Version 0.1.13

Install python SDK (python 3.5 above) by running:

pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.13/kfp.tar.gz --upgrade

See the Change Log

Version 0.1.12

To deploy this version, visit
https://deploy.kubeflow.cloud/#/deploy?version=a1afdd6c4b297b56dd103a8bb939ddeae67c2c92

Or following this instruction and set

export KUBEFLOW_TAG=a1afdd6c4b297b56dd103a8bb939ddeae67c2c92

Install python SDK (python 3.5 above) by running:

pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.12/kfp.tar.gz --upgrade

See the Change Log

Version 0.1.11

Install python SDK (python 3.5 above) by running:

pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.11/kfp.tar.gz --upgrade

Version 0.1.10

Deploy this release to GCP
https://deploy.kubeflow.cloud/#/deploy?version=e1408f2293ce72b5a89a9b40bc1998c56ac0d73b

Install python SDK (python 3.5 above) by running:

pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.10/kfp.tar.gz --upgrade

Connect to the UI:

kubectl port-forward --namespace kubeflow $(kubectl get pod --namespace kubeflow --selector="service=ambassador" --output jsonpath='{.items[0].metadata.name}') 8080:80

open http://localhost:8080/pipeline

See the Change Log

Version 0.1.9

To deploy this version, visit
https://deploy.kubeflow.cloud/#/deploy?version=64a7c55ea8a9b3732a3bba6d25057f5dbf301cfa

Or following this instruction and set

export KUBEFLOW_TAG=64a7c55ea8a9b3732a3bba6d25057f5dbf301cfa

Install python SDK (python 3.5 above) by running:

pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.9/kfp.tar.gz --upgrade

See the Change Log

Version 0.1.8

Install python SDK (python 3.5 above) by running:
pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.8/kfp.tar.gz --upgrade

See the Change Log.

Version 0.1.7

This pipeline version is included in Kubeflow v0.4.1. To deploy, visit
https://www.kubeflow.org/docs/started/getting-started-gke/

Install python SDK (python 3.5 above) by running:
pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.7/kfp.tar.gz --upgrade

Change Log

Closed issues:

• Use "Start" for runs, "Create" for experiments #649
• go vet in Travis tests breaks tests for unrelated PRs #646
• Building backend using Bazel fails on mac #638
• ml-pipeline-persistenceagent fails a few times. #624
• Unable to plug-in default values to Pipeline #618
• Add deployed model cleanup code to the Kubeflow notebook #608
• Compare page perf optimizations #597
• OAth client instructions are ambiguous #586
• "Waiting for the IAP setup to get ready..." after clicking "Skip IAP" #585
• UI should allow creating a run with no experiment #573
• studyjob-controller start failed #546
• Failing e2e sample tests do not log any errors #515
• Authentication and service account plan for Pipeline + Kubeflow #374
• Error getting logs #290
• Support filtering in list APIs #270
• Switch to Go 1.11 modules and package management. #187

Merged pull requests:

• Release component image version d3c4add #655 (IronPan)
• Correctly ignore src/apis when building frontend #654 (yebrahim)
• Use linguist annotations to skip diffing generated files #652 (yebrahim)
• Use "create" rather than "start" except when initiating a run #650 (rileyjbauer)
• Fix shadowing errors in Viewer reconciler #648 (neuromage)
• Add IS_SUBSTRING operator for use in API resource filtering. #645 (neuromage)
• Add changelog to pipeline repo #644 (IronPan)
• Update WORKSPACE and BUILD files incoporating recent changes #639 (neuromage)
• fix deploy model name conflict in case of concurrent notebook sample test #636 (gaoning777)
• Print sample test logs in case of exception throw #635 (gaoning777)
• Expose pipeline/job API through setup.py #634 (IronPan)
• Fix retrying logic which was causing persistenceagent to crash loop. #633 (neuromage)
• Add resnet-cmle sample back. Update all component images. #632 (qimingj)
• Updates material-ui and react npm libraries #630 (rileyjbauer)
• Generate pipeline and job python client as part of SDK #628 (IronPan)
• Fix gpu sample issues #627 (hongye-sun)
• Run go vet as part of the Travis CI. #626 (neuromage)
• Sanity check filtering/sorting options in list requests. #625 (neuromage)
• Support replacable arguments in command as well (besides arguments) in container op. #623 (qimingj)
• Update sample notebook to clean up deployed models. #622 (qimingj)
• URLEncode instead of base64 encode the filter string #620 (neuromage)
• DSL refactor #619 (gaoning777)
• Expose that the python API is Python3.5+ only #616 (TimZaman)
• Load sample when pipeline initially started #615 (IronPan)
• Use Bazel to build the entire backend and perform API code generation #609 (neuromage)
• Improve condition sample to demonstrate ==, >= and <. #607 (qimingj)
• fix for boostrapp problem #602 (xiaozhouX)
• Initial version of BigQuery query execution component. #601 (cbreuel)
• First step to bring back CMLE sample. #599 (qimingj)
• Compare perf - pure components, disable ROC curve thumbnail animations #598 (yebrahim)
• Move backend unit tests to Travis #589 (yebrahim)
• Deployment - Minikube support - Passing the platform parameter to kfctl #588 (Ark-kun)
• Fix the List run to get all runs #583 (IronPan)
• retry on create table in api server #582 (IronPan)
• switch from go dep to go module #581 (IronPan)
• Add sample test without image build #578 (gaoning777)
• remove xgboost compiled sample #576 (gaoning777)
• Add a gpu sample #575 (hongye-sun)
• Backend - Removed hardcoded metrics file name #574 (Ark-kun)
• update dockerfile and add build step of frontend #567 (chenzhiwei)
• Encode filter parameter as a base64-encoded JSON string in List requests #563 (neuromage)
• Tests - Updated image-builder Makefile #500 (Ark-kun)
• Add the Viewer CRD controller for managing web views such as Tensorboard instances from within the Pipelines UI. #449 (neuromage)

Version 0.1.6

You can install ML Pipeline services by running:
kubectl create -f https://storage.googleapis.com/ml-pipeline/release/0.1.6/bootstrapper.yaml

Install python SDK (python 3.5 above) by running:
pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.6/kfp.tar.gz --upgrade

Access UI instructions:
https://www.kubeflow.org/docs/guides/accessing-uis/

Changelog since v0.1.5

• Bumping the sample version

Version 0.1.5

You can install ML Pipeline services by running:
kubectl create -f https://storage.googleapis.com/ml-pipeline/release/0.1.5/bootstrapper.yaml

Install python SDK (python 3.5 above) by running:
pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.5/kfp.tar.gz --upgrade

Changelog since v0.1.4

• Bumping the sample version

Version 0.1.4

You can install ML Pipeline services by running:
kubectl create -f https://storage.googleapis.com/ml-pipeline/release/0.1.4/bootstrapper.yaml

Install python SDK (python 3.5 above) by running:
pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.4/kfp.tar.gz --upgrade

Changelog since v0.1.3

SDK

• Support Cloud TPU