When a program runs in production, you cannot step through it in a debugger, so you need other ways to understand what it is doing and why it misbehaves. Logging is the first: writing structured, leveled messages about a program's execution to a destination, so you have a record of what happened. Done well, logs are the primary tool for diagnosing issues in running systems, and done badly they are noise or, worse, a performance and security liability.
When a problem is about performance rather than correctness, profiling is the tool: measuring where a program actually spends its time and memory, so you optimise based on evidence rather than guesswork. And during development, when you need to inspect a program's state precisely, a debugger lets you pause execution, step through code, and examine variables. Together, logging, profiling, and debugging are the three pillars of understanding and fixing program behaviour.
Understanding these matters because writing code is only half the job; the other half is operating and fixing it, and that depends entirely on observability. Knowing how to log usefully (with levels, structure, and the right facade), how to profile to find real bottlenecks instead of imagined ones, and how to debug methodically is what turns a baffling production incident or a mysterious slowdown into a tractable problem, a skill set as essential as the coding itself.