meteatamel / cloudrun-tutorial

A tutorial showing some of the features of Cloud Run

Cloud Run Tutorial

Cloud Run is a managed serverless platform that enables you to run stateless containers invocable via HTTP requests on Google Cloud.

Cloud Run is built from open-source Knative, letting you choose to run your containers either fully managed with Cloud Run, or in your Google Kubernetes Engine cluster with Cloud Run on Anthos, or use Knative on any Kubernetes cluster running anywhere.

Slides

There's a presentation that accompanies the tutorial.

Setup

Cloud Run is a fully managed service, so there's no setup other than enabling Cloud Run and Cloud Build.

Cloud Run for Anthos runs on GKE on Anthos platform.

Setup your project id and number that we'll need throughout samples:

export PROJECT_ID="$(gcloud config get-value core/project)"
export PROJECT_NUMBER="$(gcloud projects list --filter=${PROJECT_ID} --format='value(PROJECT_NUMBER)')"

Enable Cloud Build and Cloud Run:

gcloud services enable --project ${PROJECT_ID} \
    cloudbuild.googleapis.com \
    run.googleapis.com

Samples

Cloud Run Serving

• Public service
• Configure service
• Private service
• Pub/Sub triggered service
• Storage triggered service
• Scheduled service
• Task triggered service
• Service to service authentication
• Cloud Run Healthchecks

Cloud Run Eventing

• Image processing pipeline v1 - Eventarc (AuditLog-Cloud Storage) + Cloud Run
• Image processing pipeline v2 - Eventarc (Cloud Storage) + Cloud Run + Workflows
• Image processing pipeline v3 - Eventarc (Cloud Storage) + Workflows
• Image processing pipeline v1 - Eventarc (AuditLog-Cloud Storage) + Cloud Run for Anthos
• BigQuery processing pipeline - Eventarc + Cloud Run
• BigQuery processing pipeline - Eventarc + Cloud Run for Anthos

Other

• Scheduled dbt service with BigQuery
• Scheduled dbt job with BigQuery
• Deploying from source code

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This is not an official Google product.

cloudrun-tutorial's Issues

Add Cloud Run button sample

All samples are fully runnable from cmd line

Need to make sure all the samples can be run from cmd line fully. Add env variables as needed.

Move Eventarc docs to GoogleCloudPlatform/eventarc-samples repo

Update scheduled Cloud Run dbt service sample with jaffle shop instructions

Add scheduled Cloud Run job running dbt with v2

Add a gRPC enabled service

Image processing pipeline labeler service - port to Cloud Run Managed

Add a scheduled Cloud Run service running dbt

Compete the task triggered service

How to trigger only when uploaded to a specific bucket?

Currently, I try to do it from the cloud run UI with the full resource name of the bucket, like so :

But, it does not work and the event does not get triggered.

Update BigQuery Processing Pipeline with new Eventarc beta

Image processing pipeline - update all services to rely on common lib (Cloud Run Eventing GKE)

Add a service-to-service auth example

Image Processing Pipeline - GKE: Update tutorial for beta

BigQuery processing pipeline - chart creator x axis is wrong

Update public service sample with .NET 6

Image processing pipeline resizer service - port to Cloud Run Managed

Add a scheduled Cloud Run job running dbt

BigQuery processing pipeline: Update for Eventarc GA

BigQuery/Image processing pipeline samples - Remove IEventReader interface and BUCKET env variable when not needed

Change the samples to use eventarc.eventReceiver role instead

Image processing pipeline filter service - port to Cloud Run Managed

Add a CI/CD example with Cloud Build

Image Processing Pipeline Managed: Make PubSubWriter handle multiple topics

Add a .NET 7.0 Cloud Run sample

Update processing pipelines C# code to use Google.Events libraries

Cloud Storage triggered service

Sample+Tutorial: Cloud Run Healthchecks

Add a deploy from source / buildpacks sample

In this example, I'd like to show how to deploy a service without needing a Dockerfile using buildpacks, if it's possible

Image Processing Pipeline Managed: Update tutorial for beta

Image processing pipeline - update all services to rely on common lib (Cloud Run Eventing Managed)

Update processing pipelines Python code to use CloudEvent SDK

Update Image Processing Pipeline with new Eventarc beta

Image processing pipeline - port to Cloud Run Eventing GKE

BigQuery Processing Pipeline - Managed: Update tutorial for beta

BigQuery/Image processing pipeline samples - Simplify and remove EVENT_DATA_READER

Image processing pipeline: Update for Eventarc GA

BigQuery processing pipeline - port to Cloud Run Eventing Managed

BigQuery/Image processing pipeline samples - Simplify and remove EVENT_WRITER

Add a traffic splitting example

Image processing pipeline watermarker service - port to Cloud Run Managed

Update processing pipelines Python code to use Google.Events libraries

BigQuery processing pipeline - port to Cloud Run Eventing GKE

BigQuery Processing Pipeline - GKE: Update tutorial for beta

Eventarc: Remove references to manual granting of the tokenCreator to Pub/Sub P4SA