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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Azure Functions is a managed service for serverless applications in the Azure cloud. More broadly, Azure Functions is a runtime with multiple hosting possibilities. KEDA (Kubernetes-based Event-Driven Autoscaling) is an emerging option to host this runtime in Kubernetes.

In the first part of this post, I compare KEDA with cloud-based scaling and outline the required components. In the second part, I define infrastructure as code to deploy a sample KEDA application to an Azure Kubernetes Service (AKS) cluster.

The result is a fully working example and a high-level idea of how it works. Kubernetes expertise is not required!

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We recently partnered with DigitalOcean to publish a new tutorial, How to Manage DigitalOcean and Kubernetes Infrastructure with Pulumi. This short tutorial walks you through provisioning a new DigitalOcean Kubernetes cluster, deploying an application to it, and then assigninging a stable domain name to your application’s load balancer — all in a handful of lines of infrastructure as code.

By using infrastructure as code to provision and update your infrastructure, it’s easy to create new environments, modify or scale existing ones, or automate your deployments using continuous delivery. This approach also ensures that deployments are reliable and repeatable, and can even standardize how you deploy code to different cloud providers, including DigitalOcean, AWS, Azure, GCP, and others.

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