How I Design Reliable Backend Systems

I've been building backend systems for about five years now. Some handle 10,000+ messages per day. Others serve AI-powered responses in real-time. A few run on a single VPS for under $5/month. Over that time, I've settled on a set of principles that keep my systems predictable and boring in production. Boring is the goal. This post covers the patterns I return to on every project. Start With the Failure Modes Most backend design starts with the happy path. I start with a different question: what breaks first? On my Message Scheduler project, the answer was clear early on. External APIs fail. Amazon SES returns transient errors. Telegram's Bot API has rate limits. If a scheduled message fails at delivery time, the user never gets it. So the first architectural decision wasn't about the framework or database. It was about retry behaviour. I went with exponential backoff — 3 attempts over 15 minutes — before marking a message as failed. That single decision drove the rest of the stack: Ce