Timeline View

Understanding the Timeline View

The Timeline tab shows virtual users, throughput and response times on one time axis, so you can see how your system behaves as load ramps up, plateaus and ramps down. The Timeline tab is available on paid plans; on a free plan the tab shows an upgrade icon instead.

Key Components

• Virtual Users Number of active virtual users at each moment (in a JMeter run, the threads executing your test plan).
• Hits / sec (throughput) Aggregate requests per second sent by all load generators.
• Response Time Per request, choose Avg, Min, Max, P90, P95 or P99 to plot latency trends.
• Granularity Selector Switch between Raw, 100ms, 500ms, 1s (the default), 1min and 5min aggregation intervals.
• Filter Panel The left-hand panel groups the series into Virtual Users, Response Time, Hits / sec, Errors, Latency, Response Codes, Sent Bytes and Received Bytes. Expand a group and tick the series you want to plot. Reset to Default and Unselect All are above the groups.
• View per location A button at the top right of the chart. It draws a separate series for each load generator (labelled Machine 1, Machine 2, and so on) instead of one merged series.

Line colors are assigned per series and change between page loads, so read the legend and the hover values rather than relying on a color.

How to Use the Timeline Tab

1. Run Your Test Run a cloud URL test, a k6 script or a JMeter .jmx on LoadFocus as usual.
2. Open Timeline Click the Timeline tab in the row of result tabs, just before Trend (after AI Assist, or after Engine Health on a JMeter run).
3. Select Metrics In the left-hand panel, expand a group such as Virtual Users, Response Time or Hits / sec and tick the series you want. Type in Filter requests to narrow a long list of requests.
4. Adjust Granularity Choose a time bucket that matches your troubleshooting needs: 1s for spikes, 1min for overall trends. See Granularity in results and charts.
5. Zoom In Drag horizontally across the chart to zoom into a time range. Click View per location to see each load generator as its own series.
6. Hover for Details Hover over any data point to see exact values. For example: HTTP Request - Hits/sec: 16 HTTP Request - Virtual Users: 10 HTTP Request - P99: 218

Interpreting Timeline Trends

• Load Ramp-Up Watch how Hits/sec scales with Virtual Users during the ramp-up phase. A plateau in throughput before target users are reached may indicate a bottleneck.
• Steady-State Behavior During the flat portion of the user curve, latency and throughput fluctuations reveal system stability under constant load.
• Ramp-Down Observations As virtual users decrease, throughput and latency should drop smoothly. Persistent high latencies during ramp-down suggest lingering resource contention or slow releases.
• Anomaly Detection Use the Granularity and Filters to spot sudden drops in throughput or spikes in P99 latency that may not appear in aggregate stats.

Best Practices

• Baseline and Ramp Profiles Configure a controlled ramp-up/ramp-down profile in your test settings or script (e.g., constant load vs. step load) to produce predictable timeline shapes.
• Correlate with Other Views If you see an unexpected plateau or spike, switch to Insights or Errors to drill into failure rates at that timestamp. For load generator resource usage, check the saturation warning on the Overview (see Load Generator Saturation); JMeter runs also have the Engine Health tab.
• Request-Level Analysis Tick several requests (for example Login, Search, Checkout) in the left-hand panel to compare their throughput and latency patterns.
• Location Comparison In multi-location tests, click View per location to see each load generator as its own numbered series and spot differences between them.