On August 28th, 2023—right in the middle of a UK public holiday—an issue with the UK’s air traffic control systems caused chaos across the country. The culprit? An entirely valid flight plan that hit an edge case in the processing software, partly because it contained a pair of duplicate airport codes.

Picture this: your alerting system needs to tell you it's broken. Sounds like a paradox, right? Yet that’s exactly the situation we face as an incident management company. We believe strongly in using our own products - after all, if we don’t trust ourselves to be there when it matters most, why should the thousands of engineers who rely on us every day? However, this poses an obvious challenge.

At incident.io, we run on a monolith. This brings a whole load of benefits that we don’t want to give up any time soon. We don’t have to worry about the speed of internal network requests, complex deployments, or optimizing work that touches multiple services. This blog post isn’t about the relative benefits of monoliths though (but we’ve written more about that here if you are interested)! Ownership in monoliths is tricky.

As a provider of incident management software, we at incident.io manage sensitive data regarding our customers. This includes Personally Identifiable Information (PII) about their employees, such as emails, first names, and last names, as well as confidential details regarding customer incidents, such as names and summaries. Consequently, we approach the management of this data with a great deal of care.

We've written several times about our data stack here incident, but never about our underlying data warehouse and the design principles behind it. This blog post will run through the high-level structure of our data warehouse and then will go in-depth into the underlying layers.