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.

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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

Deploying KEDA

There are many ways to deploy KEDA including Helm, YAML files, and the Azure Functions Core Tools.

Documentation

Interested to learn more? Head over to keda.sh.

FAQ

You can find a FAQ here with some common questions.

Samples

You can find several samples for various event sources here

Community

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

• Meeting time: Weekly Thurs 18:00 UTC. (Subscribe to Google Agenda | Convert to your timezone)*
• Zoom link: https://zoom.us/j/150360492
• Meeting agenda: https://hackmd.io/s/r127ErYiN

Just want to learn or chat about KEDA? Feel free to join the conversation in #KEDA on the Kubernetes Slack!

Building: Quick start with Visual Studio Code Remote - Containers

This helps you pull and build quickly - dev containers launch the project inside a container with all the tooling required for a consistent and seamless developer experience.

This means you don't have to install and configure your dev environment as the container handles this for you.

To get started install VSCode and the Remote Containers extensions

Clone the repo and launch code:

git clone [email protected]:kedacore/keda.git
cd keda
code .

Once VSCode launches run CTRL+SHIFT+P -> Remote-Containers: Reopen in container and then use the integrated terminal to run:

make build

Note: The first time you run the container it will take some time to build and install the tooling. The image will be cached so this is only required the first time.

Building: Locally directly

This project is using Operator SDK framework, make sure you have installed the right version. To check the current version used for KEDA check the RELEASE_VERSION in file tools/build-tools.Dockerfile.

git clone [email protected]:kedacore/keda.git
cd keda
make build

Deploying Custom KEDA

If you want to change KEDA's behaviour, or if you have created a new scaler (more docs on this to come) and you want to deploy it as part of KEDA. Do the following:

1. Make your change in the code.
2. In terminal, create an environment variable IMAGE_TAG and assign it a value for your preference, this tag will be used when creating the operator image that will run KEDA. Note: make sure it doesn't clash with the official tags of KEDA containers in DockerHub.
3. Still in terminal, run make build at the root of the source code. This will also build the docker image for the KEDA operator that you can deploy to your local cluster. This should build 2 docker images: kedacore/keda and kedacore/keda-metrics-adapter tagged with the tag you set in step 2
4. If you haven't downloaded them before, clone the charts repository: git clone [email protected]:kedacore/charts.git
5. Still in terminal, navigate to the chart/keda folder (downlodaed in step 4), and run the following command (don't forget to replace the placeholder text in the command) helm install . --set image.keda=kedacore/keda:$IMAGE_TAG,image.metricsAdapter=kedacore/keda-metrics-adapter:$IMAGE_TAG,image.pullPolicy=IfNotPresent. This will use the images built at step 3. Notice the need to override the image pullPolicy to IfNotPresent in order to use the locally built images and not try to pull the images from remote repo on Docker Hub (and complain about not finding them).
6. Once the keda operator pod is up, check the logs of both containers to verify everything running ok, eg: kubectl logs <keda operator pod name> -c keda-operator-metrics-apiserver and kubectl logs <keda operator pod name> -c keda-operator

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 [email protected] with any additional questions or comments.