Before you deploy a service to Cloud Run, you can develop it locally using a Cloud Run emulator.
Configuring your service for development
If you don't have a .vscode/launch.json
file defined, the
Run/Debug on Cloud Run Emulator dialog lets you configure your launch and
then saves your settings to .vscode/launch.json
. If you have a
.vscode/launch.json
file configured, you can edit the file directly.
To run your service locally, specify your configuration:
- Open the command palette (press
Ctrl
/Cmd
+Shift
+P
or click View > Command Palette) and then run the Run on Cloud Run Emulator command. In the Run/Debug on Cloud Run Emulator dialog, set the specifications for your configuration:
- Only locally-installed build tools are available for Cloud Run Emulator
- Choose Docker or Buildpacks as your builder and then specify the source
- (Optional) To specify any environment variables to pass to the running
containers, expand Advanced Build Settings and then click to specify
key-value pairs.
Name Description Example PORT The port for the HTTP server to listen on. 8080 K_SERVICE The name of the Cloud Run service being run. hello-world K_REVISION The name of the Cloud Run revision being run. hello-world.1 K_CONFIGURATION The name of the Cloud Run configuration that created the revision. hello-world - (Optional) To specify Cloud SQL connections, expand Advanced Service Settings, click Connections, and then specify one Cloud SQL connection per line.
- (Optional) Check the Make the service accessible from other devices on the local network option.
- (Optional) If you only want to rebuild and run your service manually, instead of automatically when you make a change, uncheck the Automatically re-build and re-run on changes option.
Running your service locally
- After you define your preferred settings, run your service by clicking Run.
Monitor the status of your deployment in the output window.
After deployment is complete, you can view your running service by opening the URL displayed in the output window.
To view verbose logs, switch to the detailed Cloud Run view in the output window.
After your session completes, right-click to use the following commands:
- View Logs: Open the application logs of a specific deployment with the Cloud Code Logs Explorer
- Open URL: Open the application service URL of a specific service in a web browser
If you've turned off watch mode in your launch configuration and you want to make changes to your application and rebuild and redeploy the application, click the Cloud Code status bar and then click Turn on watch mode.
To stop your deployment, you can click the Stop button in the action bar for your current deployment.
Storing secrets
If your code includes potentially sensitive data like API keys, passwords, and certificates, storing them as secrets can help secure them. The Cloud Code Secret Manager integration lets you securely store these secrets and fetch them programmatically. For a detailed look at how you can create and manage secrets with Cloud Code, see the Secret Manager guide.
Customizing an existing launch.json configuration
The Cloud Code plugin updates the launch.json
configuration file
automatically when you choose a run action. To further customize how your
service is run, you can specify the following fields in your
.vscode/launch.json
file:
watch: Watches for changes in the workspace and reruns the service. True by default.
The following sample shows watch set to
true
:"watch": true,
build: Specify the builder (Docker, jibMaven, jibGradle, or buildpacks) to build your images with.
The following sample shows a Docker builder:
"build": { "docker": { "path": "Dockerfile" } },
The following sample shows a buildpack builder:
"build": { "buildpacks": { "path": "src/requirements.txt", "builder": "gcr.io/buildpacks/builder:v1" } },
image: Specify the name of the image to use.
The following sample shows how to specify an image name:
"image": "hello-world",
service: Specify the Cloud Run service to use.
The following sample shows how to specify a service name, port, and resource limits:
"service": { "name": "hello-world", "containerPort": 8080, "resources": { "limits": { "memory": "256Mi" } } },
debug: Specify debug settings such as remote path mapping to map a local path to a path on the remote container.
The following sample shows a debug section that indicates the source files' location:
"debug": { "sourceFileMap": { "${workspaceFolder}": "/app" } }
Enable Skaffold file sync and hot reloading
To improve the efficiency of your local development workflow and avoid having to rebuild, redeploy, and restart your pods, Skaffold supports copying changed files to a deployed container. This means that when you're making changes to static and source code files, you can see your changes take effect in seconds, making for an accelerated feedback loop.
For static files (like HTML and CSS files), this file copying behavior is called file syncing.
For source code files, this behavior is called as hot reloading and supports the following file types:
- Go: *.go
- Java: *.java, *.kt, *.scala, *.groovy, *.clj
- NodeJS: *.js, *.mjs, *.coffee, *.litcoffee, *.json
With hot reloading configured, Skaffold detects changes to supported files and syncs these changes to the running container on your cluster. Changes to file types that don't support hot reloading trigger an image rebuild and pod restart.
Automatic file-syncing and hot reloading are enabled by default when you're
working with Buildpacks as your preferred builder. For other builders like
Docker, you can specify a sync
section in your skaffold.yaml
file for the
artifact you're customizing.
Your sync setting can be one of (in order of preference):
auto
: Skaffold automatically configures the sync. (only for Jib and Buildpacks artifacts.) This is the default for Buildpacks.infer
: The destinations for each changed file are inferred from the builder.manual
: You must specify the files in your local workspace and their destination in the running container.
The following sample sync
section in a skaffold.yaml
file specifies a
manual
sync to synchronize all /static-html
HTML files to the static
folder in a container:
build: artifacts: - image: gcr.io/k8s-skaffold/node-example context: node sync: manual: - src: 'static-html/*.html' dest: static
For a detailed look at file syncing and specifying sync rules, see the Skaffold guide on file sync.