[ci] Upload autoscaling in K8s test results

[selenium-ci]

User description

This PR contains the results of the autoscaling tests in Kubernetes

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PR Type

Tests

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Description

• Updated Kubernetes autoscaling test results across multiple scenarios.

• Adjusted metrics for deployment count and job count strategies.

• Refined results for chaos scenarios and node max sessions.

• Improved consistency and accuracy in test data representation.

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Changes walkthrough 📝

Relevant files

Tests

results_test_k8s_autoscaling_deployment_count.md Updated deployment count autoscaling test results                .keda/results_test_k8s_autoscaling_deployment_count.md Updated test results for deployment count strategy. Adjusted metrics for session creation and pod scaling. Improved data consistency across iterations. +20/-20  results_test_k8s_autoscaling_deployment_count_in_chaos.md Updated deployment count in chaos test results                      .keda/results_test_k8s_autoscaling_deployment_count_in_chaos.md Updated test results for deployment count in chaos scenarios. Refined metrics for pod scaling and session handling. Enhanced accuracy in chaos scenario data. +20/-20  results_test_k8s_autoscaling_deployment_count_with_node_max_sessions.md Updated node max sessions autoscaling test results              .keda/results_test_k8s_autoscaling_deployment_count_with_node_max_sessions.md Updated test results for node max sessions strategy. Adjusted metrics for pod scaling and session limits. Improved data representation for node constraints. +20/-20  results_test_k8s_autoscaling_job_count_strategy_default.md Updated default job count strategy test results                    .keda/results_test_k8s_autoscaling_job_count_strategy_default.md Updated test results for default job count strategy. Refined metrics for session creation and pod scaling. Enhanced consistency in job count data. +20/-20  results_test_k8s_autoscaling_job_count_strategy_default_in_chaos.md Updated job count in chaos test results                                    .keda/results_test_k8s_autoscaling_job_count_strategy_default_in_chaos.md Updated test results for job count in chaos scenarios. Adjusted metrics for pod scaling and session handling. Improved accuracy in chaos scenario data representation. +20/-20  results_test_k8s_autoscaling_job_count_strategy_default_with_node_max_sessions.md Updated job count with node max sessions test results        .keda/results_test_k8s_autoscaling_job_count_strategy_default_with_node_max_sessions.md Updated test results for job count with node max sessions. Refined metrics for session creation and pod scaling. Enhanced data consistency for node constraints. +20/-20

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[qodo-merge-pro]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🧪 PR contains tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Performance Concern High session creation times (30-40s) in early iterations may indicate scaling inefficiencies that need investigation | 1 | 2 | 39.74 s | 0 | 2 | 2 | 2 | 1 | 0 | 2 | | 2 | 2 | 39.03 s | 0 | 1 | 2 | 3 | 1 | 1 | 0 | | 3 | 3 | 37.15 s | 0 | 2 | 5 | 5 | 1 | 0 | 0 | | 4 | 2 | 41.82 s | 0 | 2 | 7 | 7 | 1 | 0 | 0 | | 5 | 3 | 31.94 s | 0 | 3 | 10 | 10 | 1 | 0 | 0 | | 6 | 1 | 43.87 s | 0 | 1 | 11 | 11 | 1 | 0 | 11 | Resource Utilization Large number of gaps between total pods and running sessions suggests potential resource waste and inefficient pod allocation | 6 | 3 | 18.11 s | 0 | 3 | 9 | 10 | 3 | 21 | 9 | | 7 | 3 | 15.75 s | 0 | 0 | 3 | 9 | 3 | 24 | 0 | | 8 | 2 | 15.64 s | 0 | 1 | 5 | 11 | 3 | 28 | 0 | | 9 | 1 | 16.46 s | 0 | 0 | 6 | 11 | 3 | 27 | 0 | | 10 | 2 | 13.45 s | 0 | 1 | 8 | 12 | 3 | 28 | 0 | | 11 | 3 | 14.04 s | 0 | 0 | 11 | 12 | 3 | 25 | 11 |

[qodo-merge-pro]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Impact
General	Reduce excessive idle pod count The high number of gaps (up to 10) in iterations 7-8 indicates inefficient pod utilization. Consider adjusting the scaling threshold to reduce the number of idle pods and optimize resource usage. .keda/results_test_k8s_autoscaling_deployment_count.md [9-10] -| 7 | 2 | 14.33 s | 0 | 0 | 2 | 11 | 1 | 9 | 0 | -| 8 | 1 | 5.54 s | 0 | 0 | 3 | 11 | 1 | 8 | 0 | +| 7 | 2 | 14.33 s | 0 | -3 | 2 | 8 | 1 | 6 | 0 | +| 8 | 1 | 5.54 s | 0 | 0 | 3 | 8 | 1 | 5 | 0 | [To ensure code accuracy, apply this suggestion manually] Suggestion importance[1-10]: 8 __ Why: The suggestion addresses a significant resource efficiency issue by identifying high pod underutilization (9 gaps) and proposing concrete scaling threshold adjustments to optimize cluster resources.	Medium
	Optimize pod resource utilization Large gap count (20-34) in later iterations suggests severe pod underutilization. Implement pod termination for idle pods to maintain optimal cluster efficiency. .keda/results_test_k8s_autoscaling_job_count_strategy_default_with_node_max_sessions.md [19-21] -| 17 | 3 | 13.87 s | 0 | 0 | 3 | 9 | 3 | 24 | 0 | -| 18 | 1 | 5.04 s | 0 | 0 | 4 | 9 | 3 | 23 | 0 | -| 19 | 1 | 12.96 s | 0 | 0 | 5 | 9 | 3 | 22 | 0 | +| 17 | 3 | 13.87 s | 0 | -3 | 3 | 6 | 3 | 15 | 0 | +| 18 | 1 | 5.04 s | 0 | 0 | 4 | 6 | 3 | 14 | 0 | +| 19 | 1 | 12.96 s | 0 | 0 | 5 | 6 | 3 | 13 | 0 | Apply this suggestion Suggestion importance[1-10]: 7 __ Why: The suggestion correctly identifies severe pod underutilization with 22-24 gaps and proposes a valid solution to improve cluster efficiency through pod termination strategies.	Medium