Luke Hoban

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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Most cloud infrastructure projects involve working with existing cloud resources — either building on top of existing resources or adopting existing resources under management with a new and more robust infrastructure provisioning solution.

Whether you are adopting resources that were deployed manually using your cloud provider’s console or CLI — or migrating existing infrastructure from tools like Terraform or CloudFormation — Pulumi makes it easy to adopt and manage your existing resources.

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Amazon Web Services provides an incredible platform for developers to build cloud-native applications, and is used by millions of customers of all sizes. The building block services that AWS offers enable teams to offload undifferentiated heavy-lifting to AWS. To maximally benefit from these services though, cloud engineering teams must learn how to compose all of these building blocks together to build and deliver their own applications. Today, this is still too hard. Getting from your laptop to a production-ready AWS deployment frequently takes days or weeks instead of minutes or hours. And AWS building block services frequently leave you to re-implement (and re-discover) best-practices instead of providing these as smart defaults.

Pulumi Crosswalk for AWS is a new open source library of infrastructure-as-code components that make it easier to get from zero to production on AWS, easier to adopt AWS best practices by default, and easier to evolve your AWS infrastructure as your application needs mature.

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Google Cloud is one of the most exciting cloud platforms available today, with a breadth of powerful infrastructure services from Google Container Engine (GKE) and Google Cloud Functions to Cloud Firestore and Cloud Spanner.

Pulumi is the most productive tooling available today for teams building cloud applications and infrastructure, in your favorite languages. Add them together, and teams can easily take maximum advantage of Google Cloud Platform’s rich features, productively, with a combined platform that makes it easy to collaborate, share, and reuse.

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Pulumi makes developing and deploying rich serverless and container-based applications a breeze. But how do you monitor and observe those applications while they are being developed and once they are deployed? There are many great answers: from the built-in capabilities of the underlying cloud services (Lambda, ECS, Kubernetes, and more), to great 3rd party solutions like IOpipe and Epsagon which we highlighted recently on this blog.

The Pulumi CLI provides another way to do logging, without requiring the additional setup of these existing solutions and seamlessly integrated into your Pulumi development workflow. The pulumi logs command provides a great first place to start for understanding your Pulumi application’s behavior. Especially during development, this command provides direct insight into the behavior of your application, bringing together logs across all of the different forms of compute you are using - from code running in serverless functions to containers to VMs.

Let’s take a quick look at pulumi logs and some of the ways it can be used as part of the inner loop of your Pulumi development.

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Pulumi makes it incredibly easy to use serverless functions within your cloud infrastructure and applications - an AWS Lambda is as simple as writing a JavaScript lambda!

const bucket = new aws.s3.Bucket("my-bucket");
bucket.onObjectCreated("onNewObject", async (ev) => console.log(ev));

By making it so easy to introduce serverless functions into cloud infrastructure, Pulumi programs often incorporate many Lambdas, all wired together as part of a larger set of infrastructure and application code.

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Just over a month ago we publicly launched Pulumi, a new cloud native development platform.  The response has been overwhelming and we’ve been hard at work responding to your feedback ever since.

Today, we are excited to release Pulumi 0.15 and make it available to download.  This release includes improvements across the entire Pulumi development experience. Pulumi supports more platforms (Kubernetes and OpenStack, is faster (Parallelism, simpler (native TypeScript support), richer (serverless frameworks for Azure and Google Cloud),  and is more deeply integrated into the application lifecycle (GitHub App for CI/CD integration).

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Here at Pulumi we are (perhaps unsurprisingly!) huge fans of using Pulumi to manage our cloud infrastructure and services. We author our infrastructure in strongly-typed programming languages, which allows us to to benefit from rich tooling - documenting and factoring our infrastructure using the same software engineering practices we apply to our application code. This also allows us to create reusable abstractions which accelerate our ability to deliver new features and services, and our ability to standardize and refactor infrastructure patterns across our services with relative ease.

Like other users, we use Pulumi at a variety of levels of abstraction. We use Pulumi for raw infrastructure provisioning, defining the core networking layer for our AWS-based backend infrastructure. And we use Pulumi to define how our application services are deployed into ECS using just a few lines of code. Pulumi hosts and manages static content for www.pulumi.com and get.pulumi.com. We use Pulumi to define the CloudWatch dashboards connected to our infrastructure. And for monitoring, Pulumi defines metrics and notifications/alarms in PagerDuty and Slack.

Best of all, we’ve been able to take things we’ve learned from these use cases, and others we’ve worked with beta users on over the last few months (thank you!), and factor common patterns out into reusable libraries like @pulumi/aws-infra and @pulumi/cloud for ourselves and others to build upon.

In this post, we’ll do a deeper dive into each of these use cases, highlighting unique aspects of how we use Pulumi itself, and some of our engineering processes around how we integrate Pulumi into the rest of our toolchain.

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