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https://github.com/kontena/akrobateo

Akrobateo is a simple Kubernetes operator to expose in-cluster LoadBalancer services as node hostPorts using DaemonSets.
https://github.com/kontena/akrobateo

go kontena kubernetes kubernetes-operator

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Akrobateo is a simple Kubernetes operator to expose in-cluster LoadBalancer services as node hostPorts using DaemonSets.

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# Akrobateo

Akrobateo is a universal load balancer service implementation for [Kubernetes](https://kubernetes.io/). Akrobateo can work in any environment which makes it suitable for many use cases. And it's super light-weight too. It is implemented as an [operator](https://github.com/operator-framework/operator-sdk) that reacts when it sees `type: LoadBalancer` services in the cluster.

Akrobateo exposes in-cluster `LoadBalancer` services as node `hostPort`s using `DaemonSet`s. The operator naturally also syncs the addresses for the services. This essentially makes the `LoadBalancer` type services behave pretty much like `NodePort` services. The drawback with `NodePort` services is that we're not able to use additional components such as [ExternalDNS](https://github.com/kubernetes-incubator/external-dns) and others.

The node-port proxy Pods utilize iptables to do the actual traffic forwarding.

## Inspiration

This operator draws heavy inspiration from [K3S](https://github.com/rancher/k3s) `servicelb` controller: https://github.com/rancher/k3s/blob/master/pkg/servicelb/controller.go

As K3S controller is fully and tightly integrated into K3S, with good reasons, we thought we'd separate the concept into generic operator usable in any Kubernetes cluster.

## Why `DaemonSet`s?

Running the "proxies" as `DaemonSet`s makes the proxy not to be a single-point-of-failure. So once you've exposed the service you can safely e.g. push the services external addresses into your DNS. This does have the drawback that a given port can be exposed only in one service throughout the cluster.

## Building

Use the included `build.sh` script. There's naturally also a `Dockerfile` for putting everything into an image.

Build automation takes care of building all the release artifacts. So just create a tag for the release and everything will be build. The current build also produces multiarch images for both the operator and the LB image itself.

## Running locally

Either use operator-sdk to run it like so:
```sh
operator-sdk up local
```

Or use the locally built binary:
```sh
WATCH_NAMESPACE="default" ./output/akrobateo_darwin_amd64
```

`LB_IMAGE` env variable can be set to define a custom LB image to be used.

## Deploying

To deploy to live cluster, use manifests in `deploy` directory. It sets up the operator in `kube-system` namespace with proper service-account and RBAC to allow access to only needed resources.

## Future

Some ideas how to make things more configurable and/or future-proof

### DaemonSet vs. Deployment

The original Klippy controller creates Deployments. Maybe user could put some annotation on the service whether he/she wants a deployment or a daemonset created. Operator SDK _SHOULD_ be able to handle the different kinds of objects as long as there's proper owner references set.

### Node selection

There should be some way for the user to select which nodes should act as LBs. So something like a node selector is needed on the services as annotation. That probably also means we'd need to support also tolerations.