What are some common mistakes in performance tuning?
An example of an AI chatbot conversation about common mistakes in performance tuning.
What are some common mistakes in performance tuning?
Some common mistakes include not measuring performance before tuning, focusing on micro-optimizations, and ignoring the impact of changes on overall system performance.
Can you elaborate on why measuring performance is important?
Measuring performance helps establish a baseline, allowing you to identify bottlenecks and assess the effectiveness of your tuning efforts.
What are micro-optimizations, and why should I avoid them?
Micro-optimizations are small, often insignificant changes that may improve performance slightly but can lead to complex code and maintenance issues.
How can I effectively measure performance before tuning?
You can use profiling tools, logging, and monitoring systems to gather data on response times, resource usage, and throughput.
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