Identify your baseline values

You’ve run the test and you have raw numbers. Now you need to decide which specific values represent your baseline. This step bridges the gap between “I ran a test” and “I have a benchmark I can enforce.” The values you record here become the criteria you encode as thresholds in the next milestone.

To identify your baseline values, complete the following steps:

1. Locate the http_req_duration line in your test summary and note the p(95) value. This is your p95 latency baseline.

   For example, if the summary shows:

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   http_req_duration..: avg=180ms  min=95ms
                        med=165ms  max=850ms
                        p(90)=280ms  p(95)=350ms

   Your p95 latency baseline is 350 ms. This means 95% of requests completed within 350 ms under your test conditions.

   Tip

   The p95 value is a good starting point for your baseline. It captures the experience of the vast majority of users while filtering out rare outliers. You can also use p90 for a less strict baseline, or add custom percentiles like p99 in your thresholds configuration later.

2. Locate the http_req_failed line and note the percentage. This is your error rate baseline.

   For example:

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   http_req_failed................: 0.00%   0 out of 1200

   Your error rate baseline is 0%. In practice, set a small tolerance, such as less than 1%, to account for transient network issues.

3. Locate the iterations line and note the per-second rate. This is your throughput baseline.

   For example:

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   iterations.....................: 1200    10.00/s

   Your throughput baseline is 10 requests per second at 20 VUs.

4. Record these values. You’ll use them directly in the next milestone to define pass/fail thresholds:

   Expand table

   Metric	Baseline value	Threshold to set
   p95 latency	350 ms	p(95)<500 (add headroom)
   Error rate	0%	rate<0.01 (allow <1%)
   Throughput	10 RPS	Monitor, not threshold

   Add headroom to your baseline values when setting thresholds. Headroom means setting the threshold higher than your observed value so normal variance doesn’t trigger false failures.

   A common approach is to multiply your observed p95 by 1.2 to 1.5 (20-50% above). For example, if your p95 is 53 ms, multiply by 1.3 to get a threshold of p(95)<70. Use less headroom (1.2x) for stable, low-latency services and more headroom (1.5x) for services with higher natural variance.

In the next milestone, you encode these baseline values into your script as thresholds.