Prometheus — Zero to Hero
Learn Prometheus from first principles to production operations. This course covers monitoring vs observability, metrics types, exporters, PromQL, Alertmanager, and Kubernetes integration with practical debugging and incident-driven scenarios.
Start Learning →Basics
Start with what monitoring means, why Prometheus exists, and how metric data is structured.
Monitoring Fundamentals
Monitoring vs observability, signals, SLIs, SLOs, and why teams instrument systems.
Introduction to Prometheus
What Prometheus is, where it fits, and why pull-based monitoring changed modern ops.
Metrics and Data Model
Counters, gauges, histograms, labels, time series, and cardinality basics.
Intermediate
Understand how Prometheus works internally, how it scrapes, and how to query data effectively.
Prometheus Architecture
Server, TSDB, exporters, service discovery, Alertmanager, and storage flow.
Data Collection (Scraping)
Scrape jobs, exporters, target discovery, relabeling, and scrape tuning.
Querying (PromQL Basics)
Instant vectors, range vectors, rates, aggregation, filtering, and joins.
Advanced
Move into actionable alerts and production-grade integrations, especially Kubernetes.
Alerting
Alert rules, Alertmanager, routing, inhibition, silencing, and noise reduction.
Integration (Kubernetes, Apps)
Prometheus Operator, ServiceMonitor, PodMonitor, kube-state-metrics, and app instrumentation.
Hands-on
Apply Prometheus in real incidents, fix broken metrics pipelines, and prepare for interviews.
Real-world Scenarios
CPU spikes, memory pressure, latency regression, and Kubernetes cluster health scenarios.
Troubleshooting
Why metrics are missing, why targets are down, and how to debug scraping and alerts.
Interview Preparation
Question bank covering monitoring theory, PromQL, exporters, and Kubernetes operations.