Posts Tagged kubernetes

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.

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Last month, we announced .NET support for Pulumi, including support for AWS, Azure, GCP, and many other clouds. One of the biggest questions we heard was about Kubernetes — “can I use Pulumi to manage Kubernetes infrastructure in C#, F#, and VB.NET as I can already in TypeScript and Python today?” With last week’s release of Pulumi.Kubernetes on NuGet, you can now also deploy Kubernetes infrastructure using your favorite .NET languages.

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AWS Elastic Kubernetes Service (EKS) provides a range of performance and control for dynamically scaling your Kubernetes clusters, including Managed Node Groups, Fargate, and Manually-Managed Node Groups in EC2. In this post, we’ll see how to use each of these compute options, and when to prefer one over the other in order to maximize productivity, flexibility, and control, based on your needs.

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A big part of our vision with Pulumi is to bring application developers and infrastructure teams closer together in the cloud. That includes both providing infrastructure teams with better software engineering tools, as well as providing developers with easier access to cloud infrastructure. We are often inspired by looking at great software engineering experiences in other development stacks and applying them to the cloud infrastructure space. Whether it be general-purpose languages and rich IDEs, testing and package management, or components and rich APIs, at Pulumi, we’ve repeatedly applied successful development tools and practices to the challenges of building and scaling modern cloud infrastructure.

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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.

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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. Kubernetes is Vast and Complex Kubernetes is the standard multi-cloud platform for modern containerized applications.

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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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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.

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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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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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