How to use Google Cloud Run with Kubernetes
Are you looking for a way to run your containerized applications on the cloud? Do you want to take advantage of the scalability and flexibility of Kubernetes, but don't want to deal with the complexity of managing your own cluster? If so, Google Cloud Run with Kubernetes might be the solution you're looking for!
In this article, we'll explore how to use Google Cloud Run with Kubernetes to deploy and manage your containerized applications on Google Cloud Platform (GCP). We'll cover the basics of Cloud Run and Kubernetes, and then dive into the details of how to set up and use Cloud Run with Kubernetes.
What is Google Cloud Run?
Google Cloud Run is a fully managed serverless platform that allows you to run your containerized applications without worrying about the underlying infrastructure. With Cloud Run, you simply upload your container image, and Google takes care of the rest. Cloud Run automatically scales your application based on incoming traffic, and charges you only for the resources you use.
Cloud Run supports both HTTP and gRPC requests, and can be used with any language or framework that can run in a container. You can also use Cloud Run with Knative, an open-source platform for building, deploying, and managing serverless workloads on Kubernetes.
What is Kubernetes?
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. With Kubernetes, you can deploy your applications across multiple nodes, and scale them up or down based on demand. Kubernetes also provides features like load balancing, service discovery, and rolling updates, which make it easier to manage your applications at scale.
Kubernetes can be deployed on-premises or in the cloud, and supports a wide range of container runtimes, including Docker and containerd. Kubernetes also has a large and active community, which means there are plenty of resources and tools available to help you get started.
How to use Google Cloud Run with Kubernetes
Now that we've covered the basics of Cloud Run and Kubernetes, let's dive into how to use Cloud Run with Kubernetes.
Step 1: Set up a Google Cloud Platform project
The first step is to set up a Google Cloud Platform (GCP) project. If you don't already have a GCP account, you can sign up for a free trial. Once you have a GCP account, you can create a new project by following these steps:
- Go to the GCP Console.
- Click the project drop-down menu at the top of the page.
- Click New Project.
- Enter a name for your project, and click Create.
Step 2: Enable the necessary APIs
Next, you need to enable the necessary APIs for Cloud Run and Kubernetes. To do this, follow these steps:
- Go to the APIs & Services Dashboard.
- Click Enable APIs and Services.
- Search for Cloud Run and click Cloud Run API.
- Click Enable.
- Search for Kubernetes Engine and click Kubernetes Engine API.
- Click Enable.
Step 3: Set up a Kubernetes cluster
Now that you've enabled the necessary APIs, you can set up a Kubernetes cluster. To do this, follow these steps:
- Go to the Kubernetes Engine page in the GCP Console.
- Click Create Cluster.
- Choose a name for your cluster, and select the desired location and version.
- Choose the desired machine type and number of nodes.
- Click Create.
It may take a few minutes for your cluster to be created. Once it's ready, you can use the Kubernetes command-line tool (
kubectl) to interact with your cluster.
Step 4: Deploy your application to Cloud Run
Now that you have a Kubernetes cluster set up, you can deploy your application to Cloud Run. To do this, follow these steps:
- Build your container image using your preferred tool (e.g., Docker).
- Push your container image to a container registry, such as Google Container Registry (GCR).
- Create a Kubernetes deployment that specifies your container image and any necessary configuration.
- Create a Kubernetes service that exposes your deployment to the internet.
- Create a Cloud Run service that points to your Kubernetes service.
Here's an example
kubectl command that creates a deployment and service for a simple Node.js application:
kubectl create deployment hello-node --image=gcr.io/[PROJECT_ID]/hello-node:v1
kubectl expose deployment hello-node --type=LoadBalancer --port=8080
gcloud beta run deploy hello-node --image=gcr.io/[PROJECT_ID]/hello-node:v1 --platform=managed --region=[REGION] --allow-unauthenticated
In this example, we're deploying a simple Node.js application called
hello-node. We first create a Kubernetes deployment and service for the application, and then create a Cloud Run service that points to the Kubernetes service.
Step 5: Test your application
Once your application is deployed, you can test it by visiting the URL provided by Cloud Run. In the example above, the URL would be something like
You can also use the
curl command to send HTTP requests to your application:
Step 6: Monitor and manage your application
Finally, you can monitor and manage your application using the Kubernetes and Cloud Run dashboards. The Kubernetes dashboard provides a visual interface for managing your Kubernetes resources, while the Cloud Run dashboard provides insights into your Cloud Run services.
Google Cloud Run with Kubernetes is a powerful platform for running your containerized applications on the cloud. With Cloud Run, you can take advantage of the scalability and flexibility of Kubernetes, without having to manage your own cluster. And with Kubernetes, you can automate the deployment, scaling, and management of your applications, making it easier to manage them at scale.
In this article, we've covered the basics of Cloud Run and Kubernetes, and shown you how to set up and use Cloud Run with Kubernetes. We hope this article has been helpful, and that you're now ready to start deploying your own applications to Cloud Run with Kubernetes!
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