Performance Tuning Practice
Performance Tuning — Practice Problems
15 MCQ questions covering CPU tuning, memory management, I/O optimization, network tuning, and profiling tools. Select an option to check your answer and view the explanation.
CPU Tuning
Memory Management
I/O Optimization
Network Tuning
Profiling Tools
Intuition
Performance tuning combines measurement with reasoning: Profiling reveals where time is spent, but understanding why a particular code path is slow requires knowledge of hardware, algorithms, and system architecture.
Why it matters: Performance tuning skills are essential for building scalable applications and efficient infrastructure.
The key insight: The 80/20 rule applies, 80% of performance problems come from 20% of the code. Focus your optimisation efforts where they matter most.
Common Mistakes
Optimising code before understanding requirements: Different requirements demand different optimisations. Low-latency systems prioritize latency over throughput. Data pipelines prioritize throughput. Know which metric matters before starting.
Ignoring algorithm complexity: An O(n^2) algorithm cannot be made fast enough for large n by optimising constants. Switch to an O(n log n) algorithm. No amount of micro-optimisation fixes a fundamentally wrong algorithm choice.
Forgetting about memory allocation patterns: Frequent small allocations cause GC pressure. Pre-allocate buffers, reuse objects, or use object pools. In hot paths, avoid allocation entirely.
See Also
Detailed Content
Core Concepts
Worked Examples
Common Mistakes
- Rushing through foundational material
- Not practising problems after reading
- Failing to connect concepts across topics