News

Proactive Autoscaling for Edge Applications in Kubernetes

Infoq

Kubernetes often reacts too late when traffic suddenly increases at the edge. A proactive scaling approach that considers response time, spare CPU capacity, and container startup delays can add or remove instances more smoothly, prevent sudden spikes, and keep performance stable on systems with limited resources.

Visit Site

Proactive Autoscaling for Edge Applications in Kubernetes
Kubernetes Operators in DepthInfoq Grab Redesigns Counter Service Storage for 50% Lower P99 LatencyInfoq The Async Multiprocessing Has Sound Foundations in Linux, But Further Testing is NeededInfoq AI Agents with Cloud Credentials Are Outrunning Billing Guardrails Built for Human-Speed MistakesInfoq How to Develop Software Engineering Skills in the Age of AIInfoq CodeGuardian: a Model Context Protocol Server for AI-Assisted Code Quality Analysis and SecurityInfoq Local Kubernetes Development Using Minikube and Redis EnterpriseRedis How Argo CD and OpenShift Enable GitOps for DevelopersThenewstack Google Anthos from the Eyes of a Kubernetes DeveloperThenewstack Security Considerations for API-Driven Apps Deployed to CloudThenewstack AWS Enterprise Container Management with PulumiPulumi Supporting Kubernetes with Faster, Easier Test EnvironmentsPulumi Neo Integrations: MCP Servers and Cloud CLIsPulumi KAUST and Cerebras Named Gordon Bell Award Finalist for Solving Multi-Dimensional SeismicCerebras Docker for Windows Desktop with KubernetesDocker Bringing More Power To Edge Rules! Introducing Variable ExpansionBunny .NET zero-code instrumentationOpentelemetry Be the Hero in Your Real-Life Cyber Heist ScriptThenewstack Siloscape: Windows Malware That Breaks KubernetesThenewstack Breakdown: The Kubernetes-Run AI Video Generation Pipeline for NIUS.TVThenewstack