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 <[email protected]>

* 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 <[email protected]> * 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 <[email protected]> * Misc fixes in logging and comment cleanup Signed-off-by: Kimonas Sotirchos <[email protected]> * Fix typo Signed-off-by: Kimonas Sotirchos <[email protected]> * Add Notebooks specific culling Query the /api/status endpoint of each Server Signed-off-by: Kimonas Sotirchos <[email protected]> * 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 <[email protected]> * Add unit tests Signed-off-by: Kimonas Sotirchos <[email protected]> * Remove unused code Signed-off-by: Kimonas Sotirchos <[email protected]> * Review changes #1 * rename `getEnvDef` to `getEnvDefault` * Add a comment to describe how the STOP_ANNOTATION gets used Signed-off-by: Kimonas Sotirchos <[email protected]> * Make cluster domain configurable Signed-off-by: Kimonas Sotirchos <[email protected]>

* 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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Update README.md

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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

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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

Closed

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

Closed

ellistarn mentioned this pull request Jan 26, 2019

Proposal: Kubeflow Serverless Serving CRD #2306

Closed

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

Merge pull request kubeflow#1 from jlewi/initial_setup

5ab8c3b

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 <[email protected]>

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 <[email protected]>

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

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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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