How can you measure the impact of a performance issue?

One practice I have found helpful is using feature scenarios to describe normal, alternate course and invariants and then automating the execution of that feature. This allows for predictable behavior and if an error is found it truly is something unknown or unexpected. That’s not to say it is bad just unexpected and unplanned. Therefore just add a new feature scenario and test it thereby extending the functionality with a fix which enhances the product and produces higher quality.

Focus on the user experience journey. This approach goes beyond just technical metrics, considering how performance issues affect the user's emotional response and overall satisfaction. By combining these user-centric insights with standard performance metrics, we gain a fuller understanding of the issue's true impact, leading to more effective and user-friendly solutions.

It's essential to start monitoring your application performance from day one. Otherwise it's impossible to understand whether something is becoming (or is) a problem. Modern frameworks support this quite well (e.g. Spring Actuator). Only then is it possible to reason about performance metrics.

A better approach I found helpful is to gather feedback from users who have experienced the performance issue. This can be done through surveys, interviews, or monitoring user reviews. Analyzing their feedback can provide insights into the impact the issue has on their experience and satisfaction. Utilize performance monitoring tools to collect data on various performance metrics such as response time, latency, throughput, and error rates. Analyze user behavior data to identify any changes or patterns that coincide with the occurrence of the performance issue. Look for indicators such as increased bounce rates, decreased engagement, or reduced conversions. These changes can indicate the impact of the issue on user behavior.

Analyzing the root cause of performance issues is like tech detective work. It's about more than just using tools; it involves understanding how different parts of your application work together. By getting to the root of the problem, you can focus on the most effective solutions.

As mentioned before- it is imperative to have a performance monitoring set from the get go. This includes the possibility to activate Zipkin or a similar tool that visually displays the execution times and paths of the request. Remember a performance issue can be caused by multiple issues happening together. That is why it's good to have a visual representation of the request. Be on a lookout for suspicious gaps between logged request paths since this indicates a bad configuration - there is something happening but we do not know why. Make sure to fix those issues first!

It comes down to the impact felt by the users of the application. Were they unable to perform the task they depended on the app for? Was there a loss of revenue? How long did the disruption last Also, there’s potential impact to the brand reputation of the company offering that product. And in my industry (financial services) there can be monetary penalties as well

Estimating the impact is about understanding how much the performance issue really matters. It involves looking at how the problem affects users and the business. This step helps in deciding if the issue is a minor annoyance or a major setback, guiding the decision on how much resource and effort to invest in fixing it.

Not all issues are alike- you can spend a day fixing a slow query that is only run once per day and maybe not even by a human or you can focus on improving the response times of the requests that are frequently used!

No matter what you choose always keep track and test. It's like choosing the right tool for a job – each alternative might fix the issue, but some are more efficient than others. It’s important to test these options and see which one really works best in your specific scenario, considering both the benefits and potential risks.

This is about putting your solution into action and seeing the results. It's a crucial step where the theoretical meets the real world. After implementing changes, it's key to monitor closely to ensure the performance has genuinely improved. This phase is not just about fixing the issue but also about validating the effectiveness of your solution in a live environment.

Taking what we've learned from solving the performance issue and using it to prevent future problems. It’s also an opportunity to update our processes and optimize our application for upcoming changes, ensuring we're better prepared for whatever comes next.