Building a Reliable ETL System with Go and Temporal: When Data Needs to Move Like a Marvel Superhero 🦸♂️
Ever tried moving your entire apartment through a drinking straw? That’s basically what building ETL (Extract, Transform, Load) systems feels like sometimes. You’ve got terabytes of data that need to go from Point A to Point B, transform from one shape to another along the way, and arrive without losing a single byte. Oh, and it needs to happen yesterday.
As a backend engineer who’s battled these challenges at scale, I’ve learned that building reliable ETL systems is less about writing perfect code (though that helps) and more about preparing for everything that could possibly go wrong. Because trust me, Murphy’s Law isn’t just a suggestion when it comes to data pipelines – it’s more like a promise.
Your Legacy System is Trying to Tell You Something (And It's Not 'Please Reboot')
You know that uneasy feeling when your car makes a noise it’s definitely not supposed to make? That moment when you turn down the radio, tilt your head, and think, “Maybe if I ignore it, it’ll go away”? Well, your legacy system is making those noises right now, and trust me – it won’t go away by itself.
I’ve spent the last 15 years listening to legacy systems whisper (and sometimes scream) their stories. Like that time at a startup when their core transaction system started hiccuping every Tuesday at 3 PM. Nobody knew why Tuesdays – the system had apparently developed a case of mid-week existential crisis. Turns out, it was trying to tell us something important: “Your transaction log is full, and I’ve been tap dancing on the edge of disaster for the past three months.”