How do you compare and benchmark your Performance Tuning performance with others?

In pure technical terms, it all narrows down to Scalability and TPS ( Transactions per second). Have a fair number in mind like from current value of 10K TPS to 50K TPS (5 times ) with just 25% increase in CPU and RAM and then see how each layer ( DB, Middle Tier, OS ) behaves. It gives the direction which part to be tuned.

To benchmark and compare your performance tuning, start by defining key metrics like response time, throughput, and resource utilization. Establish baselines for your current system performance. Use industry benchmarks (e.g., SPEC, Load Runner,JMeter) and compare against these standards. For a competitive edge, analyze performance data from competitors when available. Implement load and stress tests to identify bottlenecks, and leverage cloud monitoring tools (e.g., AWS CloudWatch, Azure Monitor, and Dynatrace) for real-time insights. Continuously monitor and adjust based on findings, documenting improvements to validate performance enhancements and guide future optimizations.

Sometimes, when you start a project, the goals are not defined from the beginning. This is especially true for Performance Tuning Projects where one may realize the outcome is no longer feasible. In order to correctly define the goals, one must consider doing the following: 1. Do your homework - You may already be getting the best performance from the product. 2. Dependency on other teams - Aligning your goals with the dependent team’s priorities and objectives. 3. Goals could be fluid and depend on infrastructure - Performance tuning goal could be waiting on next gen hardware that is releasing next year. In all of the above cases, define your objectives explicitly and review them with all stakeholders before moving ahead.

Usually with Baseline we compare also with different parameters at each layer according to our needs we test the use cases with multiple (1k,2k users) user loads and test the regression. Main things How is CPU utilisation , Memory utilisation , Query performance at DB side Network issue etc

??Measuring your performance tuning efforts is essential to stay competitive and efficient??. Here’s how you can : 1. Leverage Industry Tools ?? – Use established benchmarking tools like JMeter, Apache Bench, or Gatling to measure your system's response times, throughput, and resource utilization. 2. Set Baseline Metrics ?? – Identify key performance indicators (KPIs) such as latency, CPU utilization, and memory usage. Establish a baseline for your systems to track improvements. 3. Collaborate and Share Insights ?? – Participate in community forums or conferences to share results and learn from peers. Collaborative learning enhances tuning skills and exposes you to new methods.

In my 8 years of experience, I have found the Performance tools and profiler to be very useful but provide misleading results if not used correctly. Some common mistakes I made while using these tools are following: 1. Load runner tools can quickly saturate a client system making it difficult to evaluate scalability of the exact system under test. 2. Profiler tools can have varying degrees of performance overhead that depends on the Sampling interval. For fine granularity, one might actually observe profiling tool to be using the most resources thereby starving the actual system / application under test. Always watch videos and read medium blogs before using these tools.

To ensure effective performance tuning, use standard tools like profilers, APM (Application Performance Monitoring) software, and load testing tools (e.g., JMeter, Gatling) to measure key metrics such as response time, CPU usage, and memory efficiency. Leverage methods like load testing, stress testing, and bottleneck analysis to identify areas for improvement. Implement benchmarking frameworks and compare against industry standards or peers using tools like SPEC or TPC benchmarks. Regularly analyze logs, conduct performance reviews, and apply best practices for tuning based on these tools' insights.

Performance tuners are researchers rather than Engineers. Only way researchers can succeed is by learning from the community and giving back. I have found Github issues page as well as StackOverflow to be a very helpful resource on learning about scalability challenges for Open source projects. General rule of thumb when engaging with Open source communities - 1. Be succinct in your communication. A verbose question / answer receive a lot less engagement. 2. Screenshot of the actual issues with labels / pointers can help others understand your topic even better.

To learn from others in performance tuning, actively engage with communities, attend industry conferences, and participate in forums or groups where experts share insights and best practices. Study case studies, technical blogs, and performance reports from organizations that have tackled similar challenges. Collaborate with peers in your network to exchange experiences and approaches, and seek out mentorship or advice from seasoned professionals. Leverage open-source projects, benchmarking tools, and published performance data from successful companies to understand what works well in your field and apply those learnings to your own tuning efforts.

Based on my day to day work, here are top 5 points to further enhance your performance tuning project: 1. Continuous Monitoring: Implement continuous monitoring tools to track performance enabling prompt identification of issues. 2. Root Cause Analysis: Develop a systematic approach to identify the root causes of performance issues, enabling more effective solutions. 3. Automated Testing: Integrate automated performance testing into your development pipeline to catch issues early. 4. User Feedback Integration: Gather feedback from end-users to identify performance issues that may not be evident through traditional monitoring. 5. Document and help others: Most performance problems are common. Writing simple 1 pager goes a long way.

To continuously review and improve performance tuning, regularly analyze system metrics and logs to identify any new bottlenecks or inefficiencies. Conduct periodic performance assessments using established benchmarks and compare them against previous results to measure progress. Gather feedback from the team and stakeholders to refine tuning strategies and align with evolving project needs. Experiment with new tools, methods, and configurations, then measure their impact on performance. Make incremental adjustments, document changes, and iterate on optimizations to ensure ongoing improvements in system performance.

When considering performance tuning, also prioritize user experience, as responsiveness significantly impacts satisfaction. Ensure your optimizations are scalable to accommodate future growth without major rework. Implement automation tools for monitoring to quickly identify and resolve issues, and optimize resource management to prevent underutilization or overload. Foster collaboration among development, operations, and QA teams to address performance challenges early, and maintain thorough documentation of tuning processes and outcomes for future reference. By integrating these factors, you can enhance the effectiveness and sustainability of your performance tuning efforts.