Cache data fetched from remote services locally to reduce repeated network calls.
Gracefully handle slow network responses with appropriate timeouts and retry mechanisms.
Reduce the number of network requests, use efficient data serialization formats, and consider parallelizing independent requests.
If applicable, leverage multi-threading or multi-processing to utilize available CPU cores more effectively.
Employ CPU profiling to pinpoint functions or code sections that consume the most processing time and optimize them.
Use memory profiling tools to identify memory leaks or excessive memory usage and optimize data handling.
Cache frequently accessed data in memory to reduce the need for repeated disk or network access.
Implement asynchronous I/O operations to allow the program to perform other tasks while waiting for I/O to complete.
Group multiple small I/O operations into larger, fewer operations to reduce overhead.
Choose data structures that are optimized for the operations being performed, like using hash maps for fast lookups instead of linear searches.
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استكشف جلسات تشخيص حقيقية لهذه المشكلة مع سيناريوهات وحلول مختلفة.
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