The Amazon Elastic File System Container Storage Interface (CSI) Driver implements the CSI specification for container orchestrators to manage the lifecycle of Amazon EFS filesystems. The CSI specification defines an interface along with the minimum operational and packaging recommendations for a storage provider to implement a CSI compatible plugin. The interface declares the RPCs that a plugin must expose. The CSI drivers are the right mechanism to work with, when using a cloud storage component with Kubernetes workloads.

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Testing your infrastructure using familiar tools like Node.js’s Mocha framework allows you to ensure configuration is correct before provisioning, and that the resulting infrastructure has certain desirable properties afterwards. This can enforce team standards, ensure security guidelines are being followed, and so much more. Because Pulumi uses general purpose languages, you can just embed tests alongside your infrastructure-as-code definitions themselves, using a familiar authoring style and reporting experience. In this post, we’ll explore the ins and outs of unit testing your infrastructure.

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Kubernetes Ingress is an API object that allows you manage external (or) internal HTTP[s] access to Kubernetes services running in a cluster. Amazon Elastic Load Balancing Application Load Balancer (ALB) is a popular AWS service that load balances incoming traffic at the application layer across multiple targets, such as Amazon EC2 instances, in a region. ALB supports multiple features including host or path based routing, TLS (Transport layer security) termination, WebSockets, HTTP/2, AWS WAF (web application firewall) integration, integrated access logs, and health checks.

The AWS ALB Ingress controller is a Kubernetes SIG-AWS subproject - it was the second sub-project added to SIG-AWS after the aws-authenticator subproject. The ALB Ingress controller triggers the creation of an ALB and the necessary supporting AWS resources whenever a Kubernetes user declares an Ingress resource on the cluster. TargetGroups are created for each backend specified in the Ingress resource. Listeners are created for every port specified as Ingress resource annotation. When no port is specified, sensible defaults (80 or 443) are used. Rules are created for each path specified in your ingress resource. This ensures that traffic to a specific path is routed to the correct TargetGroup.

In this post, we will work through a simple example of running ALB based Kubernetes Ingresses with Pulumi EKS, AWS, and AWSX packages.

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Pulumi is excellent at connecting multiple cloud components into a cohesive application. In my previous post, I introduced the way to mix JavaScript or TypeScript serverless functions directly into the cloud infrastructure programs.

Today, I will build a serverless application with both the data store and the HTTP endpoint located close to end users to ensure prompt response time. The entire application runs on top of managed Azure services and is defined as a single Pulumi program in TypeScript.

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Static websites are back in the mainstream these days. Website generators like Jekyll, Hugo, or Gatsby, make it fairly easy to combine templates and markdown pages to produce static HTML files. Static assets are the simplest thing to serve and cache, so the whole setup ends up being fast and cost-efficient.

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Amazon offers multiple solutions for running containers in AWS, through its managed Elastic Container Service (ECS). This includes three major approaches: ECS managed automatically with Fargate, ECS backed by EC2 instances, and Elastic Kubernetes Service (EKS), delivering the full power of Kubernetes. It’s not always easy to choose between these, so in this article we provide some basic guidance on the tradeoffs you’ll encounter when choosing.

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One year ago today – on June 18, 2018 – we open sourced Pulumi, a new approach to multi-cloud infrastructure as code using your favorite languages. And what a year it has been!

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Amazon Elastic Container Registry (ECR) is a fully-managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images. ECR is integrated with Amazon Elastic Container Service (ECS), including for Kubernetes (EKS), simplifying your development to production workflow, securing access through IAM, and eliminating the need to operate your own container repositories or worry about scaling the underlying infrastructure. ECR hosts your images in a highly available and scalable architecture, allowing you to reliably deploy containers for your applications. In this article, we’ll see how Pulumi Crosswalk for AWS lets you use infrastructure as code to easily build, publish, and pull from private ECR repositories.

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Pulumi Crosswalk for AWS modules can be used to get first class insights and visualizations directly inside your Pulumi application.

As cloud applications tend to be long-lived, we think it’s vital that it be possible to get regular insights on the performance of the application at all times. Using Crosswalk for AWS Pulumi applications allow you to easily define and visualize the appropriate metrics that show the health of your services, create alarms to let you know when something is wrong, and easily create dashboards to get live visualization of what is happening in the cloud. Because this is vital to the health of the application, we think this should be something built in from the start, and not something added after the fact as an out of band artifact.

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Guest Author: Chris Toomey, Solution Architect Lead @ Mapbox

With 8 billion+ connected IoT devices and 2 billion GPS-equipped smartphones already online, logistics businesses are tracking assets at every step in the supply chain. At this scale and complexity, it is imperative to have a flexible way to ingest, process, and act upon this data, without sacrificing security or best practices.

To meet this need, Mapbox has created an Asset Tracking Solution that uses Pulumi’s open source JavaScript libraries (AWS, AWSX) available with multi-language support with Pulumi Crosswalk for AWS. Pulumi Crosswalk for AWS is an open source framework that streamlines creation, deployment and management of AWS services with built-in AWS Best Practices and minimal lines of code in common programming languages.

In this blog, we will show snippets of the Javascript code that embraces the power of Pulumi to program AWS service APIs to create the Mapbox solution. To see the full architecture in action with a live bike race across America, please refer to this webinar recorded on June 13th 2019 and the Mapbox whitepaper. Also refer to this blog of the Race across America showcased live during the webinar tomorrow.

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