Enhanced Grafana k6 Dashboard Features: Bridging Reporting Gaps and Focusing on Visualization Needs

[oshalahan]

Hello, fellow performance enthusiasts! 👋 I'm Oleh, and I'm excited to share my journey with you in the dynamic realm of performance testing. After four dedicated years as a JMeter user, I recently dove into the world of Grafana k6, seeking a more flexible and modern approach to performance monitoring.

The shift to k6 has been an exhilarating adventure, introducing a breath of fresh air in terms of usability and scalability. However, as with any transition, challenges inevitably arise. A particular hurdle I've encountered is the pursuit of comprehensive insights within the k6 generation reports. While JMeter has been a rich source of information in the past, the transition to Grafana k6 has left me longing for more detailed metrics and analytics.

In this journey, I've discovered that the default k6 generation reports sometimes fall short in delivering the depth of information I grew accustomed to with JMeter. As a performance enthusiast with a keen eye for data, I'm now navigating the landscape of Grafana k6, exploring ways to enhance and enrich the reports to meet the high standards set by my JMeter experience.

I'm on a mission to find or create reports in Grafana k6 that mirror the key metrics I heavily relied upon in JMeter — reports such as Response Codes per Second, Hits per Second, Response Times Over Time, Aggregate Report, and Transactions per Second. These metrics not only provided valuable insights into the performance of my applications but also served as a benchmark for assessing their health and efficiency.

JMeter Reports Breakdown

Transactions per Second:

• Purpose: Measures the rate at which complete business transactions are executed per second.
• Significance: Focusing on transactions per second allows you to align performance metrics with business goals. This metric is crucial for assessing the holistic impact of user interactions on the system, providing insights into the overall health and efficiency of your application's critical workflows.
  

Hits per Second:

• Purpose: Measures the rate at which requests (hits) are made to the server per second.
• Significance: Tracking hits per second is crucial for understanding the overall load on the server. Sudden spikes or drops in this metric can indicate changes in user behavior, marketing campaigns, or issues affecting the user experience.
  

Response Codes per Second:

• Purpose: This metric provides an overview of the distribution of HTTP response codes over time.
• Significance: Monitoring response codes per second helps identify potential issues, such as an increasing rate of error responses or unexpected status codes, aiding in the early detection of performance bottlenecks or application errors.
  

Response Times Over Time:

• Purpose: Illustrates how the response times of your application vary throughout the test.
• Significance: Examining response times over time helps identify patterns, trends, or anomalies. It assists in pinpointing periods of peak load, and potential performance degradation, and understanding how the application responds under different levels of stress.
  

Aggregate Report:

• Purpose: Aggregates and summarizes key performance metrics such as average response time, throughput, error rate, and more.
• Significance: The aggregate report provides a consolidated view of the test results, making it easier to analyze overall performance. It is a go-to resource for understanding the average behavior of your application during a test and identifying areas that may require optimization.
  

If you have insights or suggestions, or if there's an ongoing effort in this direction, I would greatly appreciate any guidance or information you can provide.

Thank you for your time and consideration. I'm looking forward to hearing your thoughts on this matter.