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Setup new staging and prod environments #57
Opening this issue to document the setup of new staging and prod environments.
We'd like to roll out some changes to the label bot frontend (see kubeflow/code-intelligence#90).
It looks like the prod instance is currently running in
It looks like there are two separate ingresses in this namespace
Here's my plan
For the dev instance the webhooks are failing with 405's method not allowed.
Maybe I have the wrong URL for the webhook; maybe there's a missing path?
* machine-learning-apps#57 is tracking setting up new staging and prod environments * This PR sets up a new staging (or dev environment) * We create a kustomize manifest for deploying the front end into that namespace * The staging environment is configured to use the dev instance of the issue label bot backend microservice (i.e the pubsub workers) * I created some python scripts to make it easier to setup the secrets. * The motivation for doing this was to test the changes to the front end * Front end now forwards all issues for the kubeflow org to the backend * This is needed because we want to use multiple models for all Kubeflow repos kubeflow/code-intelligence#70 * The backend should also be configured with logging to measure the impact of the predictions. kubeflow/code-intelligence#104 is an a test issue showing that the bot is working. * Fix how keys are handled * For GOOGLE_APPLICATION_CREDENTIALS; depend on that environment variable being set and pointing to the file containing the private key; don't get the private key from an environment variable and then write it to a file. * For the GitHub App private key; use an environment variable to point to the file containing the PEM key. * Create a script to create the secrets. * Flask app is running in dev namespace * create_secrets.py creates secrets needed for dev instance