Prometheus & Grafana – Advanced Course in Chennai

Module 1: Observability Fundamentals and Prometheus

• Three pillars of observability: metrics, logs, and traces
• Prometheus architecture: server, exporters, Alertmanager, and Pushgateway
• Prometheus data model: time series, metrics types, and labels
• Installing Prometheus with Docker and Kubernetes Helm chart

Module 2: PromQL – Prometheus Query Language

• Instant vectors, range vectors, and scalar values
• Metric selectors: label matching and regex filters
• Aggregation operators: sum, avg, max, min, and count by label
• Functions: rate, irate, increase, histogram_quantile, and predict_linear

Module 3: Instrumentation and Exporters

• Prometheus metric types: counter, gauge, histogram, and summary
• Instrumenting applications: Python, Java, and Go client libraries
• Node Exporter for Linux host metrics
• Popular exporters: MySQL, PostgreSQL, Redis, and Blackbox Exporter

Module 4: Kubernetes Monitoring with kube-prometheus-stack

• kube-prometheus-stack: Prometheus Operator, Grafana, and Alertmanager
• ServiceMonitor and PodMonitor CRDs for automatic scrape configuration
• Kubernetes metrics: kube-state-metrics and metrics-server
• cAdvisor for container resource usage monitoring

Module 5: Alertmanager and Alert Rules

• Prometheus alerting rules: expressions, severity, and annotations
• Alertmanager configuration: routes, receivers, and inhibition rules
• Notification channels: Slack, PagerDuty, email, and OpsGenie
• Silences and alert grouping for noise reduction

Module 6: Grafana Fundamentals

• Grafana architecture: data sources, dashboards, and alerting
• Connecting Grafana to Prometheus, Loki, and other data sources
• Dashboard building: panels, visualisations, and variables
• Grafana Explore: ad-hoc metric and log querying

Module 7: Grafana Advanced Features

• Grafana Loki: log aggregation and LogQL query language
• Grafana Tempo: distributed tracing backend and TraceQL
• Grafana alerting: unified alerting rules and notification policies
• Grafana dashboards as code: provisioning with JSON and Terraform

Module 8: Capstone Project and Assessment

• Full observability stack deployment: Prometheus, Grafana, and Loki
• Custom application instrumentation and dashboard build
• Alerting rules and Alertmanager notification pipeline project
• Final assessment and course certification

Experience in the Industry Gain expertise from site reliability engineers who have built production monitoring and observability stacks using Prometheus and Grafana for cloud-native applications, Kubernetes clusters, and microservices at scale.

Backgrounds at the Top Our Prometheus and Grafana trainers have operated monitoring platforms at technology companies and SRE teams managing high-availability systems where observability is critical for incident detection and resolution.

Clear & Effective Teaching Prometheus architecture, PromQL, exporters, Kubernetes monitoring, Alertmanager, Grafana dashboards, Loki log aggregation, and Tempo distributed tracing are taught with real observability stack examples.

Hands-On Learning Focus Students deploy the full Prometheus and Grafana stack, write PromQL queries, instrument applications, build dashboards, configure alerting, and set up Loki log analysis through structured lab exercises.

Up-to-Date Knowledge Trainers keep content current with the latest Prometheus and Grafana releases, Grafana Cloud features, OpenTelemetry integration, and evolving cloud-native observability best practices.