This document outlines the standards and best practices for environmentally sustainable software development at Bayat.
- Carbon Efficiency: Emit the least carbon possible
- Energy Efficiency: Use the least amount of energy possible
- Carbon Awareness: Do more when the electricity is cleaner
- Hardware Efficiency: Use the least amount of hardware possible
- Measurement: What you can't measure, you can't improve
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Algorithm Optimization:
- Prefer algorithms with lower computational complexity
- Reduce unnecessary iterations and operations
- Use appropriate data structures to minimize processing
- Implement lazy loading and lazy computation patterns
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Resource Management:
- Implement efficient memory usage patterns
- Release resources promptly when no longer needed
- Minimize network calls and data transfers
- Optimize database queries and data access patterns
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Idle Resources:
- Implement sleep modes for inactive components
- Scale down or shut down unused services
- Use event-driven architecture to minimize polling
- Implement efficient background processing
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Energy-Aware UX:
- Design dark mode interfaces by default
- Minimize animations and transitions on battery-powered devices
- Implement reduced motion and low-power modes
- Design interfaces that require fewer interactions to complete tasks
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Network Efficiency:
- Implement effective caching strategies
- Compress data for transmission
- Use efficient data formats (JSON vs. XML, Protocol Buffers, etc.)
- Batch API requests to reduce connection overhead
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Sustainable Design Patterns:
- Implement pagination to limit data processing
- Use virtualization for large data sets
- Implement incremental loading patterns
- Design for offline-first where appropriate
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Right-sizing:
- Guidelines for appropriate instance sizing
- Auto-scaling configuration best practices
- Scheduling for non-production environments
- Serverless vs. container vs. VM selection criteria
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Region Selection:
- Criteria for selecting regions with lower carbon intensity
- Multi-region strategy considering energy sources
- Data locality to reduce transmission energy
- Carbon-aware deployment strategies
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Data Lifecycle:
- Data retention policies to minimize storage
- Tiered storage strategies for energy efficiency
- Data compression and deduplication requirements
- Archive guidelines for rarely accessed data
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Database Optimization:
- Index optimization standards
- Partitioning strategies for efficient queries
- Connection pooling requirements
- Read replica usage guidelines
- Tools and methodologies for measuring software carbon intensity
- Required metrics for application carbon footprint
- Benchmarking standards for energy consumption
- Dashboard requirements for environmental impact
- Periodic energy consumption reporting
- Carbon reduction goal setting
- Efficiency improvements tracking
- Environmental impact documentation
- Energy profiling requirements
- Hotspot identification methodology
- Energy debt tracking (similar to technical debt)
- Optimization priority framework
- Green software review checklist
- Energy efficiency considerations in code reviews
- Team KPIs for sustainable development
- Knowledge sharing requirements
- Recommended profiling tools for energy consumption
- Static analysis tools for identifying inefficient patterns
- Performance monitoring tools with energy metrics
- Carbon-aware development plugins
- Carbon-aware schedulers and deployment tools
- Energy monitoring and reporting platforms
- Infrastructure optimization tools
- Carbon intensity APIs and integrations
- Alignment with Green Software Foundation principles
- Compliance with energy efficiency regulations
- Sustainable software certification requirements
- Reporting standards for environmental impact
- Minimum efficiency requirements for production deployment
- Energy budgets for applications and services
- Green software maturity model
- Environmental impact statement guidelines