Updates to the Readme that include mission #1

aronchick · 2017-12-01T01:35:08Z

No description provided.

foxish · 2017-12-01T01:46:31Z

README.md

+
+Because ML practitioners use so many different types of tools, it is a key goal that you can customize the stack to whatever your requirements (within reason), and let the system take care of the "boring stuff." While we have started with a narrow set of technologies, we are working with many different projects to include additional tooling.
+
+Ultimately, we want to have a single deployable artifact (a manifest) that gives you an easy to use ML stack _anywhere_ Kubernetes is already running and can self configure based on the cluster it deploys into.


a set of deployable manifests? Because we're doing a directory of them, with the application step being:
kubectl apply -f dir/ -R

great point, fixed!

jlewi · 2017-12-03T01:45:47Z

README.md


-The Kubeflow project is a new open source Github repo dedicated to reducing friction in doing Machine Learning on Kubernetes. Contained in this repository are:
+The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable. Contained in this repository are:


The elements listed below aren't included in the repository; they are included in the Kubeflow distribution. Should we change the text to something like
Contained in the Kubeflow distribution? or
Contained in the Kubeflow stack?

vishh · 2017-12-03T19:14:47Z

README.md

+Our goal is to help folks use ML more easily, by letting Kubernetes to do what it's great at:
+- Easy, repeatable, portable deployments
+- Deploying and managing loosely-coupled microservices
+- Scaling based on demand


add: managing diverse infrastructure

vishh · 2017-12-03T19:16:28Z

README.md


-### Google Kubernetes Engine


Do not delete this section. It is the best way currently to try out GPUs k8s clusters.

That's fine, but it shouldn't be here - or if it is, it should have other solutions as well. As it stands, it makes it seem that this is the only way to create a production cluster.

foxish · 2017-12-04T21:19:19Z

@aronchick PTAL. Needs resolving conflict. Good to merge after that

foxish · 2017-12-05T15:23:34Z

Squashing and merging this now.

Initial repository setup.

* rename `getEnvDef` to `getEnvDefault` * Add a comment to describe how the STOP_ANNOTATION gets used Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com>

* Create a culler as a package Helper functions for culling resources. Takes for granted that ISTIO is installed to the system and queries Prometheus to get metrics. Specifically, requests/{configurable time}. If the resource should be culled, then it should be done by setting an annotation. This way the UIs can also show that the Resource is stopping and also easily stop a resource by making a PATCH request. Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Culling logic enhancements Add necessary ENV Vars. Culling won't happen by default. To enable it the user will need to set the ENABLE_CULLING=true Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Misc fixes in logging and comment cleanup Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Fix typo Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Add Notebooks specific culling Query the /api/status endpoint of each Server Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Remove the generic culling logic We need to discuss if it would make sense to have this logic as a go library, or use knative. Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Add unit tests Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Remove unused code Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Review changes #1 * rename `getEnvDef` to `getEnvDefault` * Add a comment to describe how the STOP_ANNOTATION gets used Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com> * Make cluster domain configurable Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com>

* adds ambassador and argo components to manifests * removes ksonnet labels * removed unused stubs for overlays

aronchick added 2 commits November 30, 2017 17:20

Update README.md

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Update README.md

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foxish reviewed Dec 1, 2017

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jlewi approved these changes Dec 3, 2017

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vishh reviewed Dec 3, 2017

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aronchick added 3 commits December 3, 2017 16:10

Update README.md

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Update README.md

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Merge branch 'master' into master

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aronchick and others added 2 commits December 4, 2017 14:24

Merge branch 'master' into master

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Merge branch 'master' into master

9da5882

foxish merged commit 9a657f3 into kubeflow:master Dec 5, 2017

ankushagarwal mentioned this pull request Feb 22, 2018

IAP component should use cert-manager to get a signed certificate #255

Closed

dwhitena mentioned this pull request Mar 8, 2018

Pachyderm and Kubeflow integration #151

Closed

jlewi mentioned this pull request Apr 2, 2018

JupyterHub spawner - Highlight PV requirement #541

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jlewi mentioned this pull request May 25, 2018

Presubmit unhealthy? Networking issues #869

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jlewi mentioned this pull request Jun 28, 2018

TFJobs UI doesn't work behind IAP; React APP needs support IAP? #574

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jlewi mentioned this pull request Aug 22, 2018

Don't use DM for IAM policy management #1401

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abhi-g mentioned this pull request Aug 23, 2018

Added a minikube setup script. #1387

Merged

monkey3199 mentioned this pull request Oct 4, 2018

Deploy kfctl.sh apply k8s: Failed to pull image #1651

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ellistarn mentioned this pull request Jan 26, 2019

Proposal: Kubeflow Serverless Serving CRD #2306

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kimwnasptd pushed a commit to arrikto/kubeflow that referenced this pull request Mar 5, 2019

Merge pull request kubeflow#1 from jlewi/initial_setup

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Initial repository setup.

holdenk mentioned this pull request Mar 11, 2019

Click-to-deploy non-IAP mode cloudshell link assumes GCP account is first user #2267

Closed

kimwnasptd added a commit to arrikto/kubeflow that referenced this pull request Aug 21, 2019

Review changes kubeflow#1

1d07950

* rename `getEnvDef` to `getEnvDefault` * Add a comment to describe how the STOP_ANNOTATION gets used Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com>

kimwnasptd added a commit to arrikto/kubeflow that referenced this pull request Aug 21, 2019

Review changes kubeflow#1

fe1fdab

* rename `getEnvDef` to `getEnvDefault` * Add a comment to describe how the STOP_ANNOTATION gets used Signed-off-by: Kimonas Sotirchos <kimwnasptd@arrikto.com>

jlewi mentioned this pull request Oct 22, 2019

IAP enabler is broken / gcloud crashes in IAP enabler #4342

Closed

yanniszark pushed a commit to arrikto/kubeflow that referenced this pull request Nov 1, 2019

adds ambassador and argo components to manifests (kubeflow#1)

26cfb30

* adds ambassador and argo components to manifests * removes ksonnet labels * removed unused stubs for overlays

zijianjoy mentioned this pull request Mar 24, 2021

Allow user to add/delete labels to user namespace using ConfigMap. Fix #5712 #5761

Merged

yike5460 mentioned this pull request Sep 24, 2021

Kubeflow 1.2.0 install failed on AWS EKS cluster (kfctl_aws.v1.2.0.yaml) #6151

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Updates to the Readme that include mission #1

Updates to the Readme that include mission #1

aronchick commented Dec 1, 2017

foxish Dec 1, 2017 •

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aronchick Dec 1, 2017

jlewi Dec 3, 2017

vishh Dec 3, 2017

vishh Dec 3, 2017

vishh Dec 3, 2017

aronchick Dec 4, 2017

foxish commented Dec 4, 2017

foxish commented Dec 5, 2017


		Because ML practitioners use so many different types of tools, it is a key goal that you can customize the stack to whatever your requirements (within reason), and let the system take care of the "boring stuff." While we have started with a narrow set of technologies, we are working with many different projects to include additional tooling.

		Ultimately, we want to have a single deployable artifact (a manifest) that gives you an easy to use ML stack _anywhere_ Kubernetes is already running and can self configure based on the cluster it deploys into.


		The Kubeflow project is a new open source Github repo dedicated to reducing friction in doing Machine Learning on Kubernetes. Contained in this repository are:
		The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable. Contained in this repository are:

Updates to the Readme that include mission #1

Updates to the Readme that include mission #1

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aronchick commented Dec 1, 2017

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foxish commented Dec 5, 2017

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