Scaling

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: ...

Master capacity planning methodologies, resource forecasting techniques, and proactive scaling strategies to ensure your systems can handle growth while optimizing costs and maintaining performance.