This is the fourth post in a series of blog posts focused on Zephyr Archaeotech Emporium—our fictional company—and their use of Pulumi to manage their online retail store. In the first three posts, you saw how Zephyr’s initial use of Pulumi changed as the company grew, and how the use of short-lived per-developer stacks helped Zephyr’s application development team meet the demands of a fast-growing company. This post is a complement to the earlier post on structuring Pulumi projects, discussing how Zephyr uses Stack References to link their projects together and sharing some IaC best practices around the use of Stack References.

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We’ve been hearing feedback from our customers that they need ways to manage permissions for their stacks at scale. Today we are announcing a --teams flag for pulumi stack init, which allows customers to assign Teams to stacks from the CLI. This flag offers a third programmatic method for assigning permissions, supplementing Pulumi Service REST API or the Pulumi Service Provider. Developers can now initialize their stacks with the right permissions directly from the CLI.

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Delivering software has been conventionally driven by CI/CD workflows. A single commit is merged into a codebase, and a small, and static set of workflow runs are triggered by the CI system to update the appropriate environments (Dev -> Staging -> Production). This may have been fine when the only product a company had to offer was a single stateless web service, but increasingly companies are called upon to deliver cloud infrastructure as a product.

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You can use the new StackReference.getOutputDetails method to get output values from other stacks directly—without calling Output.apply.

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We have been busy shipping improvements in the last 2 months. Let’s walk through the release highlights across Pulumi engineering areas from January and February. If you want to learn more between release blogs, follow the CLI improvements in the pulumi/pulumi repo changelog and Pulumi Service features in the new features blogs.

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At Pulumi we read every single error message that our API produces. This is the primary mechanism that led to a 17x YoY reduction in our error rate. You’re probably wondering how reading error messages make them go away.

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This is the third post in a series of blog posts focused on Zephyr Archaeotech Emporium—our fictional company—and their use of Pulumi to manage their online retail store. In the first post, you saw how Zephyr initially decided to go with a single Pulumi project for managing deployments of their online retail store application. In this post, you’ll see how Zephyr’s use of Pulumi changes as their company grows and evolves.

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Point and click in the console is great when you’re first starting out learning a new cloud or managed service, but it quickly becomes a hindrance when cloud infrastructure is widely adopted by an organization. The point at which the term “widely adopted” becomes applicable to your situation differs, but at some point in their careers, many infrastructure and platform engineers are faced with situations where a large number of critical infrastructure resources were created through “click ops” with no ability to track changes, reproduce environments consistently, and so on. When this happens (and it will probably happen to many of you), it’s time to import those resources into infrastructure as code.

Fortunately, Pulumi has one of the smoothest and most powerful import processes of any IaC tool. In this post, we’re going to show you how to automate the bulk importation of Google Cloud resources into Pulumi! This approach will also work on resources that were created by another IaC tool.

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In the first post about code organization and stacks, we introduced Zephyr, a fictional company that uses Pulumi to manage its online retail store. Following on from that post, which discusses code organization and stacks, this post explores two more questions users frequently ask when working with Pulumi in teams — namely, How can I best enable multiple developers to collaborate on a Pulumi project? And how can I use Git and Git branching to support this kind of collaboration? In this post, we’ll provide some guidance and best practices around these topics, using Zephyr and its online store as the use case.

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The Pulumi Docker Provider has been a top Pulumi provider since it launched in 2018. It can be used to provision any of the resources available in Docker, including containers, images, networks, volumes and more.

One of the most heavily used features of this provider is the docker.Image resource, which enables Pulumi users to build and (optionally) push a local Docker context (like an application folder) to a registry as part of a Pulumi deployment. Today we are excited to announce a set of improvements to the docker.Image resource driven by the feedback we have received from our community. This set of improvements includes:

• Significantly improved performance (including reduced need for rebuilds)
• BuildKit support (including cross-platform builds)
• Rich Docker build logs inside Pulumi IaC program output
• Pulumi YAML and Pulumi Java support

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