Here at Pulumi, everyone on our engineering team is a Gopher. Go has quickly become the “language of the cloud,” and so when we chose to build our open-source pulumi/pulumi engine and SaaS backend, we chose Go. As such, we are very excited to welcome Go to the family of supported infrastructure as code languages as part of Pulumi 2.0. What is Pulumi? Go has become the lingua franca of cloud-native infrastructure development.
In an earlier article, we introduced examples of Policy as Code to prevent two of the most common causes of data breaches. Policies are the guardrails of infrastructure. They control access, set limits, and manage how infrastructure operates. In many systems, policies are created by clicking on a GUI, making it difficult to replicate or version. Pulumi implements policy by writing it in Typescript, which ensures that you can write policies using software development practices such as automated testing, deployment, and version control.
Google Cloud Run is the latest addition to the serverless compute family. While it may look similar to existing services of public cloud, the feature set makes Cloud Run unique: Docker as a deployment package enables using any language, runtime, framework, or library that can respond to an HTTP request. Automatic scaling, including scale to zero, means you pay for what you consume with no fixed cost and no management overhead.
Running Kubernetes in production can be challenging. This past year, Pulumi has collected common patterns of usage informed by best practices for provisioning Kubernetes infrastructure and running containerized applications. We call this Pulumi Crosswalk for Kubernetes: a collection of playbooks and libraries to help you to successfully configure, deploy, and manage Kubernetes in a way that works for teams in production. Kubernetes is Vast and Complex Kubernetes is the standard multi-cloud platform for modern containerized applications.
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.
In this post, we will work through an example that shows how to use Pulumi to create Jupyter Notebooks on Kubernetes. Having worked on Kubernetes since 2015, a couple of critical benefits jump out that may resonate with you as well:
- You write everything in code - TypeScript in our example here.
- You need not initialize Tiller or Helm to work with existing Helm charts like
nginx-ingress-controllerthat we use here.
- The security patterns in Helm and Tiller are no longer concerns, rather you get to focus on the RBAC of the actual service which is Jupyter-notebook in this example.
- You accomplish more with less YAML and iteratively work towards your use cases.
Google Cloud is one of the most exciting cloud platforms available today, with a breadth of powerful infrastructure services from Google Container Engine (GKE) and Google Cloud Functions to Cloud Firestore and Cloud Spanner.
Pulumi is the most productive tooling available today for teams building cloud applications and infrastructure, in your favorite languages. Add them together, and teams can easily take maximum advantage of Google Cloud Platform’s rich features, productively, with a combined platform that makes it easy to collaborate, share, and reuse.