Mike Metral

Kubernetes developers and operators work together to manage workloads and to continuously ship software through CI/CD. These users have an affinity for automation and pipelines, and richer integration with Kubernetes is a growing theme across the cloud native ecosystem.

We’re excited to introduce the Pulumi Kubernetes Operator: a Kubernetes controller that deploys cloud infrastructure in Pulumi Stacks for you and your team.

These program stacks include virtual machines, block storage, managed Kubernetes clusters, API resources, serverless functions and more!

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We recently announced the 2.0 release of Pulumi which includes parity for Node.js (JavaScript, TypeScript), Python, .NET (C#, F#, etc) and Go, and improvements to Kubernetes and dozens of other supported cloud resource providers.

Kubernetes support in Pulumi spans orchestration of clusters and application workloads. Clusters can be managed by cloud providers or self-managed. Workloads use the same Kubernetes API to create and manage API resources in the supported Pulumi languages through packages directly generated from the OpenAPI specification.

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Amazon EKS clusters can use IAM roles and policies for Pods to assign fine-grained access control of AWS services. The AWS IAM entities map into Kubernetes RBAC to configure the permissions of Pods that work with AWS services.

Together, AWS IAM and Kubernetes RBAC enable least-privileged access for your apps, scoped to the appropriate policies and user requirements.

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Kubernetes clusters from the managed platforms of AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), and GCP Google Kubernetes Engine (GKE) all vary in configuration, management, and resource properties. This variance creates unnecessary complexity in cluster provisioning and application deployments, as well as for CI/CD and testing.

Additionally, if you wanted to deploy the same app across multiple clusters for specific use cases or test scenarios across providers, subtleties such as LoadBalancer outputs and cluster connection settings can be a nuisance to manage.

In this post, we’ll see how to use Pulumi to deploy the kuard app across EKS, AKS, GKE and a local Kubernetes cluster, such as Docker Desktop or a self-managed cluster. We’ll spin up the clusters in each provider, launch the app, and manage both cluster and app using the TypeScript programming language.

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Managed Kubernetes offerings greatly reduce the overhead required in administering Kubernetes. However, the cluster is only one of the components under management, as app lifecycles are self-driven tasks that vary by workloads.

In Kubernetes, node groups are a useful mechanism for creating pools of resources that can enforce scheduling requirements. They also provide a utility for shifting workloads around during cluster management and updates.

In this post, we’ll see how to use Pulumi for Day 2 Kubernetes administration. We’ll spin up a new EKS cluster with two node groups and a given workload. Then we’ll add one more node group with an updated configuration, and migrate the workload over to it with zero downtime using code and kubectl.

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The Kubernetes landscape is constantly evolving as end users and developers search for the right tools, approaches, and abstractions to help them manage Cloud Native infrastructure in production.

On Feb 5, Heptio (now part of VMWare) announced that work on ksonnet, a project launched by Heptio, Box, Microsoft, and Bitnami, will stop. We’re sad to see ksonnet winding down, but are thankful for the collaborative exchange of ideas between projects, and are excited to see continued investment in VMWare/Heptio’s other projects. The good news is that, if you liked ksonnet, we’re confident that you’ll love Pulumi. In this post, we’ll tell you why.

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