Microservices: a Perfect Paradox
Viewer Discretion Advised: Microservices-rated! When I worked on Spring Boot microservices, I remember my focus was all about error and exception handling, polishing the code quality, and improving performance to reduce the traffic time between API calls. You know, the usual grind. But then came the microservice interviews. Oh boy, did I get hit with a wave of questions on every microservice detail imaginable.
Guess what I did learn from my interviews? As usual, I always learned something from my interviews, but unfortunately, just not the technical ones I was hoping for 😅
I just found a Perfect Paradox.
It’s like the “Less is more” mantra in action. Microservices aim to make things simple by breaking down applications into small, manageable pieces (as the name says). But here’s the kicker: it also ramps up complexity everywhere else.
Suddenly, you’re knee-deep in error handling, latency issues, resilience checks, scalability puzzles—the list just keeps growing. For a developer, this means more on managing performance, retries, data consistency, exceptions, and yes, I forgot to mention about this: way more deployments than you ever bargained for.
With microservices, it’s like swapping one big problem for a hundred smaller ones. Congratulations, now we break down a whole ecosystem into “manageable” headaches!
Sure, those smaller issues come with neat APIs and catchy names like "Service Discovery" and "Circuit Breaker," Oh, let alone another fancy name, "Saga", but they also bring along their best buddies: "Retry Logic" and "Data Consistency Crisis." So, in a way, microservices turn you into a kind of digital juggler—except the balls are on fire, and they all have opinions on load balancing.