Latency Principles

This skill provides a systematic framework for minimizing delay in software systems, covering the entire stack from Physics and Hardware to Application Architecture and User Experience.

1. Core Principles

Start here for theory and diagnosis.

• •references/principles.md: Definitions of Little's Law, Amdahl's Law, Tail Latency, and Coordinated Omission.
• •references/diagnostic_checklist.md: A checklist for identifying bottlenecks across Hardware, OS, and Runtime.

2. Optimization Strategies

Choose the strategy based on the bottleneck layer:

Data Layer (Storage & Access)

Problem: Database queries are slow, network round-trips are killing performance, or throughput is low. Solution: references/data_patterns.md

• •Colocation: Moving code to data (Edge/Kernel-bypass).
• •Partitioning: Sharding data to increase parallelism.
• •Caching: Storing hot data in memory (Strategies & Eviction policies).
• •Replication: Consistency models (Strong vs Eventual) and topologies.

Compute Layer (Processing Logic)

Problem: High CPU usage, lock contention, Garbage Collection pauses, or slow algorithms. Solution: references/compute_optimization.md

• •Eliminating Work: Better algorithms, Zero-copy serialization, Object pooling.
• •Wait-Free Sync: Replacing Mutexes with Atomics, Ring Buffers, and Lock-free structures.
• •Concurrency: Thread-per-core, Coroutines, and parallel execution models.

UX Layer (Hiding Latency)

Problem: The backend cannot be made faster, but the user experience feels sluggish. Solution: references/hiding_latency.md

• •Asynchronous Processing: Event loops, Non-blocking I/O, Request Hedging.
• •Predictive Techniques: Prefetching data, Optimistic UI updates, Speculative execution.

Decision Guide: Which technique to use?