---
title: "Visualize the spike in Grafana Cloud k6 | Grafana Labs"
description: "Send spike test results to Grafana Cloud k6 to see how latency, error rate, and throughput changed across the baseline, spike, and recovery phases."
---

> For a curated documentation index, see [llms.txt](/llms.txt). For the complete documentation index, see [llms-full.txt](/llms-full.txt).

# Visualize the spike in Grafana Cloud k6

The end-of-test summary aggregates metrics across the entire run, which blends the spike with the calm periods. Grafana Cloud k6 shows a timeline of when the spike happened and how latency, errors, and throughput changed in each phase. Use the timeline to measure recovery time; the summary alone does not split metrics by phase.

To visualize your spike test in Grafana Cloud k6, complete the following steps:

1. If you haven’t already authenticated with Grafana Cloud k6, log in from the CLI:
   
   Bash ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy
   
   ```bash
   k6 cloud login --token <YOUR_API_TOKEN> --stack <YOUR_STACK_SLUG_OR_URL>
   ```
   
   In Grafana Cloud, go to **Testing &amp; synthetics** &gt; **Performance** &gt; **Settings**. Under **Access**, copy your **Personal token** or **Stack token**. For `--stack`, pass your stack URL slug or full stack URL (for example `my-team` or `https://my-team.grafana.net`). Refer to [Authenticate on the CLI](/docs/grafana-cloud/testing/k6/author-run/tokens-and-cli-authentication/).
2. Run the spike test with cloud output:
   
   Bash ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy
   
   ```bash
   k6 cloud run --local-execution spike.js
   ```
   
   The `--local-execution` flag runs the test on your machine while streaming results to Grafana Cloud k6 for storage and visualization, as described in [Use the CLI](/docs/grafana-cloud/testing/k6/author-run/use-the-cli/#run-a-test-locally-and-stream-the-results-to-grafana-cloud-k6). k6 prints a URL to the test result in Grafana Cloud.
   
   > Note
   > 
   > `--local-execution` runs the test on your machine and streams results to Grafana Cloud k6. It’s convenient for small tests like this one. For higher VU counts, your machine can become the bottleneck and skew the results; run the test on managed cloud load generators instead by dropping the flag:
   > 
   > Bash ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy
   > 
   > ```bash
   > k6 cloud run spike.js
   > ```
   > 
   > Both commands use the same `spike.js` script; only where k6 executes the test differs. Refer to [Use the CLI](/docs/grafana-cloud/testing/k6/author-run/use-the-cli/#run-a-test-on-grafana-cloud-k6).
3. Open the test result URL in your browser.
4. In the Grafana Cloud k6 test result, look at the **Performance Overview** section.
   
   The VU count shows the spike shape: a flat line at 5, a sharp jump to 100, and a drop back to 5. When request rate and response time series are visible, request rate tracks the burst and response time shows whether latency changed during or after the spike.
5. Correlate the VU shape with the response time and throughput lines on the same chart.
6. Compare the response time across each phase of the test:
   
   - **Baseline phase** (first two minutes): Confirm latency and throughput are stable. These are your reference values.
   - **Spike phase** (the burst): Note whether response time stayed flat, rose proportionally, or spiked with errors when VUs jumped to 100.
   - **Recovery phase** (three minutes after the spike): Compare post-spike response time to the baseline phase. A resilient system returns to baseline values within seconds.
   
   > Note
   > 
   > If the system handled the spike without any visible change in the timeline, that’s a valid result. It means the 20x spike didn’t exceed the system’s instantaneous capacity. You can increase the spike multiplier (for example, from 100 VUs to 200 or 500) and run again to find where the response changes.

In the next milestone, you document per-phase metrics and calculate recovery time from the timeline.