How do you learn from your performance tuning failures and successes?

Identifying the problem and ascertaining if tuning is indeed needed to fix the problem, is very important step. In my experience, there were many instances where the problem statement was very ambiguous and reported metric was pre-existing state but the reporter of the problem was either unaware of it or new to the environment. Checking the historic metric of the reported problem really helped in deciding if it was really a performance issue.

From my experience, the first thing you need to do to identify the problem is finding the correct SQL query need to be tunned. You can use the monitoring tool like OEM, SQL developer,... and also can use AWR report for troubleshooting.

???Learning from Performance Tuning: Failures & Wins ?? Analyze Failures Without Bias ?? – Failures aren’t setbacks; they’re learning opportunities. Break down what went wrong, whether it was resource bottlenecks, inefficient code, or misconfigured systems. Failures expose areas for growth. Document Successes for Repeatability ?? – When a tuning effort works, capture the details! What tools did you use? What strategies did you implement? Documentation ensures that future projects benefit from past wins. Foster a Culture of Continuous Feedback ?? – Encourage open dialogue with your team. Share both your mistakes and achievements. The most innovative SREs learn not just from personal experience but from the collective wisdom of the team.

After experiencing performance tuning failures and successes, it is important to follow a structured approach for learning and improvement. First, it is crucial to identify the root cause by thoroughly analyzing logs, metrics, and behaviors to pinpoint the exact issue. Once the root cause is identified, it is essential to document findings, noting what worked and what didn't in a structured manner. After documenting findings, it is important to evaluate the impact of the changes made to address the performance issues. This assessment should include both positive and negative effects on performance. Using the insights gained from the evaluation, it is important to iterate and refine the approach for future performance tuning efforts.

For performance issues, usually the root cause is either of the below. 1. Change in usage pattern like sudden spike in usage of specific API which could cause delay or poor performance. 2. New code that was not performance tested in production like environment. It was important to identify the root cause, only then our solution will help in addressing the specific performance issue.

Based on my experience and root cause analysis, I use performance data and analysis to conduct root cause analysis and identify factors contributing to performance issues. Look for underlying causes such as inefficient code, resource contention, database bottlenecks, network latency, third-party dependencies, or infrastructure limitations. Evaluate the system architecture and design to identify architectural bottlenecks or scalability limitations. Determine if the system architecture adequately supports the expected workload and user concurrency. Assess the impact of architectural decisions on system performance.

I solved many performance tuning case during my career, where the user reported a feature which ran fast before but suddenly run slow, most of the cases over 90% are changing execution plan. (maybe statistic changes, the indexes became invalid, new index added, or database system itself evaluate the query again and find other execution plan for the query,..). There are many reasons for that.

In the process of performance tuning, it is important to follow a systematic approach to analyze the root cause of any performance issues. This involves collecting data such as logs, metrics, and system behavior details, identifying patterns or anomalies, breaking down components to isolate the problem area, using profiling tools to detect bottlenecks, and testing hypotheses through experimentation. By following these steps, it becomes easier to pinpoint the root cause and implement effective solutions to improve performance.

Before implementing the solution, given solution should be validated and ensured that a best possible fix is provided. otherwise temporarily the problem will be avoided but at a later time, the same or similar issue will pop-up.

The solution should be implemented carefully. Adding new indexes can make other query change their execution plan (which can be bad). Apply patch can make another bug appear on your system. Partition table need some downtime,... We should evaluate many aspect before implement the solution in production.

To effectively implement a performance tuning solution, it is important to follow a systematic approach. First, it is essential to develop a clear plan outlining the specific changes needed to address the root cause of the performance issues. This plan should detail the steps to be taken and the expected outcomes. Next, it is advisable to apply incremental changes rather than making multiple adjustments at once. Implementing one solution at a time allows for better isolation of its impact, making it easier to identify what is working and what is not. Monitoring the results of the implemented changes is crucial. Tracking performance metrics will provide insight into whether the changes are improving efficiency as intended.

Validation at the immediate suitable time slot by comparing old metrics and lates metrics is a critical step of the performance tuning process, which saves many hours of troubleshooting after the fix is placed :).

After performance tuning, it's important to evaluate the results to ensure that the changes have been effective. Here are some steps to consider: 1. Compare metrics: Analyze key performance indicators (KPIs) before and after the change to see if there have been any improvements in areas such as load time and response rates. 2. Check for improvements: Make sure that the solution has addressed the initial issue,such as reducing load time and improving response rates. 3. Gather feedback: It's important to get input from users or stakeholders on the system's performance to understand their experience and any remaining concerns. 4. Identify side effects:Look for any unintended impacts or new issues caused by the changes to address them promptly.

Yes, listening to feedback and learning from our past experiences helps to improve efficiency of the performance tuning process.

It seems like you are discussing the process of learning from feedback. It's important to review feedback, identify trends, adapt and improve, communicate changes, and incorporate lessons for future improvement. This iterative process can lead to continuous improvement and better outcomes in future projects.

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