System Capacity Design and Evaluation: Concepts, Metrics, and Practical Steps
This article explains how to design and evaluate system capacity by defining key concepts such as design capacity, TPS, QPS, and concurrency, outlining when capacity assessment is needed, and providing a step‑by‑step methodology with real‑world examples and calculations for accurate performance planning.
Background
The article starts with a real‑world scenario of a company sports event where the number of participants and limited time caused capacity problems, illustrating the need for proper capacity design.
Concept
Design capacity is defined as the process of estimating system resources (data volume, concurrency, bandwidth, CPU, memory, storage, etc.) required to meet business needs.
Analysis Process
Key performance indicators are introduced:
TPS (Transactions Per Second) : number of transactions processed each second.
QPS (Queries Per Second) : number of requests handled each second, a common measure of throughput.
Concurrency : number of simultaneous requests the system can handle.
Formulas are provided, e.g., QPS = (Total PV * 80%) / (Seconds per day * 20%) and the relationship QPS = Concurrency / AvgResponseTime.
When to Evaluate System Capacity
Temporary traffic spikes (e.g., promotional events like 618, Double‑11).
Initial system capacity assessment before launch.
Changes in capacity baseline as features and data grow.
Evaluation Steps
Analyze total daily visits (PV/UV) from product, operations, and monitoring data.
Calculate average daily QPS.
Estimate peak‑interval QPS using traffic curves or the 80/20 rule.
Conduct performance stress testing (e.g., using nGrinder or JMeter) to find the maximum QPS a single instance can sustain.
Adjust based on redundancy and desired response time, then determine the required number of instances.
Case Study
A library reservation system example shows how to compute QPS, peak QPS, and required concurrency using the 80/20 rule and a pessimism/optimism factor, resulting in a recommended concurrency of about 200.
Conclusion
The article summarizes the timing, steps, and practical considerations for system capacity design, emphasizing that early and accurate capacity planning prevents performance disasters and ensures smooth operation during traffic surges.
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Top Architect
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