Best-Practices

Modern cloud-native applications demand intelligent scaling that goes beyond simple CPU and memory metrics. KEDA (Kubernetes Event-Driven Autoscaling) revolutionizes how we scale workloads by enabling event-driven autoscaling based on external metrics like message queue depth, API response times, and custom application metrics. This comprehensive guide explores production-ready KEDA implementations for two critical use cases: Kafka consumer lag scaling and REST API workload scaling. Prerequisites Before implementing KEDA autoscaling, ensure you have: ...

Site Reliability Engineers face a fundamental challenge: monitoring complex distributed systems without drowning in metrics noise. Google’s Golden Four signals provide a battle-tested framework for focusing on what truly matters for service reliability. In this comprehensive guide, we’ll walk through practical implementations using Prometheus, Grafana, and Datadog, complete with production-ready configurations and real-world examples. Prerequisites Before diving into implementations, ensure you have: Basic understanding of Kubernetes and container orchestration Familiarity with Prometheus metrics and PromQL queries Access to a Kubernetes cluster (kind, minikube, or cloud-managed) Basic knowledge of HTTP status codes and API design principles Estimated implementation time: 2-4 hours depending on your existing monitoring setup. ...