Claude on AWS
Claude models from Anthropic are available on Amazon Bedrock as fully managed API endpoints. Running Claude in production means caring about three things: latency (how fast responses arrive), cost (what you pay per request), and reliability (how you handle failures). This section covers practical optimization techniques drawn from real production deployments.
Why Optimization Matters​
A naive Claude integration works fine in development. In production, the difference between an optimized and unoptimized setup can mean:
- 3-5x latency reduction through streaming, model routing, and prompt design
- 60-80% cost savings through prompt caching, token optimization, and model selection
- 99.9% reliability through proper retry logic, timeout configuration, and error handling
Performance Optimization​
Learn what drives Claude response times and how to reduce them.
- What Affects Claude Response Time - Input/output tokens, model selection, region, and prompt design
- Claude Model Selection Guide - When to use Haiku, Sonnet, or Opus
- Streaming vs Batch Response Patterns - Time-to-first-token and streaming implementation
- Common Claude Performance Pitfalls - Timeout errors, cold starts, and retry logic
Cost Optimization​
Understand Claude pricing and reduce your API spend.
- Anatomy of Claude API Costs - Token pricing, cost calculation, and provisioned throughput
- Prompt Caching for Cost Reduction - Cache hits, TTL, and cache-optimized prompt structure
- Token Optimization Techniques - Measuring usage, shorter prompts, and output control