What do you work on, anyway?

I often struggle to describe the project that I work on at my day job, even though it’s an open-source project that even has its own domain name: managed.delivery. I’ll often mumble something like, “it’s a declarative deployment system”. But that explanation does not yield much insight.

I’m going to use Kubernetes as an analogy to explain my understanding of Managed Delivery. This is dangerous, because I’m not a Kubernetes user(!). But if I didn’t want to live dangerously, I wouldn’t blog.

With Kubernetes, you describe the desired state of your resources declaratively, and then the system takes action to bring the current state of the system to the desired state. In particular, when you use Kubernetes to launch a pod of containers, you need to specify the container image name and version to be deployed as part of the desired state.

When a developer pushes new code out, they need to change the desired state of a resource, specifically, the container image version. This means that a deployment system needs some mechanism for changing the desired state.

A common pattern we see is that service owners have a notion of an environment (e.g., test, staging, prod). For example, maybe they’ll deploy the code to test, and maybe run some automated tests against it, and if it looks good, they’ll promote to staging, and maybe they’ll do some manual tests, and if they’re happy, they’ll promote out to prod.

Example of deployment environments

Imagine test, staging, and prod all have version v23 of the code running in it. After version v24 is cut, it will first be deployed in test, then staging, then prod. That’s how each version will propagate through these environments, assuming it meets the promotion constraints for each environment (e.g., tests pass, human makes a judgment).

You can think of this kind of promoting-code-versions-through-environments as a pattern for describing how the desired states of the environments changes over time. And you can describe this pattern declaratively, rather than imperatively like you would with traditional pipelines.

And that’s what Managed Delivery is. It’s a way of declaratively describing how the desired state of the resources should evolve over time. To use a calculus analogy, you can think of Managed Delivery as representing the time-derivative of the desired state function.

If you think of Kubernetes as a system for specifying desired state, Managed Delivery is a system for specifying how desired state evolves over time

With Managed Delivery, you can say express concepts like:

  • for a code version to be promoted to the staging environment, it must
    • be successfully deployed to the test environment
    • pass a suite of end-to-end automated tests specified by the app owner

and then Managed Delivery uses these environment promotion specifications to shepherd the code through the environments.

And that’s it. Managed Delivery is a system that lets users describe how the desired state changes over time, by letting them specify environments and the rules for promoting change from one from environment to the next.

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