Justin Harms
3703e40442
- Introduced multiple new markdown files detailing caching patterns, configuration management, development workflows, Go language conventions, HTTP proxy patterns, logging and monitoring practices, performance optimization guidelines, project structure, security validation, and VFS architecture. - Each document outlines best practices, patterns, and guidelines to enhance the understanding and implementation of various components within the SteamCache2 project. - This documentation aims to improve maintainability, facilitate onboarding for new contributors, and ensure consistent application of coding and architectural standards across the codebase.
71 lines
2.3 KiB
Plaintext
71 lines
2.3 KiB
Plaintext
---
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description: Performance optimization guidelines
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---
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# Performance Optimization Guidelines
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## Memory Management
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- Use appropriate data structures for the use case
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- Implement proper cleanup for long-running services
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- Monitor memory usage and implement limits
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- Use memory pools for frequently allocated objects
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## I/O Optimization
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- Use buffered I/O for better performance
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- Implement connection pooling for HTTP clients
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- Use appropriate buffer sizes (64KB for HTTP)
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- Minimize system calls and context switches
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## Concurrency Patterns
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- Use worker pools for CPU-intensive tasks
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- Implement proper backpressure with semaphores
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- Use channels for coordination between goroutines
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- Avoid excessive goroutine creation
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## Caching Strategies
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- Use tiered caching (memory + disk) for optimal performance
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- Implement intelligent cache eviction policies
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- Use cache warming for predictable access patterns
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- Monitor cache hit ratios and adjust strategies
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## Network Optimization
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- Use HTTP/2 when available
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- Enable connection keep-alives
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- Use appropriate timeouts for different operations
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- Implement request coalescing for duplicate requests
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## Data Structures
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- Choose appropriate data structures for access patterns
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- Use sync.RWMutex for read-heavy operations
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- Consider lock-free data structures where appropriate
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- Minimize memory allocations in hot paths
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## Algorithm Selection
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- Choose GC algorithms based on access patterns
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- Use LRU for general gaming workloads
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- Use LFU for gaming cafes with popular content
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- Use Hybrid algorithms for mixed workloads
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## Monitoring and Profiling
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- Implement performance metrics collection
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- Use structured logging for performance analysis
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- Monitor key performance indicators
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- Profile the application under realistic loads
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## Resource Management
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- Implement proper resource cleanup
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- Use context.Context for cancellation
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- Set appropriate limits on resource usage
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- Monitor resource consumption over time
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## Scalability Considerations
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- Design for horizontal scaling where possible
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- Use sharding for large datasets
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- Implement proper load balancing
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- Consider distributed caching for large deployments
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## Bottleneck Identification
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- Profile the application to identify bottlenecks
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- Focus optimization efforts on the most critical paths
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- Use appropriate tools for performance analysis
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- Test performance under realistic conditions |