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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How do I speed up Docker image builds with Pulumi? Use BuildKit (the default since Docker 23), enable a registry or layer cache so repeated builds reuse work, write a multi-stage Dockerfile so production images skip build-time dependencies, and reach for the dedicated Docker Build provider when you need buildx features like multi-platform images, build secrets, or Docker Build Cloud. With these techniques together, repeat builds in a Pulumi program commonly drop from minutes to seconds.

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Today is International Women’s Day, and this year the theme is #EmbraceEquity - which means creating an equitable environment. An equitable work environment means understanding that everyone, regardless of gender, religion, ethnicity, background, or resources, brings strength to the workforce and that opportunities should be given to them based on their individual needs.

For Pulumi, it means a work environment where everyone can share ideas and respect them even when disagreeing. Women’s experiences - as well as men’s and nonbinary’s experiences - inform the direction of digital technology and innovation.

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This is the first in a series of blog posts that explores how a fictional company—Zephyr Archaeotech Emporium—uses Pulumi to manage their online retail store. This post explores a couple of common questions that users ask when working with Pulumi; specifically, where should I store my Pulumi code? And how do I support multiple environments with Pulumi? This post will provide some guidance and Infrastructure as Code best practices around these topics, using Zephyr and their online store as the use case.

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Event streaming is used across diverse industries that demand real-time data processing. Apache Kafka is the most popular open-source streaming platform. Confluent Cloud lets you run Kafka on the cloud provider of your choice.

In this blog post, you’ll use the Confluent Cloud Pulumi provider and Pulumi to create a Kafka cluster, topic, and customer account.

1. About Apache Kafka and Confluent Cloud
2. Initializing the Project
3. Adding Resources
4. Testing Kafka Cluster
5. See it in action
6. Conclusion
7. Additional Resources

About Apache Kafka and Confluent Cloud

What is Apache Kafka?

Apache Kafka is an event store and stream-processing platform, used by more than 30% of the Fortune 500 today. Using Kafka streams, developers can write modern, event-driven applications for real-time data streaming and processing. Kafka is used across many industries, including gaming, financial services, healthcare, retail, automotive, and manufacturing.

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What is FinOps?

The FinOps Foundation eloquently defines FinOps as “an evolving cloud financial management discipline and cultural practice that enables organizations to get maximum business value by helping engineering, finance, technology and business teams to collaborate on data-driven spending decisions.” Simply put, FinOps is the continuous effort to control cloud spend.

Just as organizations have adopted operations-focused best practices into software development cycles and have considered how to best insert security best practices along the way, financial best practices may also be codified by developers writing cloud programs.

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In an enterprise organization, an IT self-service “vending machine” allows employees to quickly and easily request and receive access to pre-approved cloud resources. Behind the scenes, Pulumi programs may orchestrate any of the requisite resources. We will look at an example of using Pulumi to create an AWS child account, within an AWS Organization.

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