How do you prioritize and resolve software performance bugs and glitches?

To address performance issues effectively, first define "acceptable performance" for your software, considering its type, user expectations, business goals, and technical context. Establish clear, measurable criteria such as response time, throughput, availability, reliability, and scalability. For example, healthcare apps should aim for a response time under 2 seconds, while finance apps need high availability to maintain trust. These criteria set benchmarks for monitoring and evaluating changes. Regularly review these metrics to adapt to evolving user needs and business objectives, ensuring optimal software performance.

Quite often, performance testing is conducted during the final stages of development or delivery. However, this approach may lead to the accumulation of issues related to performance. By integrating observability and logging stacks early in the development process, we can identify performance-related code smells and issues much sooner. For instance, if a piece of code is making N+1 database calls or invoking redundant outbound API calls, these issues should be addressed promptly, without waiting for performance test reports. Furthermore, this strategy empowers the development team to be proactive in identifying and addressing such issues during the initial stages of development, thereby minimizing mistakes down the line.

Performance consideration should start at the beginning of the project undertaking, right from the design and application architecting stage. If at later stage you realize some design issues it will be too late and costly to go back and change something drastically. There are many facet and dimension of performance engineering - Attention should be paid to every layer of application components. It is becomes more important in multi-layered application development - database , web and application layer. Data volumes , concurrent user activities , parallelism possibilities and limitations thereof, code reviews and analysis from performance perspective are often ignored. Efficient coding (and SQLs) is one of the most important factor

Agreed sir. Performance engineering needs to be a pre-requisite from design itself to minimize performance bottlenecks moving forward towards development of the project application.

A performance bottleneck is any factor that reduces software efficiency, such as inefficient code, inadequate hardware, network issues, or external dependencies. - To identify these bottlenecks, use tools like profiling, tracing, logging, and testing. Profilers can pinpoint resource-heavy functions, while logging helps track errors over time. - Best practices involve regular testing under varied conditions and optimizing code based on performance data. For instance, quick transaction processing is vital in finance, and timely data retrieval can be lifesaving in healthcare. - Proactive monitoring and optimization are essential for improving performance across all fields.

Not all performance issues are equally significant; some have minimal impact on user experience, while others can severely hinder usability. - To prioritize these issues, evaluate their severity, frequency, impact, and the effort and risk involved in resolving them. - Frameworks like MoSCoW (Must have, Should have, Could have, Won't have) or ICE (Impact, Confidence, Ease) can help rank performance challenges systematically. For example, in a healthcare app, a bug causing delays in patient data retrieval is a "Must have" fix, whereas a cosmetic issue is a "Could have." This structured method ensures critical issues are addressed promptly, improving user satisfaction and business outcomes.

After identifying and prioritizing performance issues, develop and implement effective solutions based on the root causes. Consider optimizing code, upgrading hardware, configuring networks, or adjusting architecture. Use systematic approaches like PDCA or DMAIC to guide problem-solving. For instance, optimizing algorithms in healthcare software can improve data processing speed, while upgrading server capacity in eGov systems can enhance user access times. Always measure results and be prepared to iterate for continuous improvement. This structured method resolves issues and enhances overall system efficiency.

One of the performance issues that has been the culprit more times than not, are the reused functions that have been updated directly in the code and not the function itself. The potential issue may not have been updated in all the required places. Also, the function could be completely missing in some of the less used functionality. This is also a chance to rewrite for performance and update the documentation of the location for where the function resides.

After resolving a performance issue, it's essential to validate that your solution improves software performance without causing new problems. Use the same tools, like APM tools (e.g., New Relic, Dynatrace), to compare pre- and post-resolution metrics. Conduct load and stress testing to simulate real-world scenarios and assess scalability. Establish clear performance benchmarks and document results thoroughly. For best results, automate these tests within your CI/CD pipeline to maintain ongoing performance integrity.

To improve your software's performance, document and communicate changes effectively. Keep a detailed record of performance issues, prioritizations, and resolutions, such as optimized database queries with original and improved load times. Include performance criteria and benchmarks for transparency. Regularly share insights with stakeholders- clients, users, and team members to gather feedback and encourage collaboration. Use dashboards for real-time updates and project management tools to track progress. This approach builds trust and aligns efforts with stakeholder expectations, promoting continuous improvement.

After fixing the performance bottlenecks, testing and deploying, continuous monitoring should be an important factor, to ensure that the issue doesn't reoccur again.