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Kedify documentation

Kedify extends KEDA with HTTP, OpenTelemetry and predictive scalers, vertical scaling, and resource recommendations.

Goal Start here
Reduce compute waste or rightsize workloads Insights recommendations
Dynamically scale pod CPU and memory Vertical scaling
Scale queues, workers or application metrics Horizontal scaling
Scale idle workloads to zero Scale-to-zero & cold starts
Prepare for predictable traffic spikes Predictive or scheduled scaling
Scale across multiple clusters Distributed scaling
Scale a large Kubernetes cluster Multi-tenant KEDA and KPA
Prescale nodes dynamically Node capacity buffers
Scale AI inference HTTP routing · vLLM metrics

Run the quickstart or install with Helm. Already using KEDA? Migrate an existing installation and check KEDA, HPA and Kedify for controller ownership.

Section Contents
Install Requirements, Helm/GitOps, versions and restricted environments
Operate Dashboard, tenants, health checks, availability and tuning
Scaling Scalers, controllers and integration recipes
Insights Resource recommendations and FinOps
Best Practices Production configuration, reliability and tuning
Security & compliance Access, data boundaries, FIPS and SOC 2

Troubleshoot · All tasks · Reference