Getting Started with Endpoints for Cloud Run for Anthos with ESPv2

This page shows you how to set up Cloud Endpoints for Cloud Run for Anthos. Endpoints uses the Extensible Service Proxy V2 (ESPv2) as an API gateway. To provide API management for Cloud Run for Anthos, you deploy the prebuilt ESPv2 container to Cloud Run for Anthos running on a GKE cluster.

With this set up, ESPv2 intercepts all requests to your services and performs any necessary checks (such as authentication) before invoking the service. When the service responds, ESPv2 gathers and reports telemetry.

For an overview of Endpoints, see About Endpoints and Endpoints architecture.

Task List

Use the following task list as you work through the tutorial. All tasks are required to complete this tutorial.

  1. Create a Google Cloud project, and if you haven't deployed your own Cloud Run for Anthos, deploy a sample service. See Before you begin.

  2. Create a GKE cluster with Cloud Run for Anthos enabled.

  3. Deploy a gRPC sample Cloud Run for Anthos service.

  4. Create an gRPC API configuration document that describes your Endpoints API, and configure the routes to your Cloud Run for Anthos service. See Configuring Endpoints.

  5. Deploy the gRPC API configuration document to create a managed service. See Deploying the Endpoints configuration.

  6. Build a new ESPv2 Docker image with your Endpoints service configuration. See Building a new ESPv2 image.

  7. Deploy the new ESPv2 Cloud Run for Anthos image. See Deploying the ESPv2 Cloud Run image.

  8. Create a domain mapping to the ESPv2 Cloud Run for Anthos service.

  9. Test your configuration by Sending a request to the API.

  10. Track activity to your services. See Tracking API activity.

  11. Clean up.

Before you begin

  1. Sign in to your Google Account.

    If you don't already have one, sign up for a new account.

  2. In the Google Cloud Console, on the project selector page, select or create a Google Cloud project.

    Go to the project selector page

  3. Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.

  4. Make a note of the project ID because it is needed later. On the rest of this page, this project ID is referred to as ESP_PROJECT_ID.
  5. Download and install the Cloud SDK.

Setting up the gcloud command line

To set up the gcloud command line for Cloud Run for Anthos for Anthos:

  1. Make sure that Cloud SDK is authorized to access your data and services.

    1. Log in.

      gcloud auth login

    2. On the new browser tab that opens, choose an account that has the Editor or Owner role in the Google Cloud project that you created for deploying ESPv2 to Cloud Run for Anthos.

  2. Update installed gcloud components:

    gcloud components update
  3. Set the platform to gke and set your default project setting for gcloud to the one you just created:

    gcloud config set run/platform gke 
    gcloud config set project ESP_PROJECT_ID

    Replace ESP_PROJECT_ID with the project ID of the project you created.

  4. Set the desired zone for the new cluster. You can use any zone where GKE is supported, for example:

    gcloud config set compute/zone ZONE

    Replace ZONE with your zone. For example, use us-central1-a. You can use any zone supported by GKE.

  5. Enable the following APIs for the project, which are needed to create a cluster, build and publish a container into the Google Container registry:

    gcloud services enable container.googleapis.com containerregistry.googleapis.com cloudbuild.googleapis.com

Creating a GKE cluster with Cloud Run for Anthos enabled

To create a cluster and enable it for Cloud Run for Anthos on Google Cloud:

  1. Create a new cluster using the command:

    gcloud container clusters create CLUSTER_NAME \ 
      --addons=HttpLoadBalancing,CloudRun \ 
      --machine-type=n1-standard-4 \ 
      --num-nodes=3 \ 
      --enable-stackdriver-kubernetes

    Replace CLUSTER_NAME with the name you want for your cluster.

    Although these instructions don't enable cluster autoscaling to resize clusters for demand, Cloud Run for Anthos on Google Cloud automatically scales instances within the cluster.

  2. Wait for the cluster creation to complete. During the creation process, you should see messages similar to the following:

    Creating cluster CLUSTER_NAME...done. 
    Created [https://container.googleapis.com/v1/projects/ESP_PROJECT_ID/zones/ZONE/clusters/CLUSTER_NAME].

    The output also shows the cluster version under the NODE_VERSION column of the output. For example, 1.15.11-gke.1 or 1.14.10-gke.27. Make note of the cluster version for use later in this document.

  3. Set gcloud defaults to use your new cluster and cluster location, to avoid having to specify these when you use the gcloud command line:

    gcloud config set run/cluster CLUSTER_NAME
    gcloud config set run/cluster_location ZONE
  4. Use the following command to view details about the new cluster:

    gcloud container clusters describe CLUSTER_NAME
  5. Use the following command to fetch credentials for your cluster:

    gcloud container clusters get-credentials CLUSTER_NAME

Deploying a sample gRPC Cloud Run service

To deploy the "grpc-bookstore" Cloud Run for Anthos sample container to the cluster you just created:

  1. Follow the steps in the gRPC Python quickstart to install gRPC and the gRPC tools.

  2. This gRPC server sample contains a pre-build Docker image for the Python "grpc-bookstore service": gcr.io/endpointsv2/python-grpc-bookstore-server:2. Use the following command to deploy "grpc-bookstore" to your cluster:

    gcloud run deploy GRPC_SERVICE \
      --image=gcr.io/endpointsv2/python-grpc-bookstore-server:2 \
      --platform=gke \
     --connectivity=internal \
      --use-http2

    Note that you specify this as an internal service so that the service is not externally accessible.

    Replace GRPC_SERVICE with the name you want for your service. For example:

    gcloud run deploy grpc-bookstore \
      --image=gcr.io/endpointsv2/python-grpc-bookstore-server:2 \
      --platform=gke \
      --connectivity=internal \
      --use-http2

    When you are done, the following message appears:

    Service [grpc-bookstore] revision [grpc-bookstore-00001-nuk] has been deployed and is serving 100 percent of traffic at http://grpc-bookstore.default.svc.cluster.local

    When you create an internal service, GKE creates a DNS name (grpc-bookstore.default.svc.cluster.local in this example) that can only be resolved for requests originating from within the cluster itself, not for external requests. You cannot access this DNS externally from the cluster. See Cloud Run services for more.

  3. To verify that your service is working correctly, deploy a pod with the same Docker image to your cluster. The image contains the gRPC client code for "grpc-bookstore" that you can use to test the internal service.

    1. Use the following kubectl command to deploy a pod to the same cluster as you deployed above:

      kubectl run grpc --generator=run-pod/v1 \
        --image=gcr.io/endpointsv2/python-grpc-bookstore-server:2

      This image contains the bookstore_client.py script that you can use to make client requests from within the cluster.

      Note: For newer versions of kubectl, the command might issue the following warning:

      Flag --generator has been deprecated, has no effect and will be removed in the future".

      You can ignore that warning.

    2. Get the name of the "grpc-bookstore" pod created on your cluster when you deployed the Docker image in the previous step:

      kubectl get pods

      You should see output in the form:

      NAME   READY    STATUS    RESTARTS   AGE
      grpc   1/1      Running   0          23h

      Where grp the name of the "grpc-bookstore" pod. Ensure that the Status of the pod is Running before continuing.

    3. Use the following command to make a client request to the "grpc-bookstore" service:

      kubectl exec grpc -ti -- python3 bookstore_client.py \
        --host grpc-bookstore.default.svc.cluster.local --port=80

      This command runs the bookstore_client.py script internally on the cluster to make a gRPC request to the "grpc-bookstore" service on the hostname grpc-bookstore.default.svc.cluster.local.

      If everything is working correctly, you should see a response in the form:

      ListShelves: shelves {
        id: 1
        theme: "Fiction"
      }
      shelves {
        id: 2
        theme: "Fantasy"
      }

Configuring Endpoints

You must have a gRPC API spec that describes the surface of your backend service and any authentication requirements.

About setting the name field of the gRPC API spec

In the name field of the gRPC API spec, you specify the Endpoints service name used to access your Cloud Run for Anthos service. The Endpoints service name is in the form of a domain name:

API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog

Because the Endpoints service name corresponds to a domain name, the name must follow these rules:

  • Must contain only lowercase letters, numbers, periods, or dashes.
  • Must not start with a dash.
  • Must not contain an underscore.

For example:

grpc-boostore-api.endpoints.ESP_PROJECT_ID.cloud.goog

Creating the gRPC API spec

The bookstore-grpc sample contains the files that you need to copy locally and configure.

  1. Create a new directory for the gRPC API spec, such as my-anthos-grpc. Then cd to that directory.

  2. Clone the git repo where the gRPC client code is hosted to your new directory:

    git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
  3. Change your working directory:

    cd python-docs-samples/endpoints/bookstore-grpc/

    Note that this directory contains the bookstore.proto file. This file defines the Bookstore service's API.

  4. Create a self-contained protobuf descriptor file from your service .proto file:

    1. Create the generated_pb2 directory under your working directory.

    2. Create the descriptor file, api_descriptor.pb, by using the protoc protocol buffers compiler. Run the following command in the directory containing bookstore.proto:

      python3 -m grpc_tools.protoc \
      --include_imports \
      --include_source_info \
      --proto_path=. \
      --descriptor_set_out=api_descriptor.pb \
      --python_out=generated_pb2 \
      --grpc_python_out=generated_pb2 \
      bookstore.proto

    In the preceding command, --proto_path is set to the current working directory. In your gRPC build environment, if you use a different directory for .proto input files, change --proto_path so the compiler searches the directory where you saved bookstore.proto.

  5. Modify the api_config_anthos.yaml file in your current working directory (the same directory that contains bookstore.proto) to add the following contents to the file:

    type: google.api.Service
    config_version: 3
    #
    # Name of the service configuration.
    #
    name: API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog
    #
    # API title to appear in the user interface (Google Cloud Console).
    #
    title: Bookstore gRPC API In Cloud Run Anthors
    apis:
    - name: endpoints.examples.bookstore.Bookstore
    #
    # Create a DNS record to map your service name to IP address
    #
    endpoints:
      - name: API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog
        target: IP_ADDRESS
    #
    # Specify the backend address to route to
    #
    backend:
      rules:
        - selector: "*"
          address: grpc://GRPC_SERVICE.default.svc.cluster.local
          disable_auth: true
    #
    # API usage restrictions.
    #
    usage:
      rules:
      # ListShelves methods can be called without an API Key.
      - selector: endpoints.examples.bookstore.Bookstore.ListShelves
        allow_unregistered_calls: true

    Indentation is important for yaml format.

  6. In the name field, specify the domain name of the Endpoints API used to access your Cloud Run for Anthos service, in the form:

    API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog

    For example:

    grpc-bookstore-api.endpoints.ESP_PROJECT_ID.cloud.goog

  7. The endpoints section registers a DNS entry for your Endpoints service on the cloud.goog domain, in the form:

    endpoints:
      - name: API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog
        target: IP_ADDRESS

    The IP_ADDRESS is the IP of the istio-ingress service for your cluster. To determine this IP address:

    1. Go to the Google Kubernetes Engine page in the Cloud Console:

      Go to Google Kubernetes Engine

    2. Click Services & Ingress in the left navigation panel to display a list of services.

    3. If your cluster version is 1.15.3-gke.19 or greater, 1.14.3-gke.12 or greater, or 1.13.10-gke.8 or greater, scroll down to the istio-ingress service. For all other cluster versions, scroll down to the istio-ingressgateway service.

    4. Copy the external IP address shown next to the Load Balancer, without the port setting, if there is one. For example, if the IP is XX.XXX.XX.XXX:15020, omit the :15020. Ignore the other IP addresses listed.

  8. The address field in the backend section specifies the internal DNS name of the Cloud Run "grpc-bookstore" service with proto scheme grpc://, and disables authentication to this service:

    address: grpc://GRPC_SERVICE.default.svc.cluster.local
    disable_auth: true

    For example:

    address: grpc://grpc-bookstore.default.svc.cluster.local
    disable_auth: true

    This is necessary because the call from ESPv2 to the Cloud Run for Anthos service is made as an internal call from within the cluster and therefore authentication is not necessary.

  9. Note the value of the title property in the api_config_authos.yaml file:

    title: Bookstore gRPC API In Cloud Run Anthos

    The value of the title property becomes the name of the Endpoints service after you deploy the configuration.

  10. Save your gRPC API document.

For information about the fields in the OpenAPI document that Endpoints requires, see Configuring Endpoints.

Deploying the Endpoints configuration

To deploy the Endpoints configuration, you use the gcloud endpoints services deploy command. This command uses Service Management to create a managed service.

To deploy the Endpoints configuration:

  1. Make sure you are in the directory that contains your gRPC document.

  2. Upload the configuration and create a managed service.

    gcloud endpoints services deploy api_descriptor.pb api_config_anthos.yaml \ 
      --project ESP_PROJECT_ID

    This creates a new Endpoints service with the name that you specified in the name field of the api_config_anthos.yaml file. The Endpoints service is configured according to your OpenAPI document.

    As it is creating and configuring the Endpoints service, Service Management outputs information to the terminal. When the deployment completes, a message similar to the following is displayed:

    Service Configuration [CONFIG_ID] uploaded for service [API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog]

    CONFIG_ID is the unique Endpoints service configuration ID created by the deployment. For example:

    Service Configuration [2019-02-01r0] uploaded for service [grpc-bookstore-api.endpoints.ESP_PROJECT_ID.cloud.goog] 

    The service configuration ID consists of a date stamp followed by a revision number. If you deploy api_config_anthos.yaml again on the same day, the revision number is incremented in the service configuration ID. You can view the service configuration and the deployment history on the Endpoints > Services page in the Cloud Console.

    If you get an error message, see Troubleshooting Endpoints configuration deployment.

Checking required services

At a minimum, Endpoints and ESP require the following Google services to be enabled:
Name Title
servicemanagement.googleapis.com Service Management API
servicecontrol.googleapis.com Service Control API
endpoints.googleapis.com Google Cloud Endpoints

In most cases, the gcloud endpoints services deploy command enables these required services. However, the gcloud command completes successfully but doesn't enable the required services in the following circumstances:

  • If you used a third-party application such as Terraform, and you don't include these services.

  • You deployed the Endpoints configuration to an existing Google Cloud project in which these services were explicitly disabled.

Use the following command to confirm that the required services are enabled:

gcloud services list

If you do not see the required services listed, enable them:

gcloud services enable servicemanagement.googleapis.com
gcloud services enable servicecontrol.googleapis.com
gcloud services enable endpoints.googleapis.com

Also enable your Endpoints service:

gcloud services enable ENDPOINTS_SERVICE_NAME

To determine the ENDPOINTS_SERVICE_NAME you can either:

  • After deploying the Endpoints configuration, go to the Endpoints page in the Cloud Console. The list of possible ENDPOINTS_SERVICE_NAME are shown under the Service name column.

  • For OpenAPI, the ENDPOINTS_SERVICE_NAME is what you specified in the host field of your OpenAPI spec. For gRPC, the ENDPOINTS_SERVICE_NAME is what you specified in the name field of your gRPC Endpoints configuration.

For more information about the gcloud commands, see gcloud services.

Building a new ESPv2 Cloud Run for Anthos image

Build the Endpoints service config into a new ESPv2 docker image. After creating this image, you can deploy it to your cluster.

To build the service config into a new ESPv2 docker image:

  1. Download this script to your local machine where the gcloud SDK is installed and run it as:

    chmod +x gcloud_build_image 
    ./gcloud_build_image -s API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog \ 
    -c CONFIG_ID -p ESP_PROJECT_ID

    The script uses the gcloud command to download the service config, build the service config into a new ESPv2 image, and upload the new image to your project container registry. The script automatically uses the latest release of ESPv2, denoted by the ESP_VERSION in the output image name. The output image is uploaded to:

    gcr.io/ESP_PROJECT_ID/endpoints-runtime-serverless:ESP_VERSION-API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog-CONFIG_ID

Deploying the ESPv2 Cloud Run for Anthos image

Deploy the ESPv2 Cloud Run for Anthos service image to your cluster:

  1. Deploy the ESPv2 Cloud Run for Anthos service with the new image:

    gcloud run deploy ESP_V2_SERVICE_NAME \ 
      --image="gcr.io/ESP_PROJECT_ID/endpoints-runtime-serverless:API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog-CONFIG_ID" \ 
      --platform gke \
      --use-http2 \
      --project=ESP_PROJECT_ID

    For ESP_PROJECT_ID specify the name that you want to use for the ESPv2 service. In this example, set ESP_V2_SERVICE_NAME to espv2.

  2. If you want to configure Endpoints to use additional ESPv2 startup options, such as enabling CORS, you can pass the arguments in the ESPv2_ARGS environment variable:

    gcloud run deploy ESP_V2_SERVICE_NAME \
      --image="gcr.io/ESP_PROJECT_ID/endpoints-runtime-serverless:API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog-CONFIG_ID" \ 
      --set-env-vars=ESPv2_ARGS=--cors_preset=basic \ 
      --platform gke --use-http2 \
      --project ESP_PROJECT_ID

    For more information and examples on setting the ESPv2_ARGS environment variable, including the list of available options and information on how to specify multiple options, see Extensible Service Proxy V2 flags.

Creating a domain mapping to the ESPv2 Cloud Run for Anthos service

To be able to omit the host header when you make a request, add a domain mapping for the ESPv2 service:

  1. Go to Cloud Run

  2. Select Manage Custom Domains.

  3. Select Add Mapping.

  4. From the dropdown, select Add service domain mapping.

  5. In the Select a service to map to field of the Add mapping popup, select your ESPv2 service.

  6. In the Enter domain name field, specify the domain name you want to use to access your Cloud Run for Anthos service through Endpoints. For example, specify:

    API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog

    Where API_NAME is the name of your Endpoints API. For this example, you can use "hello-api":

    grpc-bookstore-api.endpoints.ESP_PROJECT_ID.cloud.goog

  7. Click Continue. A summary of the mapping appears.

  8. Select Done to save the mapping.

Sending requests to the API

To send requests to the sample API, you can use a sample gRPC client written in Python.

  1. Make sure you are in the directory that contains your gRPC documents, such as api_config_anthos.yaml.

  2. Install dependencies:

    pip3 install virtualenv
    virtualenv env
    source env/bin/activate
    pip3 install -r requirements.txt
  3. Send a request to the sample API:

    python3 bookstore_client.py --host API_NAME.endpoints.ESP_PROJECT_ID.cloud.goog --port 80

    For example:

    python3 bookstore_client.py --host grpc-bookstore-api.endpoints.ESP_PROJECT_ID.cloud.goog --port 80

    If everything is working correctly, you should see a response in the form:

    ListShelves: shelves {
      id: 1
      theme: "Fiction"
    }
    shelves {
      id: 2
      theme: "Fantasy"
    }

If you don't get a successful response, see Troubleshooting response errors.

You just deployed and tested an API in Endpoints!

Configuring Endpoints API to use HTTPS

Automatic TLS support is disabled by default for Cloud Run for Anthos on Google Cloud. Therefore, in this example when you access your Endpoints API through ESPv2, you make the call using HTTP.

You can configure ESPv2 to support requests using HTTPS. Note that you configure HTTPS support on ESPv2, the external service, not on "hello", the internal backend service.

To support HTTPS with ESPv2, you must:

  1. Own a domain. If you don't have a domain, you can obtain one from Google or from another domain vendor.

  2. Create a domain mapping for your ESPv2 service and have updated your DNS record accordingly following the instructions at the domains mapping page.

    If you obtained your domain from Google Domains, use that as your DNS server. Otherwise use Cloud DNS, or a DNS server of your choice. Using a domain from Google Domains is the easiest option.

  3. In the Endpoints OpenAPI spec:

    1. Set the name field to refer to your domain instead of to *.cloud.goog.

    2. Remove the endpoints tag and its two child properties.

For complete instructions and tutorial, see Enabling HTTPS and automatic TLS certificates.

Tracking API activity

  1. View the activity graphs for your API on the Endpoints > Service page in the Cloud Console.

    View Endpoints activity graphs

    It may take a few moments for the request to be reflected in the graphs.

  2. Look at the request logs for your API on the Logs Viewer page.

    View Endpoints request logs

Creating a developer portal for the API

You can use Cloud Endpoints Portal to create a developer portal, a website that you can use to interact with the sample API. To learn more, see Cloud Endpoints Portal Overview.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used in this quickstart, follow these steps.

See Deleting an API and API instances for information on stopping the services used by this tutorial.

What's next