notebooks/components/tensorboard-controller
apoger 939e1e22ca Introduce a mechanism to build all Kubeflow images (kubeflow/kubeflow#6555)
* build: Update components makefiles for building

We'll create a top-level Makefile under components/ dir
that has the following rules:

* build-all:
  To build all images locally

* push-all:
  * We can use a specific REGISTRY and retag the images
  * Push all the images

This top-level Makefile will run the sub-Makefiles that every
component has for building and pushing the images.

We modified every sub-Makefile as follows:
* We don't use a registry in images by default
* Removed unused rules and vars
* Use the --dirty flag of git describe in TAG

        --dirty[=<mark>]
               Describe the working tree. It means describe HEAD and
               appends <mark> (-dirty by default) if the working tree
               is dirty.

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* build: Create makefiles for notebook servers

The common starting point of building the notebook-server
images are the following 4 *base* images:
- base
- codeserver
- jupyter
- rstudio

All other server images need to build on top of them. We'll
dynamically pass the base images in every Dockerfile by
using an ARG IMG. We can set the value of this ARG during
docker build with the --build-arg CLI argument.

This way we build both the base images with a tag locally,
and then we pass that image as arg via the Makefile and build the rest

So we modified our building procedure as follows:
1. Build the base image since everything starts from there

2. Pass the base image as an ARG in the Dockerfiles of
jupyter, codeserver, rstudio images and build on top

3. Pass the base images in all other server images and build
on top

For that we will:

1. Create a Makefile for each of the notebook servers, in each folder
   a. Each makefile will be responsible for building the bases and use args for passing them on

2. Use the central Makefile to call each Makefile from above

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* cherry-pick: Notebook server upstream fixes

Relevant upstream PR: https://github.com/kubeflow/kubeflow/pull/6466/files

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* build: Fix Makefiles

- Remove build-gcp and build-gcr rules as we don't use them anywhere in
the project
- Fix code conficts

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* build: Fix Dockerfiles for notbook-server images

We remove the previous logic of using already built images as bases.
The users must use only the Makefiles to pass the appropriate BASE_IMG
and build the images correctly.

Thus, we have Makefiles everywhere that:

- Can build any base image
- If an image requires another notebook base, then we first build that one using its makefile,
  and then use it as docker ARG for building the next one

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* build: Fix notebook-controller Makefile

Removed a misplaced "|" char that breaks the Makefile

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* build: Update GH action workflows

* Update workflow for notebook-server images:
  - Add a step for building all images by using the
  central-Makefile under components/example-notebook-servers/ dir.
  - Add a step for pushing all images by using the
  central-Makefile under components/example-notebook-servers/ dir.

* Update workflow for all Kubeflow images:
  - Add a step for building & pushing all images by using the
  top-level Makefile under components/ dir.

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* build: Remove completely ECR references from images

Replace everywhere the "public.ecr.aws/j1r0q0g6/notebooks/notebook-servers"
prefix with "kubeflownotebookswg"

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>

* build: Fix GH actions for Kubeflow components

Fix GH actions to use the updated make rules
when building the Kubeflow component images.

Remove the "docker.io" prefix when building with
GH action workflows

Signed-off-by: Apotolos Gerakaris <apoger@arrikto.com>
2022-07-01 17:54:06 +00:00
..
api/v1alpha1 Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
config Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
controllers Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
hack Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
.dockerignore Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
.gitignore Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
Dockerfile Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
Makefile Introduce a mechanism to build all Kubeflow images (kubeflow/kubeflow#6555) 2022-07-01 17:54:06 +00:00
OWNERS Add OWNERs file to tensorboard controller (kubeflow/kubeflow#5088) 2020-08-07 06:32:19 -07:00
PROJECT Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
README.md Add RWO_PVC_SCHEDULING env var to the Tensorboard Controller deployment (kubeflow/kubeflow#5266) 2020-08-31 08:12:21 -07:00
go.mod Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
go.sum Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
main.go Upgrade API version of `Tensorboard` CRD to `v1` (kubeflow/kubeflow#6406) 2022-06-17 09:20:10 +00:00
skaffold.yaml Fix docker builds of notebook and tensorboard controller (kubeflow/kubeflow#4664) 2020-01-21 17:54:34 -08:00

README.md

GSoC 2020 - TENSORBOARD CONTROLLER

Prequisites to build and run the controller:

  1. GO

  2. Docker

  3. kustomize

  4. kubectl

RUN TENSORBOARD CONTROLLER LOCALLY

Steps:

  1. Clone the repository

  2. Change directories to components/tensorboard-controller

  3. Generate and install manifests and build the controller: make install

  4. Run the controller locally: make run

If you want to enable the scheduling functionality for Tensorboard servers that use ReadWriteOnce PVCs as log storages, then set the RWO_PVC_SCHEDULING to true and run: RWO_PVC_SCHEDULING="true" make run

BUILD TENSORBOARD CONTROLLER IMAGE AND DEPLOY TO CLUSTER

  1. Clone the repository

  2. Change directories to components/tensorboard-controller

  3. Generate and install manifests and build the controller: make manifests

  4. Build and push the docker image: make docker-build docker-push IMG=YOUR_IMAGE_NAME

  5. Deploy the Tensorboard controller: make deploy IMG=YOUR_IMAGE_NAME

If you want to enable the scheduling functionality for Tensorboard servers that use ReadWriteOnce PVCs as log storages, then:

  1. Change directories to components/tensorboard-controller/config/manager

  2. Modify the manager.yaml file by navigating to the deployment.spec.template.spec field and manually setting the value of the RWO_PVC_SCHEDULING env var to "true" in the manager container.

  3. Run: make deploy IMG=YOUR_IMAGE_NAME