It is assumed that you have a working Python environment and a Google Cloud account and SDK configured.

1. Install dependencies using virtualenv:

   virtualenv -p python3 env
   source env/bin/activate
   pip install -r requirements.txt

2. Test running the code, optional:

   # Run the server:
   python greeter_server.py
   
   # Open another command line tab and enter the virtual environment:
   source env/bin/activate
   
   # In the new command line tab, run the client:
   python greeter_client.py

3. The gRPC Services have already been generated. If you change the proto, or just wish to regenerate these files, run:

   python -m grpc.tools.protoc \
       --include_imports \
       --include_source_info \
       --proto_path=protos \
       --python_out=. \
       --grpc_python_out=. \
       --descriptor_set_out=api_descriptor.pb \
       helloworld.proto

4. Edit, api_config.yaml. Replace MY_PROJECT_ID with your project id.

5. Deploy your service config to Service Management:

   gcloud endpoints services deploy api_descriptor.pb api_config.yaml
   
   # Set your project ID as a variable to make commands easier:
   GCLOUD_PROJECT=<Your Project ID>
   

6. Also get an API key from the Console's API Manager for use in the client later. Get API Key

7. Enable the Cloud Build API:

   gcloud services enable cloudbuild.googleapis.com

8. Build a docker image for your gRPC server, and store it in your Registry:

   gcloud container builds submit --tag gcr.io/${GCLOUD_PROJECT}/python-grpc-hello:1.0 .

9. Either deploy to GCE (below) or GKE (further down).

1. Enable the Compute Engine API:

   gcloud services enable compute-component.googleapis.com

2. Create your instance and ssh in:

   gcloud compute instances create grpc-host --image-family gci-stable --image-project google-containers --tags=http-server
   gcloud compute ssh grpc-host

3. Set some variables to make commands easier:

   GCLOUD_PROJECT=$(curl -s "http://metadata.google.internal/computeMetadata/v1/project/project-id" -H "Metadata-Flavor: Google")
   SERVICE_NAME=hellogrpc.endpoints.${GCLOUD_PROJECT}.cloud.goog

4. Pull your credentials to access Container Registry, and run your gRPC server container:

   /usr/share/google/dockercfg_update.sh
   docker run --detach --name=grpc-hello gcr.io/${GCLOUD_PROJECT}/python-grpc-hello:1.0

5. Run the Endpoints proxy:

   docker run --detach --name=esp \
       --publish=80:9000 \
       --link=grpc-hello:grpc-hello \
       gcr.io/endpoints-release/endpoints-runtime:1 \
       --service=${SERVICE_NAME} \
       --rollout_strategy=managed \
       --http2_port=9000 \
       --backend=grpc://grpc-hello:50051

6. Back on your local machine, get the external IP of your GCE instance:

   gcloud compute instances list

7. Run the client:

   python greeter_client.py --host=<IP of GCE Instance>:80 --api_key=<API Key from Console>

8. Cleanup:

   gcloud compute instances delete grpc-host

1. Create a cluster. You can specify a different zone than us-central1-a if you want:

   gcloud container clusters create my-cluster --zone=us-central1-a

2. Edit deployment.yaml. Replace SERVICE_NAME and GCLOUD_PROJECT with your values:

   SERVICE_NAME is equal to hellogrpc.endpoints.GCLOUD_PROJECT.cloud.goog, replacing GCLOUD_PROJECT with your project ID.

3. Deploy to GKE:

   kubectl create -f ./deployment.yaml

4. Get IP of load balancer, run until you see an External IP:

   kubectl get svc grpc-hello

5. Run the client:

   python greeter_client.py --host=<IP of GKE LoadBalancer>:80 --api_key=<API Key from Console>

6. Cleanup:

   gcloud container clusters delete my-cluster --zone=us-central1-a