This is a demo deployment which will illustrate leveraging a Kubernetes custom metric to scale pods based on the depth of a RabbitMQ pod. It leverages RabbitMQ-Server, Prometheus, Prometheus Adapter, and a sample python worker and publisher script.
This repo is meant to go along with my blog post.
Everything you need to deploy this demo is located within this repo. However, there are a few requirements you will need in order to get it working:
- A Kubernetes Cluster with kubectl setup(minikube will be fine)
- Helm deployed to the K8S cluster and a local helm client (Instructions here)
- Support for HPA version v2beta2 (
kubectl get apiservices | grep "autoscaling")
To make this as easy as possible, I have included a deploy.sh script, which will deploy all the helm charts that are needed, as well as deploying a sample consumer of messages.
To get started, clone the repo the repo locally, then run the deploy script
./deploy.sh
This will deploy the RabbitMQ, Prometheus, Prometheus Adapter, and a sample RabbitMQ python application..
If you are interested in an explanation of how all the components work together, it would be best to check out my blog post.
If you just want to published messages to RabbitMQ and see the HPA scale the number of worker pods, just run the following command:
kubectl run publish -it --rm --image=theryanbaker/rabbitmq-scaling-demo --restart=Never publish 500
The HPA is set to scale at 100 messages per pod, so make sure you publish at least more than 100 (plus some additional give the HPA time to scale)
Once you are done testing, you can run the destroy.sh script to clean up all the provisioned resources. Make sure to delete the namespace from Kubernetes once you are completed done to delete the PVC as well.