Regression Detected in Kepler or kube-apiserver CPU Utilization Performance

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Regression detected from the following reports:

Report: https://sustainable-computing-io.github.io/kepler-metal-ci/kepler-stress-test-metrics.html

Details:
Significant Regression Detected

Detailed Analysis and Conclusion:
Upon reviewing the test results from the last two days, a significant performance regression is observed in the Kepler CPU utilization metrics. Specifically, the data from 2024-07-31 shows a drastic increase in both the mean Kepler CPU Utilization and the Standard Deviation (Std Dev) percentages.

1. Comparison of Metrics:

   • On 2024-07-30, the Mean Kepler CPU Utilization was 0.0597766338% with a Std Dev of 0.0362022150%.
   • On 2024-07-31 at 18:18:00Z, the Mean Kepler CPU Utilization jumped to 0.3280331034%, and the Std Dev increased to 0.2598348881%.
   • A subsequent test on the same day at 19:50:43Z showed a Mean Kepler CPU Utilization of 0.3038928317% and a Std Dev of 0.2290510851%.

2. Magnitude of Change:

   • The increase in Mean Kepler CPU Utilization from the previous day is approximately 448%, and the increase in Std Dev is approximately 618%.
   • Such changes are well beyond typical fluctuations and indicate a severe degradation in performance.

3. Potential Causes:

   • This significant increase could be due to changes in the test environment, updates in the software stack, increased load, or possibly an introduction of a performance bug in the latest deployment.

4. Recommendations:

   • It is crucial to investigate the changes made to the system between the tests on 2024-07-30 and 2024-07-31.
   • Reviewing code changes, configuration updates, and increased load scenarios will be essential to pinpoint the cause.
   • Rolling back recent changes or applying quick fixes might be necessary to mitigate the impact on system performance.

5. Next Steps:

   • Conduct a root cause analysis with all stakeholders involved in the recent changes.
   • Monitor the system closely to check if the regression persists in subsequent tests.
   • Consider implementing additional alerting mechanisms to detect such regressions promptly in the future.

This regression is critical and requires immediate attention to prevent potential impacts on production environments or further degradation of system performance.