prestandaproblem

A prestandaproblem is a condition in which a system's performance does not meet defined requirements or user expectations. It can affect software applications, websites, services, embedded devices, or networks, manifesting as high latency, low throughput, or degraded reliability even under nominal load.

Causes include hardware constraints such as CPU, memory and I/O limits; software inefficiencies like inefficient algorithms or memory leaks; architectural decisions that create scaling ceilings or single-threaded bottlenecks; external dependencies such as database latency or slow third-party services; configuration issues including suboptimal thread pools, cache sizes, or timeout settings; workload characteristics such as bursty traffic or skewed distributions; and environmental factors like network congestion or virtualization overhead.

Detection and measurement involve using monitoring and profiling to assess latency, p95 and p99, throughput, error rate, CPU and memory utilization, disk I/O and network bandwidth. Conducting load testing and stress testing helps reveal behavior under pressure, and tracing can locate bottlenecks in code paths and databases.

Mitigation focuses on identifying and addressing bottlenecks. Approaches include optimizing code and algorithms; introducing caching, asynchronous processing, and batching; database tuning and indexing; horizontal or vertical scaling; load balancing; content delivery networks; queuing; and configuration tuning, along with considered hardware upgrades or architectural changes such as service decomposition. Maintaining performance budgets and SLAs supports ongoing accountability.

Process and governance involve detection, root-cause analysis, remediation, verification, and documentation. Performance concerns should be integrated into development practices and CI/CD pipelines, with clear performance requirements and runbooks to guide repeatable responses.