Course Outline

Introduction to Scaling Ollama for Government

  • Ollama’s architecture and key considerations for scaling in government environments
  • Common bottlenecks encountered in multi-user deployments within the public sector
  • Best practices for ensuring infrastructure readiness for government operations

Resource Allocation and GPU Optimization for Government

  • Strategies for efficient CPU/GPU utilization tailored to government needs
  • Memory and bandwidth considerations in public sector deployments
  • Implementing container-level resource constraints for enhanced performance and security

Deployment with Containers and Kubernetes for Government

  • Containerizing Ollama using Docker for government applications
  • Running Ollama in Kubernetes clusters to support scalable and secure operations
  • Implementing load balancing and service discovery for reliable public sector services

Autoscaling and Batching for Government

  • Designing autoscaling policies to optimize resource usage in government systems
  • Batch inference techniques to enhance throughput for government applications
  • Evaluating latency versus throughput trade-offs in public sector environments

Latency Optimization for Government

  • Profiling inference performance to identify and address bottlenecks in government systems
  • Caching strategies and model warm-up techniques for improved efficiency
  • Reducing I/O and communication overhead to enhance performance in public sector deployments

Monitoring and Observability for Government

  • Integrating Prometheus for comprehensive metrics collection in government infrastructure
  • Building custom dashboards with Grafana to monitor Ollama’s performance in the public sector
  • Implementing alerting and incident response mechanisms for robust Ollama infrastructure management

Cost Management and Scaling Strategies for Government

  • Strategies for cost-aware GPU allocation in government IT environments
  • Evaluating cloud versus on-premises deployment options for optimal resource utilization
  • Developing sustainable scaling strategies to support long-term public sector operations

Summary and Next Steps for Government

Requirements

  • Experience with Linux system administration for government environments
  • Understanding of containerization and orchestration technologies
  • Familiarity with the deployment of machine learning models

Audience

  • DevOps engineers in public sector organizations
  • Machine learning infrastructure teams for government agencies
  • Site reliability engineers supporting federal systems
 21 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories