Programming Tutorials

  The most insidious bugs in Go microservices aren't the ones that cause immediate panics; they are the ones that silently degrade performance over weeks. You see a steady sawtooth pattern in your memory usage dashboard. Eventually, the baseline memory consumption exceeds the container limit, the OOM (Out of Memory) killer wakes up, and your pod restarts. This is the classic signature of a  Goroutine Leak . Unlike languages with managed thread pools, Go allows you to spawn lightweight threads cheaply. However, the Go runtime does not automatically garbage collect a goroutine just because it is no longer doing useful work. If a goroutine is blocked and cannot proceed, it will exist forever, holding onto its stack memory (starting at 2KB but often growing) and heap references. This guide provides a rigorous approach to identifying the root cause of these leaks, fixing them using Context cancellation patterns, and preventing regression using automated testing. The Root Cause: Why...

  For over a decade, Go developers have abused channels. Lacking a standard iterator interface, we turned to buffered channels and goroutines to implement generator patterns. We treated   chan T   as an   Iterator<T> , spawning goroutines just to iterate over paginated API responses, file lines, or database rows. While syntactically elegant, this pattern is a performance trap. With the release of Go 1.23 and the standardization of the  iter  package (via the "range over func" experiment becoming standard), we can finally stop using concurrency primitives for sequential logic. The Root Cause: The Hidden Cost of Channel Iteration Using channels for simple iteration introduces unnecessary  scheduler overhead  and  memory contention . When you spawn a goroutine to feed a channel solely for iteration (the Producer-Consumer pattern applied to sequential data), you incur the following costs: Context Switching:  Every time the channel buff...