When developing a service to deploy on Kubernetes, do you sometimes feel like you’re more focused on your YAML files than on your application? When working with YAML, do you find it hard to detect errors early in the development process? We created Cloud Code to let you spend more time writing code and less time configuring your application, including authoring support features such as inline documentation, completions, and schema validation, a.k.a. “linting.”

1  Completions provided by Cloud Code.gifCompletions provided by Cloud Code for a Kubernetes deployment.yaml file

2 Inline documentation provided by Cloud Code.gifInline documentation provided by Cloud Code for a Kubernetes deployment.yaml file

3 Schema validation provided by Cloud Code.gifSchema validation provided by Cloud Code for a Kubernetes deployment.yaml file

But over the years, working with Kubernetes YAML has become increasingly complex. As Kubernetes has grown more popular, many developers have extended the Kubernetes API with new Operators and Custom Resource Definitions (CRDs). These new Operators and CRDs expanded the Kubernetes ecosystem with new functionality such as continuous integration and delivery, machine learning, and network security.Today, we’re excited to share authoring support for a broad set of Kubernetes CRDs, including:

  • Over 400 popular Kubernetes CRDs out of the box—up from just a handful
  • Any existing CRDs in your Kubernetes cluster
  • Any CRDs you add from your local machine or a URL

Cloud Code is a set of plugins for the VS Code and JetBrains Integrated Development Environments (IDEs), and provides everything you need to write, debug, and deploy your cloud-native applications. Now, its authoring support makes it easier to write, understand, and see errors in the YAML for a wide range of Kubernetes CRDs.

Cloud Code’s enhanced authoring support lets you leverage this custom Kubernetes functionality by creating a resource file that conforms to the CRD. For example, you might want to distribute your TensorFlow jobs across multiple pods in a cluster. You can do this by authoring a TFJob resource based on the TFJob CRD and applying it to the cluster where the KubeFlow operator can act on it.

Expanding built-in support

Cloud Code has expanded authoring support for over 400 of the most popular Kubernetes CRDs, including those used by Google Cloud and Anthos. This includes a wide variety of CRDs such as:

  • Agones for game servers
  • Gatekeeper for enforcing policy
  • KubeFlow for machine learning workflows
  • Calico for networking and network security
  • cert-manager for managing and issuing TLS certificates
  • and many more

#application development #google cloud platform #containers & kubernetes

Cloud Code features expanded support for Kubernetes CRDs
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