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Kubernetes-based Event Driven Autoscaling

KEDA allows for fine grained autoscaling (including to/from zero) for event driven Kubernetes workloads. KEDA serves as a Kubernetes Metrics Server and allows users to define autoscaling rules using a dedicated Kubernetes custom resource definition.

KEDA can run on both the cloud and the edge, integrates natively with Kubernetes components such as the Horizontal Pod Autoscaler, and has no external dependencies.

📢 Experimental Phase - Please note this software is experimental and should not be used for anything resembling a production workload. We want to create KEDA in the open with the community to bring event driven scale to Kubernetes.

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In partnership with

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Getting started

• QuickStart - RabbitMQ and Go
• QuickStart - Azure Functions and Queues
• QuickStart - Azure Functions and Kafka on Openshift 4

FAQ

You can find a FAQ here with some common questions.

Setup

Deploying with a Helm chart

Add Helm repo

helm repo add kedacore https://kedacore.azureedge.net/helm

Update Helm repo

helm repo update

Install keda-edge chart

helm install kedacore/keda-edge --devel --set logLevel=debug --namespace keda --name keda

Install keda-edge chart with ARM image

helm install kedacore/keda-edge --devel --set logLevel=debug --namespace keda --name keda --set image.tag=arm

Deploying with the Azure Functions Core Tools

func kubernetes install --namespace keda

Deploying using the deploy yaml

If you want to try KEDA on minikube or a different Kubernetes deployment without using Helm, you can deploy the yaml under the /deploy directory.

kubectl apply -f KedaScaleController.yaml

How KEDA works

KEDA performs two key roles within Kubernetes. First, it acts as an agent to activate and deactivate a deployment to scale to and from zero on no events. Second, it acts as a Kubernetes metrics server to expose rich event data like queue length or stream lag to the horizontal pod autoscaler to drive scale out. It is up to the deployment to then consume the events directly from the source. This preserves rich event integration and enables gestures like completing or abandoning queue messages to work out of the box.

Event sources and scalers

KEDA has a number of "scalers" that can both detect if a deployment should be activated or deactivated, and feed custom metrics for a specific event source. Today there is scaler support for:

• AWS CloudWatch
• AWS Simple Queue Service
• Azure Event Hub
• Azure Service Bus Queues and Topics
• Azure Storage Queues
• GCP PubSub
• Kafka
• Liiklus
• Prometheus
• RabbitMQ
• Redis Lists

You can view other planned scalers in our wiki and issue backlog.

ScaledObject custom resource definition

In order to sync a deployment with an event source, a ScaledObject custom resource needs to be deployed. The ScaledObject contains information on the deployment to scale. ScaledObjects contain information on the deployment to scale, metadata on the event source (e.g. connection string secret, queue name), polling interval, and cooldown period. The ScaledObject will result in corresponding autoscaling resource (HPA definition) to scale the deployment. When ScaledObjects get deleted, the corresponding HPA definition is cleaned up.

ScaledObject examples and schemas can be found here.

HTTP scaling integration

KEDA enables scaling based on event sources where the event resides somewhere to be pulled. For events like HTTP where the event is pushed to the container, KEDA works side by side with HTTP scale-to-zero components like Osiris or Knative serving. By pairing KEDA with an HTTP scale-to-zero component you can provide rich event scaling for both HTTP and non-HTTP.

Azure Functions Integration

While KEDA can be used with any container or deployment, the Azure Functions tooling natively integrates with KEDA for a seamless developer experience and event-driven programming model. With functions, developers only need to write the code that should run on an event, and not have to worry about the event consuming scaffolding. Azure Functions is open source, and all of the existing tooling and developer experience works regardless of the hosting option.

You can containerize and deploy an existing or new Azure Function using the Azure Functions core tools

func kubernetes deploy --name my-function --registry my-container-registry

Using Azure Functions with KEDA and Osiris

Samples

Samples and blog posts

Community Standup

If interested in contributing or participating in the direction of KEDA, you can join our community meetings.

Meeting time: Weekly Thurs 17:00 UTC. Convert to your timezone. Zoom link: https://zoom.us/j/150360492
Meeting agenda: https://hackmd.io/s/r127ErYiN

Building

git clone git@github.com:kedacore/keda.git
cd keda
make build
./dist/keda

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.