prometheus-configuration

Prometheus scrape configuration defines how the monitoring system discovers and collects metrics from targets. You define scrape_configs in prometheus.yml with target addresses, ports, and service discovery methods (static IPs, Kubernetes SD, file-based discovery) to automatically collect metrics at regular intervals from your applications and infrastructure.

Yes, Prometheus supports Kubernetes service discovery natively. Configure kubernetes_sd_config in your scrape_configs to automatically detect and monitor pods and services across your cluster, eliminating the need to manually manage target lists as your infrastructure scales.

Alerting rules in Prometheus evaluate metric conditions and fire alerts when thresholds are breached. Define rules in YAML files referencing your rule_files configuration, then integrate with Alertmanager to route notifications. Rules support complex queries for events like service downtime or resource exhaustion.

Recording rules pre-compute and store frequently-used metric queries as new time series. They optimize query performance and simplify complex expressions, reducing computational overhead during dashboard queries and alert evaluation on large-scale monitoring deployments.

Yes, Prometheus supports TLS credentials in scrape configurations for encrypted metric collection from applications. Configure tls_config in scrape_configs with certificate files to securely authenticate and collect metrics over HTTPS from protected endpoints.

Prometheus deployment varies by environment: use Helm charts for Kubernetes clusters, docker-compose manifests for containerized stacks, and direct YAML configuration for bare-metal servers. Each environment requires adjusting service discovery methods and networking configuration in prometheus.yml to match your infrastructure topology.