KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.
Zoomies is a lightweight, self-hosted GitHub Actions runner fleet controller. Ephemeral runners by default, GitHub App auth, webhook-driven autoscaling, multi-host agents, a polished live web UI, and a one-line interactive installer. Single Go binary, SQLite, no Kubernetes.
Diskless Kafka® on S3. 10x Cost-Effective. No Cross-AZ Traffic Cost. Autoscale in seconds. Single-digit ms latency. Multi-AZ Availability.
Get your resource requests "Just Right"
Docker-native control plane for autoscaling ephemeral CI runners on a single host—without Kubernetes.
A local emulator of the Scaleway, Outscale and Exoscale APIs. Their own official CLIs drive it end to end, Terraform and OpenTofu drive two of the three — no cloud account, no cloud credentials, nothing billed.
Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.
Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
Kubernetes-based, scale-to-zero, request-driven compute
Ultrafast serverless GPU inference, sandboxes, and background jobs
Open Security Controls Assessment Language (OSCAL)
Add-on for KEDA to scale HTTP workloads
Best-effort high availability for single-replica Kubernetes workloads: no downtime from announced node disruptions (drains, upgrades, consolidation, spot reclaims) without a standing second replica.
AI Inference Operator for Kubernetes. The easiest way to serve ML models in production. Supports VLMs, LLMs, embeddings, and speech-to-text.
Terraform On AWS for EC2, VPC, ASG, ALB, CLB, NLB, CloudWatch, SNS, S3, CodePipeline, ACM, Route53
Kubernetes Cluster Proportional Autoscaler Container
OpenSearch Kubernetes Operator
General purpose metrics adapter for Kubernetes HPA metrics
Deployment & experimentation of LLM inference at production scale (P/D disaggregation, KV offloading, parallelism, and autoscaling).
Autoscaling components for Kubernetes
Tortoise: Shell-Shockingly-Good Kubernetes Autoscaling