We had a fantastic time at KubeCon in San Diego. At the event, the Pulumi team released two technology previews: Pulumi Crosswalk for Kubernetes and Pulumi Query for Kubernetes.

Crosswalk for Kubernetes is a set of common patterns compiled in playbooks. These patterns reduce the complex Kubernetes API syntax by providing trusted defaults with idiomatic Kubernetes. Checkout a quick introduction to Crosswalk for Kubernetes in this blog post.

Sara Novotny defined observability as “the ability to ask of your system and learn from it” during her keynote with Liz Fong-Jones. Query for Kubernetes enables observability programmatically by exposing resource processes through either batch or streaming queries. Learn more about Query for Kubernetes in our blog post.

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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.

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We often need answers to simple questions about Kubernetes resources. Questions like:

• How many distinct versions of MySQL are running in my cluster?
• Which Pods are scheduled on nodes with high memory pressure?
• Which Pods are publicly exposed to the internet via a load-balanced Service?

Each of these questions would normally be answered by invoking kubectl multiple times to list resources of each type, and manually parsing the output to join it together into a single report.

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Today we announced Pulumi Crosswalk for Kubernetes, a collection of open source tools, libraries, and playbooks to help developers and operators work together to bring Kubernetes into their organizations. They capture the lessons we learned this past year working with organizations to go from zero to Kubernetes in production for their infrastructure and application workloads. By releasing these as open source, we hope to help everybody be more successful with their Kubernetes projects — as we have learned through experience, it isn’t easy going!

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Kubernetes provides a rich, standards-based API that works across cloud and on-premise infrastructure. However, many of the API fields are deeply nested and require users to specify the same values redundantly across different resources. While this explicit specification is necessary for Kubernetes to operate, this often leads users to copy-paste existing code to manage the boilerplate.

Today, as part of our Crosswalk for Kubernetes announcement, we’re introducing the Kubernetes Extensions (kx) library for Pulumi. kx is designed to simplify the declaration of Kubernetes resources, and make the API easier for everyone to use.

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Today we are excited to announce the Preview of .NET Core support for all of your modern infrastructure as code needs. This means you can create, deploy, and manage your infrastructure, on any cloud, using your favorite .NET language, including C#, F#, and VB.NET.

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We are always excited when people join the Infrastructure as Code community and write about their experiences. Pulumi can be used for a range of common tasks such as standardizing VPC builds, building VSphere virtual machines, or deploying your infrastructure from a CI/CD pipeline. Whether it’s TypeScript, JavaScript, or Python you can build your infrastructure with your language and tools of choice. Here are three new blog posts that show how to use Pulumi with code examples to perform these tasks.

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Continuous delivery is about making changes in your application and getting them into production securely, quickly, and consistently. Pulumi’s infrastructure as code approach uses source code to model cloud resources, making it ideal for continuous delivery. Your infrastructure code can share the same process as your application code including running unit and integration tests, performing code reviews via Pull Requests, and examining your infrastructure using linters or static analysis tools. Like your application, your cloud infrastructure can be validated and tested before deploying to production. Pulumi can integrate into any CI/CD system (such as Jenkins, Azure DevOps, CircleCI, TravisCI, Codefresh, and others), so let’s take a look at how to implement a deployment server, using Octopus as an example.

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In this post, we will talk about the best way to architect your Pulumi applications. We are going to build out the following infrastructure in AWS:

• AWS Fargate service that does not serve traffic directly
• AWS ALB as the entry point to the Fargate Service
• AWS RDS Instance that is stored in a separate network from the Application and does not service traffic directly from the internet

To do this, we are going to split the infrastructure into two AWS VPCs. One VPC will be used for the application based resources (e.g Fargate Service, ALB) and the other VPC will be for the database resources. The VPCs will be peered to allow communication between them so that the application can communicate with the database securely.

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