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.

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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.

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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.

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In a previous blog post, I shared how easy it is to create a globally distributed, highly-available, low-latency application with Azure Functions, Azure Cosmos DB, and Pulumi.

Today, I want to show how the same approach can be generalized for any cloud compute service, including containers, virtual machines, and serverless functions.

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It’s been a few years since Google shut down Google Reader, and while a number of nice commercial alternatives have sprung in its wake, none of them has ever been quite the right fit for me personally.

So a while back, after far too much time spent wandering the blogsphere manually, typing URLs into address bars by hand, I decided to go looking to see whether the universe had produced an open-source solution to this problem — and to my surprise and delight, it had! Miniflux is an excellent little open-source RSS server and reader, written in Go and backed by PostgreSQL, that also happens to be packaged as a Docker container. So in this post, I’ll show how easy it is to deploy a Miniflux server of your own on AWS, using only Pulumi and a few lines of TypeScript.

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“What’s in a name? That which we call a rose by any other name would smell as sweet.” William Shakespeare’s oft repeated quote was used to help Juliet explain that a “Montague” is worthy of love. Juliet may have underestimated the importance of a name, however, since things didn’t work out so well for everyone in Verona! Many customers have questions about “names” in Pulumi – and in an effort to make sure that things work out better for them than they did for Romeo, here’s a quick note on naming!

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Today we are excited to announce the general availability of Pulumi 1.0. Pulumi is a modern infrastructure as code tool that lets you declare infrastructure using real languages, with a SaaS management console for configuring identities, organizations, and related policies. By using real languages, developers and operators are able to work better together, sharing and reusing best practices, accomplishing new levels of automation, and unlocking access to ecosystems of existing tools.

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In this post, we’ll take a look at 10 “pearls”—bite-sized code snippets—that demonstrate using Pulumi to build serverless applications with Azure Functions and infrastructure as code. These pearls are organized into four categories, each demonstrating a unique scenario:

• Function App Deployment: Deploy an existing Azure Functions application using infrastructure as code.
• HTTP Functions as Callbacks: Mix JavaScript or TypeScript functions with your infrastructure definition to produce strongly-typed, self-contained, serverless HTTP endpoints.
• Cloud Event Handling: Leverage a variety of event sources available to Azure Functions with lightweight event handlers.
• Data Flows with Function Bindings: Take advantage of function bindings—declarative connectors to Azure services.

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We are very excited to announce that we have partnered with GitHub to offer our users better protection for their Pulumi Access Tokens.

By default, Pulumi users manage the state of their cloud infrastructure deployments using https://app.pulumi.com. This service provides state storage, concurrency control, audit history and access controls for both individuals and teams working with Pulumi. Each user and service account can generate one or more Pulumi Access Tokens to be used to authenticate with this service. These access tokens can be used on both local development machines, as well as in CI/CD systems for automated infrastructure deployments. These access tokens are sensitive secrets which should never be shared publicly, and in particular should never be committed to source control.

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