An opinionated list of Python frameworks, libraries, tools, and resources
It was 2:47 AM when the alerts started. A seemingly straightforward database migration had triggered a cascading failure across three downstream services, and our payment processing pipeline was dropping roughly 12% of transactions. The on-call engineer didn't need to wake anyone, locate a rollback script, or wait for a CI pipeline to churn through another deploy. She opened the LaunchDarkly dashb
If you’ve been around data engineering long enough, you’ve probably heard these terms thrown around in meetings: “Just dump it in the data lake” “We’ll expose it through the warehouse” “That goes into the mart” “We’re moving to a lakehouse architecture” And honestly… it can sound like four different ways of saying the same thing. They’re not. Each one solves a slightly different problem in the dat