True Scale-to-Zero with Intelligent Wake-Up Proxy
1-5 second cold starts • 100% memory reduction for idle services
Modern Kubernetes platforms deploy hundreds of microservices, but most organizations run them always-on even when traffic is sparse or unpredictable, wasting 30-65% of compute budget on idle containers delivering no business value.
HPA keeps minimum replicas running. Serverless introduces lock-in and variable cold starts. Knative adds complexity. No production-ready pattern exists for true scale-to-zero with predictable wake-up.
Average clusters run at 13-25% utilization. Internal tools and low-traffic services kept warm 24/7 represent $50K-$500K annual waste depending on cluster size and cloud pricing.
Kubernetes-native solution combining KEDA scale-to-zero, API-driven wake-up proxy, and activation catalogue. Zero vendor lock-in, sub-5s cold starts, seamless integration.
ScaledObjects drive true scale-to-zero using standard Kubernetes and KEDA. Idle workloads consume zero CPU/memory when not serving traffic.
Simple HTTP API (wake/app) patches KEDA and deployments, coordinates readiness, then hands control back to autoscaling. 1-5s from trigger to first request.
Web portal lists applications with status. Users trigger wake-up then access service without kubectl or cluster access. ITSM/portal integration ready.
Runs on any CNCF-conformant cluster. No proprietary platforms, per-invocation billing, or serverless runtimes. Portable across on-prem, private cloud, managed K8s.
100% memory/CPU reduction for dormant services. Turn always-on microservices into on-demand workloads aligned with actual business demand.
1-5 second cold starts keep within UX thresholds (0.1s instant, 1s uninterrupted, 10s acceptable). Full autoscaling preserved during active periods.
Standard Kubernetes + open-source KEDA. No proprietary serverless platforms or per-invocation pricing. Works with existing observability/ITSM investments.
Production-ready Kubernetes pattern cutting TCO while preserving SLAs
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CxOs • Platform Engineering • FinOps • SRE teams
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