For years, we knew how to test software. A method receives an input. It produces an output. We write a test. For a traditional service, that model works remarkably well. We test business rules. We test APIs. We test database…
For a long time, one region was enough. The application ran there. The database ran there. The message infrastructure ran there. Backups existed. Monitoring was in place. We had redundancy inside the region. From an infrastructure perspective, the system looked…
The application was healthy. CPU was normal. Memory was stable. The database was performing well. Internal services were responding within their expected latency. And yet one part of the system was getting slower. Payment requests. At first, we looked at…
The monolith had become difficult to work with. Deployments were getting larger. Teams were stepping on each other. Some parts of the system needed to scale independently. A small change in one area could require deploying the entire application. The…
It was 2AM. Most of the engineering team was asleep. The payment system was processing transactions normally. Then an alert fired. Duplicate charges were increasing. Not thousands. Not enough to immediately bring the entire system down. But enough to tell…
The system was slow. But the dashboards looked healthy. We had CPU utilization under 50%. Memory was stable. Error rates were below 1%. Our monitoring alerts weren’t triggering. And yet customers were complaining about slowness. This was the contradiction we…
