And for all the discussions on the topic in the last 24h, the answer is: until a postmortem is published, we don’t actually know.
There are a lot of possible explanations for the observed events. Of course, one simple and very easy to believe explanation would be that the software quality processes and reliability engineering at CrowdStrike are simply below industry standards – if we’re going to be speculating for entertainment purposes, you can in fact imagine them to be as comically bad as you please, no one can stop you.
But as a general rule of thumb, I’d be leery of simple and easy to believe explanations. Of all the (non-CrowdStrike!) headline-making Internet infrastructure outages I’ve been personally privy to, and that were speculated about on such places as Reddit or Lemmy, not one of the commenter speculations came close to the actual, and often fantastically complex chain of events involved in the outage. (Which, for mysterious reasons, did not seem to keep the commenters from speaking with unwavering confidence.)
Regarding testing: testing buys you a certain necessary degree of confidence in the robustness of the software. But this degree of confidence will never be 100%, because in all sufficiently complex systems there will be unknown unknowns. Even if your test coverage is 100% – every single instruction of the code is exercised by at least one test – you can’t be certain that every test accurately models the production environments that the software will be encountering. Furthermore, even exercising every single instruction is not sufficient protection on its own: the code might for instance fail in rare circumstances not covered by the test’s inputs.
For these reasons, one common best practice is to assume that the software will sooner or later ship with an undetected fault, and to therefore only deploy updates – both of software and of configuration data – in a staggered manner. The process looks something like this: a small subset of endpoints are selected for the update, the update is left to run in these endpoints for a certain amount of time, and the selected endpoints’ metrics are then assessed for unexpected behavior. Then you repeat this process for a larger subset of endpoints, and so on until the update has been deployed globally. The early subsets are sometimes called “canary”, as in the expression “canary in a coal mine”.
Why such a staggered deployment did not appear to occur in the CrowdStrike outage is the unanswered question I’m most curious about. But, to give you an idea of the sort of stuff that may happen in general, here is a selection of plausible scenarios, some of which have been known to occur in the wild in some shape or form:
The update is considered low-risk (for instance, it’s a minor configuration change without any code change) and there’s an imperious reason to expedite the deployment, for instance if it addresses a zero-day vulnerability under active exploitation by adversaries.
The update activates a feature that an important customer wants now, the customer phoned a VP to express such, and the VP then asks the engineers, arbitrarily loudly, to expedite the deployment.
The staggered deployment did in fact occur, but the issue takes the form of what is colloquially called a time bomb, where it is only triggered later on by a change in the state of production environments, such as, typically, the passage of time. Time bomb issues are the nightmare of reliability engineers, and difficult to defend against. They are also, thankfully, fairly rare.
A chain of events resulting in a misconfiguration where all the endpoints, instead of only those selected as canaries, pull the update.
Reliabilty engineering not being up to industry standards.
Of course, not all of the above fit the currently known (or, really, believed-known) details of the CrowdStrike outage. It is, in fact, unlikely that the chain of events that resulted in the CrowdStrike outage will be found in a random comment on Reddit or Lemmy. But hopefully this sheds a small amount of light on your excellent question.