deployment

Deploying MLApp

This directory contains manifests for the backend of the mlapp associated with mlbot.net.

This is currently running on a GKE cluster.

See machine-learning-apps/Issue-Label-Bot#57 for a log of how the service was deployed.

To build a new image

skaffold build

Then to update the image

cd overlays/dev|prod
kustomize edit set image gcr.io/github-probots/label-bot-frontend=gcr.io/github-probots/label-bot-frontend:${TAG}@${SHA}

github-probots

There is a dedicated instance running in

• GCP project: github-probots
• cluster: kf-ci-ml
• namespace: mlapp

Deploying it

1. Create the deployment

   kubectl apply -f deployments.yaml  
   

2. Create the secret

   gsutil cp gs://github-probots_secrets/ml-app-inference-secret.yaml /tmp
   kubectl apply -f /tmp/ml-app-inference-secret.yaml
   

3. Create the ingress

   kubectl apply -f ingress.yaml
   

issue-label-bot-dev

There is a staging cluster for testing running in

• GCP project: github-probots
• cluster: kf-ci-ml
• namespace: label-bot-dev

Deploying it

1. Create the secrets

TODO(jlewi): instructions below are outdated

1. Create the deployment

   kubectl apply -f deployments-test.yaml  
   

2. Create the secret

   gsutil cp gs://github-probots_secrets/ml-app-inference-secret-test.yaml /tmp
   kubectl apply -f /tmp/ml-app-inference-secret-test.yaml -n mlapp
   

3. Create the service

   kubectl apply -f service-test.yaml
   

4. Create the ingress

   kubectl apply -f ingress-test.yaml