You ran a performance test. JMeter shows 47 columns of data. Grafana has 12 dashboards. The test report is 200 pages long. Your manager asks: "So, are we good?" You need to answer that question with 3-4 numbers, not 47 columns.
Performance testing produces a mountain of data. But only a handful of metrics actually matter for decision-making. Learn these metrics deeply, and you can read any performance test report in any tool and know exactly what is happening.
| Metric | What It Measures | Unit | Good Value |
|---|---|---|---|
| Response Time | How long a user waits for a response | Milliseconds (ms) | p95 < 2 seconds for pages, < 500ms for APIs |
| Throughput | How many requests the system handles | Requests per second (RPS) | Depends on expected traffic |
| Error Rate | Percentage of failed requests | Percentage (%) | < 1% under expected load |
| Concurrent Users | Users actively sending requests simultaneously | Count | Depends on application |
Think of it like a restaurant. Response time is how long a customer waits for food. Throughput is how many meals the kitchen serves per hour. Error rate is how many orders come out wrong. Concurrent users is how many people are sitting in the restaurant at the same time.
Key Point: Four metrics tell the story: response time (how fast), throughput (how much), error rate (how reliable), and concurrent users (how many). Master these four and you can read any performance report.
Key Point: Four core metrics: response time, throughput, error rate, concurrent users -- these tell the complete performance story