A Minimal Go Loop Reveals How CPUs, Threads, and Memory Really Work

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A developer running a near-empty infinite loop in Go observed surprising system activity — 100% CPU usage, 5 threads, 22,000 context switches, and over 400 GB of virtual memory — despite writing almost no code. The CPU spikes because the loop never blocks or sleeps, keeping the goroutine perpetually runnable and the processor constantly busy. The 5 OS threads were not created explicitly in the source code; they are part of the Go runtime's internal machinery, which manages goroutines, scheduling, memory, and garbage collection automatically. Above the Go runtime sits the OS scheduler, which arbitrates CPU access among all threads from every running process, causing the thousands of context switches observed. The experiment illustrates that a Go program is far more than its source code — the runtime and OS together handle the low-level work that developers never have to write themselves.

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Understanding What Databases Actually Do Under the Hood

A developer reflecting on system design realized they lacked a foundational understanding of how databases work internally, beyond just writing SQL queries. The article explores how databases handle large-scale data retrieval, explaining why full table scans become impractical at millions of rows. Indexes, such as those on a user_id column, allow databases like PostgreSQL to locate relevant rows efficiently without scanning entire tables. The piece also distinguishes between index types — including B-trees, Hash indexes, and LSM Trees — noting each suits different read and write workloads. The author concludes that a system designer's role is not to implement these structures manually, but to understand access patterns well enough to choose the right database features.

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

How to test n8n webhook workflows locally without triggering live APIs

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