Microservices have become the go-to approach for building systems that need to scale efficiently and stay resilient under pressure. However, a microservices architecture comes with many potential points of failure—dozens or even hundreds of distributed components communicating over a network. To ensure your code makes it all the way to the customer without hiccups, you need to design for failure from the start. This is where fault tolerance and observability come in. By embracing Site Reliability Engineering (SRE) practices, developers can build microservices that not only survive failures but automatically detect and recover from them.
In this article, we’ll explore how to build fault-tolerant backend microservices on Kubernetes, integrating resilience patterns (retries, timeouts, circuit breakers, bulkheads, rate limiting, etc.) with robust observability, monitoring, and alerting. We’ll also compare these resilience strategies and provide practical examples—from Kubernetes health probes to alerting rules—to illustrate how to keep services reliable from code to customer.