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Add docs for KIND deployment #266
Add docs for KIND deployment #266
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Resolves machine-learning-exchange#73 Signed-off-by: Christian Kadner <[email protected]>
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I have the 2016 15 inch macbook pro. Here are my spec By giving all my resources to the Docker daemon, I'm able to deploy the manifests and run basic pipelines. However, if I try to run notebooks or after the model is deployed, my laptop will get very slow and loud to a point that start to crash my apps. |
Signed-off-by: Christian Kadner <[email protected]>
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brew install kubectl | ||
kubectl version --client | ||
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brew install kustomize |
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We need kustomize 3.2 for this manifest. Can you point to the kustomize instruction like the one on ibm kubeflow?
https://www.kubeflow.org/docs/distributions/ibm/deploy/deployment-process/#kubeflow-installation
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I added this para:
Note: We successfully tested this KIND deployment with the latest version of
kustomize
v4.4.0
.
However, there have been issues in the past with versions later thenv3.2.0
. To be on the safe side
you could download thekustomize
v3.2.0
binary as described
here
Signed-off-by: Christian Kadner <[email protected]>
Signed-off-by: Christian Kadner <[email protected]>
@@ -67,7 +67,7 @@ git clone https://github.com/IBM/manifests -b v1.4.0-mlx | |||
cd manifests | |||
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# run the below command two times if the CRDs take too long to provision. | |||
while ! kustomize build mlx-single | \ | |||
while ! kustomize build mlx-single-kind | \ |
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@yhwang @Tomcli -- I think the install-mlx-on-kind.md is ready to be merged, unless you have further change requests. We can improve it in follow up PRs, like coming up with a better alternative to the port-forwarding: Instead of:
Use a kind cluster configuration like this apiVersion: kind.x-k8s.io/v1alpha4
kind: Cluster
nodes:
- role: control-plane
extraPortMappings:
- containerPort: 3000
hostPort: 80
- role: worker |
@phu since you got the most powerful laptop in the team now, would you mind giving this KIND deployment a spin and let us know your feedback? Deployment takes about 20 minutes on older machines. I am curious what deployment times you'll get :-) Thanks! |
/lgtm |
* Add link to KIND deployment doc * Update the script that checks for broken links * Fix broken links in usage steps and API README * Update the resource requirements for KIND * Add a deployment wait-loop for KIND * Update the import assets documentation Related machine-learning-exchange#266 Signed-off-by: Christian Kadner <[email protected]>
* Add link to KIND deployment doc * Update the script that checks for broken links * Fix broken links in usage steps and API README * Update the resource requirements for KIND * Add a deployment wait-loop for KIND * Update the import assets documentation Related #266 Signed-off-by: Christian Kadner <[email protected]>
Add first draft document for deploying MLX on KIND (Kubernetes in Docker).
https://github.com/ckadner/mlx/blob/add_kind_deployment_doc/docs/install-mlx-on-kind.md
@Tomcli @yhwang