Trend Analysis and Baselining in CI
Track performance over time across pipeline runs by storing baselines and detecting regressions automatically before they ship.
Trend Analysis and Baselining in CI is a free Load Testing & Performance Benchmarking (JMeter & k6) lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Load Testing & Performance Benchmarking (JMeter & k6) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
A Single Run Is Not Enough
Pass/fail gates catch obvious breakage, but slow drift over weeks is invisible to a single run. Baselining compares each build against historical performance to catch creeping regressions.
What Is a Baseline?
A baseline is a stored reference result, usually the metrics from a known-good build. New runs are measured against it. Common baselines are the previous release or a rolling average of recent runs.
Tagging Runs for Trends
To compare across builds, tag each run with a unique identifier such as the commit SHA or build number. This lets the backend separate and chart each run.
k6 run --tag testid=$GIT_COMMIT --out influxdb=http://metrics:8086/k6 perf.jsStoring Results Over Time
Persist results in a time-series database (InfluxDB, Prometheus) or a results store. Without persistence there is no history to trend against.
Defining Acceptable Drift
Decide how much regression is tolerable, for example p95 may not exceed the baseline by more than 10%. Encode this as a comparison step in the pipeline.
BASELINE_P95=400
MAX_ALLOWED=$((BASELINE_P95 * 110 / 100))
echo "Threshold: $MAX_ALLOWED ms"Comparing Against Baseline
A small script can read the new p95 from the k6 JSON summary and fail the build if it exceeds the allowed drift.
P95=$(jq '.metrics.http_req_duration.values["p(95)"]' summary.json)
if (( $(echo "$P95 > $MAX_ALLOWED" | bc -l) )); then
echo 'Regression detected'
exit 1
fiRolling Baselines
Instead of one fixed reference, a rolling baseline averages the last N runs. This adapts to gradual, intentional changes while still flagging sudden regressions.
Visualizing Trends
A Grafana panel of p95 over build numbers makes drift obvious to the whole team. A slowly rising line is a warning even when every individual build passed its gate.
Avoiding Noisy Baselines
Run performance tests on consistent, isolated infrastructure. Comparing against a baseline collected on noisy shared hardware produces false regressions and erodes trust.
Updating the Baseline
When a release intentionally changes performance, promote its result to the new baseline. Automate this so the reference stays current without manual edits.
Annotating Releases
Mark deploys and config changes on your trend charts. An annotation at the exact build where p95 jumped turns a mysterious line into an obvious culprit.
Quick Check
Test your trend-analysis knowledge.
Recap
You learned to trend performance in CI.
- Tag and persist every run for history.
- Define acceptable drift and compare new runs to a baseline.
- Use rolling baselines and clean infrastructure to avoid noise.
Frequently asked questions
Is the “Trend Analysis and Baselining in CI” lesson free?
Yes — the full text of “Trend Analysis and Baselining in CI” is free to read here on the web, and the Load Testing & Performance Benchmarking (JMeter & k6) course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Load Testing & Performance Benchmarking (JMeter & k6) course, upgrade to CoddyKit PRO.
What will I learn in “Trend Analysis and Baselining in CI”?
Track performance over time across pipeline runs by storing baselines and detecting regressions automatically before they ship. You practise Load Testing & Performance Benchmarking (JMeter & k6) with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Load Testing & Performance Benchmarking (JMeter & k6)?
No prior experience is required. Load Testing & Performance Benchmarking (JMeter & k6) on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Trend Analysis and Baselining in CI” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Load Testing & Performance Benchmarking (JMeter & k6) lesson?
Yes. Every Load Testing & Performance Benchmarking (JMeter & k6) lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Integrating JMeter with Jenkins
- k6 in GitHub Actions
- Performance Gates and SLOs
- Trend Analysis and Baselining in CI