When building with Kubernetes for the first time, we often need to stand up a lot of infrastructure just to get to the point of having a base to build an application. Let’s explore how we can wire together two of our architecture templates to generate a base for a web application running on Kubernetes on Google Cloud with Python and Poetry.
🚀 Deploying cloud infrastructure is hard. Getting the architecture right from the start can be time-consuming. What if you could skip the hassle and start with prebuilt, best-practice templates?
📢 Pulumi Architecture Templates let you scaffold cloud infrastructure instantly with a single command. Whether you’re launching a serverless app on AWS, a container service on GCP, or a Kubernetes cluster on Azure, Pulumi gives you ready-to-use templates to get started faster.
➡️ Let’s dive in and see how these templates simplify cloud deployments.
When you’re working with infrastructure, you’re inevitably going to need to upgrade or update that infrastructure. Whether it’s an operating system update or a desire to get CPU or memory upgrades, you will need the ability to pick resources and change them as necessary. In the past, this kind of upgrade would be done on the basis of individual resources, with each one being updated and checked either by hand or programmatically before moving onto the next resource. If you’ve ever done a database migration or if you ever did the recommended way of upgrading your computer’s operating system including all of the backup steps, you’re familiar with this process. Stand up the new resource. Check everything works. Move over the data. Check again. Tear down the old infrastructure. In a cloud computing environment, though, you’re often dealing with hundreds or thousands of resources, and doing one-by-one replacement is a nightmare that takes ages. However, there are other options, many borrowed from the application deployment world, that we have available to us because we write infrastructure as code.
As a reader of this blog, you’ve probably heard of the Pulumi Service, the default state-management backend of the Pulumi CLI, and if that’s the case, there’s a good chance you’ve also heard of many of its key features. But did you know we’re adding new features to the Service all the time—some of which are incredibly easy to miss? In this post, we’ll highlight a few of those lesser-known features that we think make it even easier to manage your infrastructure with Pulumi.
Pulumi’s hackathon tradition continued in the last weeks of 2021 with our 2021 December hackathon. For one solid week, we had teams from across the company focus on improvements across the Pulumi ecosystem, and we brought in people from outside the engineering org to get perspectives on different needs. While there were some projects that were focused on internal work, there were still quite a few open-source projects that we can talk about publicly. We’ll get more details from some of those teams over a few more posts. In this post, however, we’re going to explore a bit about how we worked.
It’s the end of the 2021 calendar year here at Pulumi, and like everyone, we’re counting down until 2022 while looking back at our year. We’ve had a very exciting year! In case you missed anything from our past year, here’s a rundown of the top stories from Pulumi:
Pulumi became SOC2 certified in early January 2021.
We brought support for all four official Pulumi languages to EKS.
We released Python support for our powerful Automation API.
Let’s talk about state, shall we? State is the collective properties of the system from one point in time. Think of it effectively as a snapshot of a system. State in computer science is actually a lot like state in physics, so let’s start with something that’s a bit easier to understand.
Cloud Engineering Summit 2021 is almost here! We’ve got a great line up this year.
Our tracks are built around the three pillars of cloud engineering: Build, Deploy, and Manage. I’m your track chair for the Deploy track, the track focused on automating and managing infrastructure. Deploy is all about unifying systems so everything in a cloud-based system is shipped together from the same automated, auditable process, reducing human error and improving quality across the board. That could mean focusing on automated testing and linting of infrastructure as code, providing shared services platforms for others to use in their pipelines, or exploring how unified and automated infrastructure changes engineering culture in an organization.
In no particular order, let’s go explore the Deploy track lineup.
