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Expand Up @@ -5,20 +5,23 @@
<a href="https://github.com/kedacore/keda/actions"><img src="https://github.com/kedacore/keda/workflows/nightly%20e2e%20test/badge.svg" alt="nightly e2e"></a>
<a href="https://twitter.com/kedaorg"><img src="https://img.shields.io/twitter/follow/kedaorg?style=social" alt="Twitter"></a></p>

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 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.
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.

---
<p align="center">
In partnership with
</p>
<p align="center">
<img src="images/partner-logos.png" width="500"/>
</p>
</p>

---

## Getting started

* [QuickStart - RabbitMQ and Go](https://github.com/kedacore/sample-go-rabbitmq)
Expand All @@ -39,7 +42,7 @@ You can find a [FAQ here](https://keda.sh/faq/) with some common questions.

## Samples

You can find several samples for various event sources [here](https://github.com/kedacore/samples)
You can find several samples for various event sources [here](https://github.com/kedacore/samples).

## Community

Expand All @@ -49,15 +52,18 @@ If interested in contributing or participating in the direction of KEDA, you can
* **Zoom link:** [https://zoom.us/j/150360492 ](https://zoom.us/j/150360492 )
* **Meeting agenda:** [https://hackmd.io/s/r127ErYiN](https://hackmd.io/s/r127ErYiN)

Just want to learn or chat about KEDA? Feel free to join the conversation in **[#KEDA](kubernetes.slack.com/messages/CKZJ36A5D)** on the **[Kubernetes Slack](https://slack.k8s.io/)**!
Just want to learn or chat about KEDA? Feel free to join the conversation in
**[#KEDA](kubernetes.slack.com/messages/CKZJ36A5D)** on the **[Kubernetes Slack](https://slack.k8s.io/)**!

## Building: Quick start with [Visual Studio Code Remote - Containers](https://code.visualstudio.com/docs/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 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](https://code.visualstudio.com/) and the [Remote Containers extensions](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers)
To get started install [VSCode](https://code.visualstudio.com/) and the [Remote Containers extensions](
https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers)

Clone the repo and launch code:

Expand All @@ -67,16 +73,20 @@ cd keda
code .
```

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

```bash
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.
> 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](https://github.com/operator-framework/operator-sdk), 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](https://github.com/kedacore/keda/blob/master/tools/build-tools.Dockerfile).
This project is using [Operator SDK framework](https://github.com/operator-framework/operator-sdk), 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](https://github.com/kedacore/keda/blob/master/tools/build-tools.Dockerfile).

```bash
git clone git@github.com:kedacore/keda.git
Expand All @@ -86,19 +96,32 @@ 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:
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
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 git@github.com: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`
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):
```bash
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
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.

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