November 7, 2019

1132 words 6 mins read



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

repo name kedacore/keda
repo link
language Go
size (curr.) 12628 kB
stars (curr.) 1814
created 2019-02-13
license MIT License

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.

We are a Cloud Native Computing Foundation (CNCF) sandbox project. CNCF Logo

Getting started

Deploying KEDA

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


Interested to learn more? Head over to


You can find a FAQ here with some common questions.


You can find several samples for various event sources here.


You can find the latest releases here


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

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
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
cd keda
make build

If the build process fails due to some “checksum mismatch” errors, make sure that GOPROXY and GOSUMDB environment variables are set properly. With Go installation on Fedora, for example, it could happen they are wrong.


If not set properly you can just run.

go env -w GOPROXY=,direct

Deploying: Custom KEDA locally outside cluster

The Operator SDK framework allows you to run the operator/controller locally outside the cluster without a need of building an image. This should help during development/debugging of KEDA Operator or Scalers.

Note: This approach works only on Linux or macOS.

To be KEDA to be fully operational we need to deploy Metrics Server first.

  1. Deploy CRDs and KEDA into keda namespace

    kubectl apply -f deploy/crds/keda.k8s.io_scaledobjects_crd.yaml
    kubectl apply -f deploy/crds/keda.k8s.io_triggerauthentications_crd.yaml
    kubectl apply -f deploy/
  2. Scale down keda-operator Deployment

    kubectl scale deployment/keda-operator --replicas=0 -n keda
  3. Run the operator locally with the default Kubernetes config file present at $HOME/.kube/config and change the operator log level via --zap-level= if needed

    operator-sdk run --local --namespace="" --operator-flags="--zap-level=info"

    Note: On older operator-sdk versions you need to use command up instead of run.

    Note: Please run operator-sdk -h to see all possible commands and options (eg. for debugging: --enable-delve)

Deploying: Custom KEDA as an image

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 VERSION 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
  5. Still in terminal, navigate to the charts/keda folder (downloaded 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:$VERSION,image.metricsAdapter=kedacore/keda-metrics-adapter:$VERSION,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 pods are up, check the logs to verify everything running ok, eg:
    kubectl get pods --no-headers -n keda | awk '{print $1}' | grep keda-operator | xargs kubectl -n keda logs -f
    kubectl get pods --no-headers -n keda | awk '{print $1}' | grep keda-metrics-apiserver | xargs kubectl -n keda logs -f

Setting log levels

You can change default log levels for both KEDA Operator and Metrics Server. KEDA Operator uses Operator SDK logging mechanism.

KEDA Operator logging

Find --zap-level= argument in Operator Deployment section in deploy/12-operator.yaml file, modify it’s value and redeploy.

Allowed values are debug, info, error, or an integer value greater than 0, specified as string

Default value: info

Metrics Server logging

Find --v=0 argument in Operator Deployment section in deploy/22-metrics-deployment.yaml file, modify it’s value and redeploy.

Allowed values are "0" for info, "4" for debug, or an integer value greater than 0, specified as string

Default value: "0"


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

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 with any additional questions or comments.

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