Performance and Monitoring for GenAI

Fast and observed: latency-optimized inference, parallelism and streaming, retrieval-index tuning, sampling-parameter effects, GenAI-aware auto scaling, and monitoring from token usage and hallucination rates to multi-agent coordination.

Content current as of 2026-10.

Lessons

1. Latency engineering for LLM workloads
2. Scaling for GenAI traffic patterns
3. Observing GenAI: tokens, hallucination rates, agent traces

Sources

• AIP-C01 exam guide — Content Domain 4 (tasks 4.1–4.3)
• Amazon Bedrock user guide — optimize model inference for latency
• Amazon Bedrock user guide — runtime CloudWatch metrics
• Amazon CloudWatch user guide — generative AI observability