Prometheus is an open source time series database for systems monitoring and alerting. It is decoupled from a larger infrastructure, making it a reliable tool to diagnose problems immediately during an outage.
This instructor-led, live training (online or onsite) is aimed at system administrators and DevOps engineers who wish to use Prometheus to monitor systems and applications natively or through highly dynamic microservices running in a cloud environment.
By the end of this training, participants will be able to:
- Install and configure Prometheus.
- Understand the features, architecture, and core concepts of Prometheus.
- Learn how to query data using PromQL.
- Build visualizations and dashboards with Grafana.
- Configure systems monitoring and alerting rules.
- Analyze and optimize systems and application performance.
- Enable secure integration to remote endpoints and existing systems.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
- Programming experience (preferably in Go or Python)
- Experience with Linux command line
- System administrators
- DevOps engineers
- Prometheus vs Graphite vs InfluxDB
- Overview of Prometheus features and architecture
- Prometheus data model and metrics
- Installing and configuring Prometheus
- Basic query operations (PromQL)
- Use cases and examples
- Navigating the UI
Monitoring and Alerting
- Recording and alerting rules
- Instrumenting codes
- Pushing metrics (Pushgateway)
- Node and WMI exporters
- Configuring Alertmanager
- Managing alerts
Visualization with Grafana
- Setting up Grafana
- Creating a Prometheus data source
- Using default dashboards
- Customizing dashboards
Security, Integrations, and Optimization
- Prometheus security model
- Authentication, authorization, and encryption
- API management
- Federation and HTTP service discovery
- Remote write tuning parameters
- Optimizing data and systems usage
Summary and Next Steps