Ross ROSS = Recommend OSS · open-source software intelligence for agents

kedacore/keda

KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes observed · 2026-08-28

github.com/kedacore/keda · homepage · Go · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

94/100

  • Activity 99
  • Release rhythm 83
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 39
  • age_days: 2759
  • days_rel: 33
  • days_push: 7
  • n_releases_24m: 14

Full methodology

Adoption not part of the score

10471 stars · 1491 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

KEDA is a Kubernetes-based event-driven autoscaler that scales any container workload based on the number of events needing processing, using a dedicated custom resource definition and 70+ built-in scalers. It acts as a Kubernetes Metrics Server, integrates with the Horizontal Pod Autoscaler, and supports scaling to and from zero.

Use cases

  • scale kubernetes deployments based on kafka queue depth
  • autoscale pods to zero when there is no traffic
  • scale workers based on rabbitmq or aws sqs queue length
  • event-driven autoscaling for kubernetes jobs
  • run and scale azure functions on kubernetes
  • replace manual hpa configuration with event-based scaling rules

When to choose

  • you need fine-grained, event-driven autoscaling including scale-to-zero for kubernetes workloads
  • you want to scale based on external event sources like queues, streams, databases, or cloud metrics
  • you need a vendor-agnostic scaler supporting many cloud providers and messaging systems
  • you want to run azure functions on kubernetes in production

When to avoid

  • you only need simple CPU/memory-based autoscaling, which the built-in HPA already handles
  • you are not running workloads on kubernetes
  • you need full serverless function platforms rather than scaling existing containers
  • you cannot add operators or CRDs to your cluster due to policy restrictions

Facets

service · maturity stable

monitoring deployment microservices cloud container-orchestration serverless cloud-computing infrastructure-as-code microservices cloud self-hosted go autoscaling event-driven kubernetes-operator hpa scale-to-zero cncf scalers metrics-server devops containers automation kubernetes docker

10 sources

Member repositories

RepositoryRoleHealth v2
kedacore/kedamain94

For agents

markdown · JSON · MCP: product_card(name="kedacore/keda")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem