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Course Outline
Advanced LangGraph Architecture for Government
- Graph topology patterns: nodes, edges, routers, subgraphs
- State modeling: channels, message passing, persistence
- DAG vs cyclic flows and hierarchical composition
Performance and Optimization
- Parallelism and concurrency patterns in Python for government applications
- Caching, batching, tool calling, and streaming to enhance performance
- Cost controls and token budgeting strategies for efficient resource management
Reliability Engineering
- Retries, timeouts, backoff, and circuit breaking to ensure robustness
- Idempotency and deduplication of steps to maintain data integrity
- Checkpointing and recovery using local or cloud stores for continuous operations
Debugging Complex Graphs
- Step-through execution and dry runs to identify issues early
- State inspection and event tracing to diagnose problems effectively
- Reproducing production issues with seeds and fixtures for thorough testing
Observability and Monitoring
- Structured logging and distributed tracing for transparency
- Operational metrics: latency, reliability, token usage to ensure service quality
- Dashboards, alerts, and SLO tracking for proactive management
Deployment and Operations
- Packaging graphs as services and containers for scalable deployment
- Configuration management and secrets handling to secure operations
- CI/CD pipelines, rollouts, and canaries for continuous improvement
Quality, Testing, and Safety
- Unit, scenario, and automated eval harnesses to ensure reliability
- Guardrails, content filtering, and PII handling to protect sensitive information
- Red teaming and chaos experiments for robustness to enhance security and resilience
Summary and Next Steps
Requirements
- An understanding of Python and asynchronous programming
- Experience with large language model (LLM) application development
- Familiarity with fundamental LangGraph or LangChain concepts
Audience for Government
- AI platform engineers
- DevOps professionals focused on AI solutions
- Machine learning architects responsible for production LangGraph systems
35 Hours
