Course Outline

Introduction to Large-Scale Monitoring

  • Challenges of monitoring in high-traffic environments
  • Scaling strategies for Prometheus and Grafana
  • Architectural considerations for distributed systems

Scaling Prometheus

  • Setting up Prometheus in a sharded environment
  • Using Prometheus federation for large-scale systems
  • Implementing Prometheus storage optimizations

Optimizing Grafana for Large Environments

  • Configuring Grafana for handling large datasets
  • Improving dashboard performance and loading times
  • Best practices for complex visualizations

Distributed Monitoring with Prometheus and Grafana

  • Integrating Prometheus with distributed tracing tools
  • Monitoring microservices in Kubernetes environments
  • Advanced alerting and notification strategies

Managing High Availability

  • Setting up redundant Prometheus and Grafana instances
  • Failover strategies for monitoring systems
  • Ensuring data consistency and reliability

Troubleshooting and Debugging

  • Identifying and resolving performance bottlenecks
  • Debugging PromQL queries and dashboard configurations
  • Common pitfalls in large-scale monitoring

Advanced Integrations

  • Integrating Prometheus and Grafana with external databases
  • Using Grafana plugins for enhanced functionality
  • Leveraging third-party tools for extended monitoring

Summary and Next Steps

Requirements

  • Strong understanding of Prometheus and Grafana basics
  • Experience with Linux system administration
  • Familiarity with distributed system architectures

Audience

  • DevOps engineers
  • Site Reliability Engineers (SREs)
 14 Hours

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  • Format: Online (live), In-company (at your offices), or Hybrid.
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