[Feature] KFP pipeline artifacts remain on in-cluster SeaweedFS while syncing to external AWS S3 or Azure Blob in the background - #311
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GiladShapira94
requested changes
Aug 20, 2026
…dation for SeaweedFS remote configuration
…d, detailing local and remote storage options with configuration examples
… configuration; enhance validation checks for Azure provider
…etails; refactor static credentials usage in templates
… disable remote storage
…guration details; add nonempty option in values.yaml for handling existing pipeline data during upgrades
…structions; update values.yaml for Azure storage configuration; enhance validation checks for Azure provider in templates
…rom values files and templates; update README.md to clarify SeaweedFS usage for pipeline artifacts.
…nfiguration; enhance validation checks for SeaweedFS remote provider in templates.
… by breaking down the command into multiple lines for better readability and maintainability.
GiladShapira94
requested changes
Sep 1, 2026
… configuration; enhance Azure Blob example and clarify usage in templates.
…riptions; include guidelines for examples, optional Helm values, and template hygiene.
| ```bash | ||
| helm upgrade --install mlrun-ce charts/mlrun-ce -n mlrun \ | ||
| -f <your-environment-values>.yaml \ | ||
| -f charts/mlrun-ce/examples/seaweedfs-remote-s3-overlay.yaml \ |
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if you point the user to the relevant values file, why the user also need the additional --set commands?
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it is a good idea but let's split it to another skill (pr-review) if you prefer you can open another PR only for this additional change
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📝 Description
Adds SeaweedFS remote gateway support so KFP pipeline artifacts remain on in-cluster SeaweedFS (
pipelines.storage.mode: local) while syncing to external AWS S3 or Azure Blob in the background.This replaces the previous model where KFP talked directly to external object storage via
pipelines.storage.mode: s3/azure-blob. MLRun and Jupyter storage (storage.mode) is unchanged and independent.🛠️ Changes Made
seaweedfs.remote.enabled):seaweedfs-remote-secret.yaml— cloud credentials (S3 keys fromstorage.s3.*, Azure fromstorage.azure.*)seaweedfs-remote-config-job.yaml— Helm hook Job that runsremote.configure+remote.mounton the filerseaweedfs-remote-gateway-deployment.yaml—filer.remote.gatewaysyncs local bucket → remote backendexamples/seaweedfs-remote-s3-overlay.yaml,examples/seaweedfs-remote-azure-overlay.yamlstorage-validation.yaml):pipelines.storage.mode: local(rejects direct external KFP modes)seaweedfs.remote.*(provider, bucket, remote name charset, S3 endpoint, credentials)_helpers.tpl):mlrun-ce.pipelines.storage.modehardcoded tolocalprovidersblock fromkfp-launcher.yamlOBJECTSTORECONFIG_REGIONfromml-pipeline.yamlmlpipeline-seaweedfs-artifact.yaml→mlpipeline-artifact-secret.yamlmysql.yaml): auth plugin flag selected by image tag —--default-authentication-pluginfor 8.0.x,--mysql-native-password=ONfor 8.4+deployment.yaml+values.yaml): addedstartupProbe(/api); readiness probe path changed from/labto/apifor slow cold startsseaweedfs.remoteblock (defaultenabled: false); added tovalues.yamland all three install-mode values files0.12.0-rc.11✅ Checklist
charts/mlrun-ce/Chart.yaml.🧪 Testing
Please see