the same problem in Metaflow 2.6.3, Argo 3.3.5.
I create workflow template with follwing command.
python helloworld.py --with kubernetes:secrets=s3-secret argo-workflows create
@ZiminPark Are you running into this issue when you submit using the UI?
I tried both metaflow cli and Argo UI. Submitting via metaflow cli (argo-workflows create) can create a workflow template but it fails on run. And submitting via Argo UI raise same error on submission.