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Course Outline
Understanding Mastra Architecture and Operational Concepts for Government
- Core components and their production roles
- Supported integration patterns for enterprise environments for government
- Security and governance considerations for government operations
Preparing Environments for Agent Deployment for Government
- Configuring container runtime environments for government systems
- Preparing Kubernetes clusters for AI agent workloads in government settings
- Managing secrets, credentials, and config stores for secure government operations
Deploying Mastra AI Agents for Government
- Packaging agents for deployment in government environments
- Using GitOps and CI/CD for automated delivery in government agencies
- Validating deployments through structured testing for government compliance
Scaling Strategies for Production AI Agents for Government
- Horizontal scaling patterns for efficient resource utilization in government systems
- Autoscaling with HPA, KEDA, and event-driven triggers for government operations
- Load distribution and request-handling strategies for government applications
Observability, Monitoring, and Logging for AI Agents in Government
- Telemetry instrumentation best practices for government agencies
- Integrating Prometheus, Grafana, and logging stacks for government monitoring
- Tracking agent performance, drift, and operational anomalies for government systems
Optimizing Performance and Resource Efficiency in Government AI Agents
- Profiling agent workloads for government applications
- Improving inference performance and reducing latency for government operations
- Cost-optimization approaches for large-scale agent deployments in government agencies
Reliability, Resilience, and Failure Handling for Government AI Agents
- Designing for resiliency under load for government systems
- Implementing circuit-breaking, retries, and rate limiting in government operations
- Disaster recovery planning for agent-based systems in government agencies
Integrating Mastra into Enterprise Ecosystems for Government
- Interfacing with APIs, data pipelines, and event buses for government integration
- Aligning agent deployments with enterprise DevSecOps in government settings
- Adapting architectures to existing platform environments for government operations
Summary and Next Steps for Government Implementation
Requirements
- An understanding of containerization and orchestration techniques for government applications.
- Experience with CI/CD workflows in a public sector environment.
- Familiarity with concepts related to the deployment of AI models within governmental systems.
Audience
- DevOps engineers for government agencies.
- Backend developers working in public sector projects.
- Platform engineers responsible for managing AI workloads in government settings.
21 Hours
