This article is over two years old. Life moves quickly, and thus there is a good chance any references, recommendations, or opinions in this content are out of date. Make sure to verify any information independently.

Resiliency in SaaS codebases through productisation

Published 14 December 2020
Updated 20 January 2021

In the world of private codebases, and especially SaaS, you can easily fall into the trap of thinking, "well, it's OK because no one is going to see this." A mindset like that can wreck a codebase, and can fuel micro-decisions that lead to painful long-term mistakes.

First, regarding "productisation," Wiktionary defines it as

The act of modifying something, such as a concept or a tool internal to an organization, to make it suitable as a commercial product.

To put it another way, I find it very helpful to frame things from the perspective of "what if someone else had to run this software?" This is obviously something that open source projects have to think about quite a bit, so you could also frame it as "what if this was open source?"

There are many facets to this, but I want to dive into just two: reproducibility and portability. These concepts frequently come up in conversations around package managers and software releases, but they are also quite pertinent to SaaS.

Reproducibility: I should be able to run the thing.

A while back, I was charged with spinning up a validation environment for a SaaS product to provide a "safe" place for a QA team to mess around with upcoming features. The goal was to have this sit somewhere in between our "staging" environment, which was often quite buggy and more for internal developers, and production, which we needed to keep as stable as possible for customers.

"Simple enough." I said. Surely, we already have a couple other environments, we can just add one more! The problem was that no one had spun up a new environment for several years, and everyone involved in doing so had long since left the company.

In the end, the new "QA" environment never fully worked. It mostly worked, but several components would fail to integrate or would mysteriously break in ways no one really understood. We tried to copy production as close as we could, and still we failed to replicate it.

This is what I mean by reproducibility: anyone should be able to run the software you make. A production environment shouldn't be an elusive, one-off occurence; you should be able to recreate production, and the steps should be obvious.

This naturally leads into discussions about "DevOps" and "Infrastructure as Code," both of which are definitely a key part of the solution to this. Being able to understand and replicate infrastructure based on playbooks or manifests solves a huge part of the problem. But it's not the whole story.

Even with a fully-automated cloud, there will always be some manual work, keys to rotate, service integrations to set up, etc. These service dependencies have to be documented and fail safely.

In a SaaS world, it's incredibly easy to add a new service dependency--for this case, let's use a hypothetical geocoding API--add the keys to production, and never think about it again. By applying a product focus, it becomes clearer that this dependency should be optional, should be documented, and should fail gracefully.

These sorts of third-party dependencies hold their own configuration, and often that configuration is difficult to export or automate. Do certain options need to be enabled for your application? Do certain addons need to be active? These are all questions that should have documented and discoverable answers -- in code or otherwise.

Additionally, external service dependencies should be resilient against missing configuration. Configuration should be validated and warnings should exist; and if a service is not critical to the operation of the application, it shouldn't block the rest of the app just because it's unconfigured.

This level of "configuration resiliency" helps during development, as devs don't need to get 1000 test API keys just to boot a console; and, additionally, helps you build better software overall. By baking in resiliency, you make your app more flexible in the face of failure, where you know that you can disable many parts of it and it won't break the entire experience.

In essence, you should be the downstream and the upstream; you should both develop the software, but also treat yourself as a consumer of it. Don't take shortcuts to production just because you own the whole pipeline.

This makes it easier to deploy multiple versions of your service -- whether that means on-premises for a large enterprise customer, or in a different geographic region for compliance purposes. Ensuring your codebase is resilient and reproducible could be a business-value feature!

Portability: hedge against your integrations.

Being able to replicate, say, a bunch of AWS service configuration is powerful, but it still leaves you tightly-coupled to AWS. That doesn't help much if we want to replicate production in an on-premises environment, or even locally on a laptop.

Just as building software to be resilient against missing or invalid dependencies, it can be even more advantageous to take it a step further, and make your software resilient across vendors.

This is not a new concept; really, all this means is build the right abstractions. Don't leak third-party libraries around your codebase, and build your interfaces with interchangeable backend implementations.

For example, integrating object storage is a very common thing to sprinkle across your codebase. Building a proper entrypoint and abstraction around it will allow you to swap out the backing implementation without having to modify your application.

In the object storage example, something like Rails' ActiveStorage is a great example of this abstraction. Depending on the environment and requirements, you can swap out backing storage, be it on-disk, to cloud, etc. Your code calls a standard API, and doesn't need to change to support a variety of implementations.

These sort of abstractions can facilitate portability, allowing you to run your service almost anywhere, with any technology you can build an implementation for. Does an enterprise customer need to store file uploads on a SAN instead of object storage? Is AWS down and you need to migrate production workloads to a DR site on a different provider? All of this can be yours, for the low-low price of strong abstractions.

However, as with everything, you need to ensure you don't go too far; you must weigh your dependencies versus any downsides of abstraction.

For example, heavy abstractions on top of a database (such as PostgreSQL) can add more trouble than they're worth, and have performance impacts compared to a more optimized, direct implementation. For these, the focus should shift from abstractions, to choosing the right APIs for your application.

Portability, the sequel: standards are good, actually

For cases where making your own standard interface for dependencies is not worth it or not possible, using standardized APIs is the next best thing.

Take the aforementioned database example; there can be great benefits in performance to optimise your usage of a database to take advantage of a specific implementation. What matters in this case is the technology you choose.

You can still achieve portability and resiliency through non-abstracted choices, as long as those choices are either open or standardized. In the database example, you can spin up a PostgreSQL server anywhere, even on your own hardware. There isn't much that is stopping you from moving providers or running in other environments.

For an opposite example: Google Spanner on GCP, or AWS's DynamoDB. While both are very powerful technologies, they are unique to their respective clouds and use non-standard APIs. You cannot move to another cloud without significantly changing your application.

To be clear, this isn't a dig on "the cloud" -- this is a dig on vendor lock-in. Where Google's Spanner invented their own interface, Microsoft Azure's CosmosDB gives the consumer the option of various different standard APIs, including SQL- or MongoDB-compatible endpoints. This is a great win by combining a standard API (one that means a developer can run a different MongoDB-like service locally) with the power of an integrated and globally-scalable cloud solution in production.

Productisation doesn't mean open source

While I think it helps with the thought process to ask "what if this was open source?", that doesn't mean you have to become open source to get the benefits of that mindset. In my experience, just being aware of the codebase you are building, and keeping future generations in mind, is enough to hopefully put you on the right paths.

Hopefully product-focused thinking can help you clean up your codebases as well.