Performance Tuning

Database Performance Tuning Techniques Performance tuning helps keep apps fast as data grows. It is a repeatable process: measure, analyze, and improve. The goal is steady latency and predictable throughput, not a single magic fix. Identifying Bottlenecks Start by knowing where time is spent. Collect measurements for latency, throughput, CPU and I/O, and memory use under realistic load. Look for slow queries, locking, or contention. Use query plans to see why a statement runs slowly. ...

Performance Tuning in Operating Systems Performance tuning in an operating system means adjusting settings so the system uses hardware more efficiently. The goal is faster, smoother responses and predictable behavior under load. Start by identifying your workload: a database, a web front end, or a batch job will need different tuning choices. Measure first. Collect data over typical days and during peak periods. Useful tools include top or htop for CPU load, iostat or vmstat for I/O and memory, sar for trends, and perf to inspect CPU events. Look for high I/O wait, memory pressure, or frequent context switches. Your measurements guide the changes, not guesswork. ...

High-Performance Web Servers and Tuning Tips If your site handles many visitors, small delays add up. A fast server not only serves pages quickly, it uses CPU and memory more efficiently. The goal is steady throughput and low latency under load, with steps you can apply across different platforms. Choose an architecture that matches your traffic. Event-driven servers such as Nginx or Caddy manage many connections with fewer threads. A traditional thread-per-connection model can waste CPU and memory on idle threads. For static sites and APIs with spikes, start lean and add modules only when needed. ...