Start with Monitoring and Profiling Analyze system logs: Review logs for error patterns, latency spikes, or unusual behavior. Use profiling tools: Tools like Xcode Instruments (iOS), Chrome DevTools (web), or React DevTools can help pinpoint performance bottlenecks in code. Database Optimization Optimize queries: Review SQL queries for inefficiencies, such as unnecessary joins, missing indexes, or non-optimized WHERE clauses. Indexing: Ensure proper indexing on frequently queried columns. Caching: Use caching mechanisms (e.g., Redis or Memcached) to reduce database load for repetitive queries.

Deal with software performance issues isn’t easy. Without a clear process, it can quickly become a frustrating and endless journey Here are my tips to handle perf challenges effectively: -Define the issue: Understand the symptoms -Measure: Use the right tools to gather and analyze data -Analyze: Go beyond surface-level results. Dive into logs to fully grasp what’s happening across the flow -Prioritize: Focus on the most impactful issues first -Optimize: fixes, improve algorithms, use caching, scale and most important, ensure your data model aligns with both your business logic and your database’s strengths -Test and iterate: Re-test to confirm improvements A structured approach can save time, reduce frustration, and deliver better results!

Review the system front to back to understand problem areas and then work on quick fix/ solution In my experience some of the primary reasons I have come across are: 1. Data Growth - Query performance 2. Server Configuration - # of transactions that the server/ cluster can handle 3. Design - e.g. Identifying areas for async communication 4. Network Hops - Batch/ Cache to handle repeated database/ filesystem calls Once the area(s) are identified look for quick wins/solutions and create a plan to address these areas. The process and messaging are key to ensure stakeholders understand the cause and remediation plan. - Incorporate performance testing & memory analysis - Tooling for log analysis to have proactive data in perf degradation

Measure, understand, fix, repeat. Spot the Problem First, catch the symptoms. Is everything slow? Where exactly does it hurt? Get the Evidence Grab your performance tools. Track down exactly where things are breaking. Dig Deep Don't just look at the surface. Logs and traces are your best friends. They tell the real story. Attack Strategically Focus on what kills performance most: Ugly database queries Memory hogs Stupid code loops Quick Wins Matter Cache smartly Rewrite nasty algorithms Sometimes less code is faster code Test Everything

Analyzing software performance doesn’t have to be overly complex if we can identify where the thread begins and methodically unwind the program to locate all the bottlenecks. Since performance is typically tied to execution time, I’ll focus on identifying the most time-intensive sections of my code and optimizing them. Debugging becomes more challenging when working with multithreaded applications. In such cases, I recommend logging the execution time of individual methods or code blocks. This approach helps pinpoint the critical areas that need attention.