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@renovate renovate bot commented Jul 1, 2021

Mend Renovate

This PR contains the following updates:

Package Type Update Change
gcr.io/ml-pipeline/api-server Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/cache-deployer Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/cache-server Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/frontend Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/metadata-envoy Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/metadata-writer Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/persistenceagent Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/scheduledworkflow Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/viewer-crd-controller Kustomization minor 1.6.0 -> 1.8.5
gcr.io/ml-pipeline/visualization-server Kustomization minor 1.6.0 -> 1.8.5
kubeflow/kubeflow minor v1.3.0-rc.1 -> v1.7.0
kubeflow/pipelines minor 1.6.0 -> 1.8.22
kubeflow/tf-operator minor v1.1.0 -> v1.6.0

⚠ Dependency Lookup Warnings ⚠

Warnings were logged while processing this repo. Please check the Dependency Dashboard for more information.


Release Notes

kubeflow/kubeflow

v1.7.0

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What's new
What's fixed
Code health

v1.6.1

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v1.6.0

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KF 1.6 release 🎉

What's new ✨
What's fixed 🐛
Upgrade notes ⏫

v1.5.0

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KF 1.5 release 🎉

What's new ✨
What's fixed 🐛
Upgrade notes ⏫
  1. Update the Jupyter web apps configmap with the new storage structure https://github.com/kubeflow/kubeflow/pull/6321
  2. Notebook Controller is using different ENV Vars for culling https://github.com/kubeflow/kubeflow/blob/master/components/proposals/20220121-jupyter-notebook-idleness.md#upgrade-notes
  3. The Profile Controller is adding different Katib metrics labels https://github.com/kubeflow/kubeflow/pull/6225

v1.4.0

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Web apps:

Internationalization progress:

Central Dashboard:

Jupyter web app

Notebooks

TensorBoards

PodDefaults

Other improvements

v1.3.0

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v1.3.0 stable release for components owned by WG-Notebooks.

kubeflow/pipelines

v1.8.22: KFP SDK v1.8.22

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Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.22

For changelog, see release notes.

v1.8.21: KFP SDK v1.8.21

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Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.21

For changelog, see release notes.

v1.8.20: KFP SDK v1.8.20

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Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.20

For changelog, see release notes.

v1.8.19: KFP SDK v1.8.19

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Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.19

For changelog, see release notes.

v1.8.18: KFP SDK v1.8.18

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Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.18

For changelog, see release notes.

v1.8.17: KFP SDK v1.8.17

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Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.17

For changelog, see release notes.

v1.8.16: KFP SDK v1.8.16

Compare Source

Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.16

For changelog, see release notes.

v1.8.15: KFP SDK v1.8.15

Compare Source

Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.15

For changelog, see release notes.

v1.8.14: KFP SDK v1.8.14

Compare Source

Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.14

For changelog, see release notes.

v1.8.13: KFP SDK v1.8.13

Compare Source

Release of the KFP SDK only.

To install the KFP SDK:

pip install kfp==1.8.13

For changelog, see release notes.

v1.8.5: Backend v1.8.5

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To deploy Kubeflow Pipelines in an existing cluster, follow the instruction in here or via UI here

Install python SDK (python 3.7 above) by running:

python3 -m pip install kfp kfp-server-api --upgrade

See the Change Log

v1.8.4: Backend v1.8.4

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To deploy Kubeflow Pipelines in an existing cluster, follow the instruction in here or via UI here

Install python SDK (python 3.7 above) by running:

python3 -m pip install kfp kfp-server-api --upgrade

See the Change Log

v1.8.3: Backend v1.8.3

Compare Source

To deploy Kubeflow Pipelines in an existing cluster, follow the instruction in here or via UI here

Install python SDK (python 3.7 above) by running:

python3 -m pip install kfp kfp-server-api --upgrade

See the Change Log

v1.8.2: Backend v1.8.2

Compare Source

To deploy Kubeflow Pipelines in an existing cluster, follow the instruction in here or via UI here

Install python SDK (python 3.7 above) by running:

python3 -m pip install kfp kfp-server-api --upgrade

See the Change Log

v1.8.1

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Bug Fixes

v1.8.0

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⚠ BREAKING CHANGES
  • Use Argo Emissary Executor instead of Docker by default. Partial #​5718 (#​7137)
  • sdk.v2: Block task dependency referencing tasks inside a sibling condition or loop group. (#​7050)
  • sdk: Deprecate V2 compatible mode in v1 compiler (#​6958)
  • sdk.v2: Merge v2 experimental change back to v2 namespace (#​6890)
Features
  • Use Argo Emissary Executor instead of Docker by default. Partial #​5718 (#​7137) (bea751c)
  • backend: Upgrade go client for MLMD to 1.5.0. Partial #​7029 (#​7101) (ba59a64)
  • backend: Upgrade MLMD to 1.4.0 (#​6910) (b3d15cd)
  • backend: Upgrade MLMD to 1.5.0 (#​6996) (7157764)
  • chore: add labels and error to the gcp_resources.proto (3da295e)
  • component: add BQ export model component (28c666f)
  • component: add code for creating and monitoring bq job (9cb0e71)
  • component: add generic custom training job component (a74eba1)
  • component: adding bq create model component (fef8c03)
  • component: adding bq evaluate model component (27d2ab5)
  • component: adding bq predict model component (90e759c)
  • component: adding component yaml and tests for bq query job component (accacf6)
  • component: fix typo in bp component (9062749)
  • component: rename bq query job remote runner to bq remote runner for more bq components. (57cc5c3)
  • component: rename VertexBatchPredictJob -> VertexBatchPredictionJob (#​6757) (ca34902)
  • component/google-cloud: Add component yaml for Dataflow python component. (5902597)
  • component/google-cloud: Add sample notebook for HP Tuning Job (98677b2)
  • component/google-cloud: Add sample notebook for HP Tuning Job (#​6729) (16c8928)
  • components: Add a KServe component (#​6881) (72185ff)
  • components: Add GetWorkerPoolSpecsOp and update sample notebook to include training new model from tuning results (30308ea)
  • components: Add IsMetricBeyondThresholdOp util function for HP tuning job; add tests for all util components (37b3397)
  • components: Add util components for getting best trial/hyperparameters; delete HP Tuning Job lightweight python version to avoid potential confusion (a62bdbe)
  • components: not wait for dataflow job to finish in python component (eeb0b9c)
  • components/google-cloud: Accept UnmanagedContainerModel artifact in Batch Prediction component (e39eed1)
  • components/google-cloud: Add distributed training sample for custom job wrapper (#​6724) (ecbbdf4)
  • components/google-cloud: Commit experimental Vertex Evaluation component. (4cf9e5b)
  • components/google-cloud: Update ground_truth_column and update public container for Vertex Evaluation component. (b892888)
  • frontend: Allow setting s3 region for artifacts (#​6409) (af51bd1)
  • frontend: Disable delete button if no pipeline version is not selected (#​6973) (6de35db)
  • frontend: RunDetail -> Detail tab for KFPv2. Fix #​6710 (#​6717) (40df465)
  • frontend: SubDAG styling for KFPv2. Fix #​6419 (#​6744) (31ff9ad)
  • frontend: Update unknown and invalid execution node style (#​6795) (2ffa212)
  • frontend: Upgrade MLMD client to 1.5.0. Partial #​7029 (#​7102) (ef8e092)
  • frontend: Upload V2 Pipelines. Fix PipelineSpec editor prettified view. (#​6909) (feebc6b)
  • frontend: V2 create run from UI (#​7001) (a1bef77)
  • frontend: View pipeline from run ID in KFPv2. Fix #​6758 (#​6759) (b7a455d)
  • google-cloud: Add 'generate_feature_attribution' and executor_output to Evaluation component inputs. (25508b6)
  • google-cloud: Update Evaluation Component to let the dataflow service account be an optional input (10df58c)
  • manifests: Add liveness Probe for cloud sql proxy. Fix #​4973 (#​6904) (3bdf8c0)
  • sdk: Add filters to python client. (#​6748) (37d3234)
  • sdk: add load_component_from_* (#​6822) (f1bb852)
  • sdk: Add load_component_from_spec. Fixes #​5708 #​3748 (#​6690) (3e6c776)
  • sdk: add metadata field for importer (#​7112) (5a29d7f)
  • sdk: add set_env_variable for Pipeline task (#​6919) (cd20373)
  • sdk: Add version description optionally to Py SDK. Part of #​6256 (#​6472) (5dfae1d)
  • sdk: Deprecate V2 compatible mode in v1 compiler (#​6958) (8aee621)
  • sdk: Extend SDK client with disable/delete run methods (#​6754) (ba0bb60)
  • sdk: ImporterSpec v2 (#​6917) (c4d8dfd)
  • sdk: Improve CLI experience for archiving experiments, managing recurring runs and listing resources (#​6934) (ddbfcde)
  • sdk: Pipeline task settings (#​6746) (78dfac7)
  • sdk: Use google.protobuf.Value in v2 for passing parameters. (#​6804) (0be57c3)
  • sdk.v2: Implement v2 experimental compiler. (#​6803) (02b96f0)
  • v2: control flow - conditional (#​7088) (048218b)
  • adds secrets to ml-pipeline-ui-artifact deployments in user profiles (#​5864) (c6c826d)
  • sdk.v2: Merge v2 experimental change back to v2 namespace (#​6890) (7921946)
  • v2: iterator and sub-DAG basic support (#​6985) (713558c)
  • allow the default-editor to edit argo workflows and fix bug #​6649 (#​6622) (83ce21f)
  • sdk.v2: Implement experimental [@component](https://togithub.com/component) component (#​6825) (ea2e5be)
  • v2: V2 create run api (#​6689) (2e94575)
  • upgrade argo to v3.1.14 (#​6809) (4cf34e2)
  • api: Update pipeline_spec.proto to add pipeline_job_uuid and pipeline_job_name in PipelineTaskFinalStatus (#​6557) (6252b09)
  • api: Updates pipeline_spec.proto to use google.protobuf.Value (#​6402) (b8c450f)
  • backend: Adding prometheus annotations for ml-pipeline service (#​6572) (7875b68)
  • backend: support uploading v2 pipeline spec. Fixes #​6169 (#​6513) (49de8a9)
  • component: add new artifact types for gcp resources (#​6627) (286a495)
  • component: use resource name for input artifact (#​6698) (89e4c1c)
  • components: Add and update existing documentations for GCPC components (#​6525) (99d1823)
  • components: Add model upload container component (#​6609) (8a363ef)
  • components: Add static YAML for batch predict, create endpoint, upload and deploy model (#​6466) (66a1840)
  • components: Adds Notebooks Executor API in the experimental components (#​6630) (cd37c2c)
  • components: Copy the GCP components to contrib folder (#​6421) (c783705)
  • components: Implement HyperparameterTuningJob component (#​6235) (d9e463f)
  • components: move dataflow/bq component to google-cloud (#​6422) (d864db1)
  • components: Refresh the create endpoint component to follow container interface (#​6647) (8b67505)
  • components: Update batch prediction component (#​6663) (fc40e0a)
  • components: Update model deploy and model export components (#​6654) (bc19d92)
  • components/google-cloud: Add a new forecasting training component that uses the experimental flags (#​6591) (77585f0)
  • components/google-cloud: add a new python based component that connects the forecasting preprocessing component with the training component (#​6568) (cd4f191)
  • components/google-cloud: add dataflow wait component (#​6484) (166c71c)
  • components/google-cloud: Add description for prep data for train component. (#​6597) (6ed4899)
  • components/google-cloud: add gcp resources proto (#​6478) (572643f)
  • components/google-cloud: add preprocessing_bigquery_dataset to the inputs of preprocessing component (#​6461) (c127996)
  • components/google-cloud: add README.md file for forecasting components. (#​6452) (a72c8b7)
  • components/google-cloud: Add support for labels in custom_job wrapper (#​6579) (400ed0c)
  • components/google-cloud: Create remote runner for batch prediction jobs (#​6580) (be47be1)
  • components/google-cloud: Expose all Custom Job parameters via Custom Job wrapper (#​6539) (680e917)
  • components/google-cloud: Move flex template python files from piper (#​6617) (7c939bd)
  • components/google-cloud: Support Proto Plus serialization (#​6464) (610a1f2)
  • components/google-cloud: Write proper GCP_RESOURCE parameter to the custom_job output (#​6558) (83ecb97)
  • deployment: update and secure metacontroller (#​6537) (5c5f210)
  • frontend: Add styling for Artifact Node. Partial #​6280 (#​6418) (964a62e)
  • frontend: Add to UI pipeline version description. Part of #​6256 (#​6393) (19b3de4)
  • frontend: Create an Expand button to open SubDAG. Partial #​6301 (#​6490) (a358124)
  • frontend: Execution,Artifact side panel for KFPv2 Run Detail. Fix #​6740 Fix #​6739 Partial #​6676 (#​6741) (d2c234a)
  • frontend: Runtime DAG in RunDetailsV2. Fix #​6673 (#​6694) (74c7773)
  • frontend: Show hyperlink from Execution to Pipeline Run detail page and Original Execution cache. Fix #​5977 (#​6556) (3ba2a18)
  • frontend: Show Pipeline Spec in Pipeline Detail page. Fix #​6279 (#​6524) (5c2b529)
  • frontend: SidePanel for static pipeline template. Fix #​6399, Fix #​6610, Fix #​6611 (#​6613) (5c89d51)
  • frontend: Stateful v2 Node styling. Fix #​6280 (#​6519) (f6ee12a)
  • frontend: SubDag Node and mock samples. Partial #​6419. Fix #​6302. Fix #​6398 (#​6420) (d03277f)
  • frontend: Support Pipeline summary card and pulling version template for V2. Fix #​6633 (#​6634) (e0f4f7c)
  • frontend: V2 Run Details - Toolbar, Page title, Experiments. Fix #​6708, partial #​6707 (#​6709) (a441369)
  • sdk: Add BaseModel to component_spec data classes (#​6372) (65174cd)
  • sdk: Add IfPresentPlaceholder and ConcatPlaceholder for dsl v2 (#​6639) (96a2609)
  • sdk: add v2 placeholder variables (#​6693) (a2cdf74)
  • sdk: ComponentStore - URI template support. Fixes #​4708 (#​5434) (daccc5a)
  • sdk: Configure pipeline run service account. Fixes #​6424 (#​6455) (139acc8)
  • sdk: detail option to kfp run get. Fixes #​6315 (#​6404) (728915f)
  • sdk: Enable containerizing v2 Python components (#​6417) (fe66377)
  • sdk: Enable re-use of PVC with VolumeOp (#​6582) (24331a9)
  • sdk: load v1 and v2 component spec (#​6497) (8100c5e)
  • sdk: Local runner supports additional docker options. Fixes #​6598 (#​6599) (36e627d)
  • sdk: Update cloudpickle to 2.0.0 (fixes #​6699) (#​6703) (bcb0d96)
  • sdk.v2: Define PipelineParameterChannel and PipelineArtifactChannel. (#​6470) (2176fee)
  • sdk.v2: Support set_display_name in v2. (#​6471) (cfefc6d)
  • sdk.v2: Support container environment variable in v2. (#​6515) (29226e9)
  • v2: added importer support (#​6415) ([4438929

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@renovate renovate bot changed the title Update gcr.io/kfserving/kfserving-controller Docker tag to v0.6.0 Update kubeflow-pipelines Docker tags (minor) Aug 6, 2021
@renovate renovate bot force-pushed the renovate/kubeflow-pipelines branch from b020667 to aaccbf4 Compare August 6, 2021 17:37
@renovate renovate bot force-pushed the renovate/kubeflow-pipelines branch 5 times, most recently from 4567f4e to 7653872 Compare August 31, 2021 04:20
@renovate renovate bot force-pushed the renovate/kubeflow-pipelines branch 2 times, most recently from 0a7f54d to f8be929 Compare October 8, 2021 18:37
@renovate renovate bot force-pushed the renovate/kubeflow-pipelines branch 3 times, most recently from 517abd8 to cfb29dd Compare October 31, 2021 19:18
@renovate renovate bot force-pushed the renovate/kubeflow-pipelines branch from cfb29dd to 86c666e Compare March 7, 2022 15:56
@renovate renovate bot changed the title Update kubeflow-pipelines Docker tags (minor) Update kubeflow-pipelines (minor) Mar 7, 2022
@renovate renovate bot force-pushed the renovate/kubeflow-pipelines branch from 86c666e to 743d877 Compare March 26, 2022 15:22
@renovate renovate bot force-pushed the renovate/kubeflow-pipelines branch from 743d877 to 91a7d0d Compare June 18, 2022 20:25
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