Prometheus + Grafana

What you'll learn

• Explain how Prometheus collects, stores and labels time-series metrics.
• Instrument applications with counters, gauges and histograms, and configure scraping and exporters.
• Write PromQL queries for rates, aggregations, percentiles and ratios, and save them as recording rules.
• Create actionable alerts and route them with Alertmanager.
• Build Grafana dashboards with variables and provision them as code.
• Run Prometheus reliably by controlling cardinality, retention and long-term storage.

Syllabus

Metrics and Prometheus Foundations

1. Metrics, Logs and Traces
2. How Prometheus Works
3. The Data Model

Metric Types and Instrumentation

1. Counters and Gauges
2. Histograms and Summaries
3. Instrumenting an Application

Collecting Metrics

1. Scrape Configuration
2. Exporters
3. Service Discovery and Relabelling

PromQL Fundamentals

1. Selectors and Matchers
2. rate, irate and increase
3. Aggregation

Advanced PromQL and Recording Rules

1. Percentiles With histogram_quantile
2. Binary Operators and Vector Matching
3. Recording Rules

Alerting

1. Alerting Rules
2. Alertmanager
3. Designing Good Alerts

Dashboards With Grafana

1. Data Sources and Panels
2. Variables and Dashboard Design
3. Dashboards as Code

Running Prometheus in Production

1. Cardinality
2. Storage, Retention and Scaling
3. RED and USE Methods
4. A Monitoring Checklist