Practice profiling tools vocabulary: Node.js CPU profiler, flame graphs, V8 profiler, py-spy for Python, async-profiler for JVM, and interpreting profiling output.
0 / 5 completed
1 / 5
'We ran the Node.js ___ profiler.' Which type of profiler measures execution time per function?
A CPU profiler (or sampling profiler) records which functions are executing over time, showing where the program spends CPU time. Node.js has a built-in CPU profiler accessible via --prof or Chrome DevTools.
2 / 5
'The ___ graph shows the hot path.' Which visualization is standard for profiling data?
A 'flame graph' visualizes CPU profiling data as stacked horizontal bars — wider bars mean more time spent in that function. The 'hot path' (widest bars at the top) reveals the performance bottleneck.
3 / 5
What is py-spy used for?
py-spy is a sampling profiler for Python that attaches to a running process without requiring code modifications or restarts — making it safe to use in production environments.
4 / 5
'The profiling run shows 60% time in ___.' Which function name is being called out?
'60% time in JSON.parse' is a classic profiling finding in Node.js services. It often means large JSON payloads are being deserialized in a hot path — a candidate for caching or streaming parsing.
5 / 5
What is async_profiler used for?
async_profiler is a low-overhead sampling profiler for the JVM (Java, Kotlin, Scala). It can profile CPU, heap allocations, and wall-clock time, and is safe to use in production.