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1 change: 0 additions & 1 deletion .gitignore
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node_modules/
build/
/docs/
.coverage/
npm-debug.log
.nyc_output
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4 changes: 4 additions & 0 deletions docs/README.md
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This directory contains advanced docs around the Functions Framework.

- [Running and Deploying Docker Containers](docker.md)

## TODO Docs

- TODO: Run Multiple Cloud Functions [#23](https://github.com/GoogleCloudPlatform/functions-framework-nodejs/issues/23)
- TODO: Pub/Sub Trigger [#37](https://github.com/GoogleCloudPlatform/functions-framework-nodejs/issues/37)
- TODO: Deploy to Cloud Run [#28](https://github.com/GoogleCloudPlatform/functions-framework-nodejs/pull/28)
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48 changes: 48 additions & 0 deletions docs/docker.md
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# Run a Function in a Docker Container

To run your function in a container, create a `Dockerfile` with the following contents:

```Dockerfile
# Use the official Node.js 10 image.
# https://hub.docker.com/_/node
FROM node:10
# Create and change to the app directory.
WORKDIR /usr/src/app
# Copy application dependency manifests to the container image.
# A wildcard is used to ensure both package.json AND package-lock.json are copied.
# Copying this separately prevents re-running npm install on every code change.
COPY package.json package*.json ./
# Install production dependencies.
RUN npm install --only=production
# Copy local code to the container image.
COPY . .
# Run the web service on container startup.
CMD [ "npm", "start" ]
```

Start the container locally by running `docker build` and `docker run`:

```sh
docker build -t helloworld . && docker run --rm -p 8080:8080 helloworld
```

Send requests to this function using `curl` from another terminal window:

```sh
curl localhost:8080
# Output: Hello, World
```

## Deploy a Container

You can deploy your containerized function to Cloud Run or any Knative-based environment by following the [Cloud Run quickstart](https://cloud.google.com/run/docs/quickstarts/build-and-deploy).
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Cloud Run or Cloud Run on GKE. Other knative instances are managed with kubectl or in the future kn. Instructions for knative in that case will also need a service.yaml.

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What would you like me to say instead of Cloud Run?
Does Cloud Run not include Cloud Run on GKE?

Can you suggest a change?

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This is for Cloud Run only: https://cloud.google.com/run/docs/quickstarts/build-and-deploy

This shows how to build and deploy an existing container image to Cloud Run on GKE: https://cloud.google.com/run/docs/quickstarts/prebuilt-deploy-gke

Deploying to Knative anywhere
https://knative.dev/docs/install/getting-started-knative-app/

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I've removed the mention of Cloud Run on GKE.


Use the `docker` and `gcloud` CLIs to build and deploy a container to Cloud Run, replacing the project id `$GOOGLE_CLOUD_PROJECT` and image name `helloworld`:

```sh
docker build -t gcr.io/$GOOGLE_CLOUD_PROJECT/helloworld .
docker push gcr.io/$GOOGLE_CLOUD_PROJECT/helloworld
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Note docker push requires some extra steps to get docker authenticating with GCP. In fact, if you use Cloud Build you don't need to get docker working locally at all.

Here are some Cloud Run-specific docs on build options

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How do we want to change these steps? Do we want to link the build options?

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Based on your needs, pick Cloud Build or Docker and include mostly bare steps here, linking to that page for more context/options?

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E.g., to keep the current instructions, add gcloud auth configure-docker.

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I've added the configure docker command.

gcloud beta run deploy helloworld --image gcr.io/$GOOGLE_CLOUD_PROJECT/helloworld --region us-central1
```

If you want even more control over the environment, you can [deploy your container image to Cloud Run on GKE](https://cloud.google.com/run/docs/quickstarts/prebuilt-deploy-gke). With Cloud Run on GKE, you can run your function on a GKE cluster, which gives you additional control over the environment (including use of GPU-based instances, longer timeouts and more).