Before you get started using KUDO, you need to have a running Kubernetes cluster setup. You can use Minikube for testing purposes.
- Setup a Kubernetes Cluster in version
1.13or later (if you plan to use Minikube, please see the notes below)
- Install kubectl in version
Install KUDO into your cluster
Once you have a running cluster with
kubectl installed, you can install KUDO like so:
kubectl create -f https://raw.githubusercontent.com/kudobuilder/kudo/v0.5.0/docs/deployment/00-prereqs.yaml kubectl create -f https://raw.githubusercontent.com/kudobuilder/kudo/v0.5.0/docs/deployment/10-crds.yaml kubectl create -f https://raw.githubusercontent.com/kudobuilder/kudo/842c7f19a0a361751f0dab330faf3be147c9c4b3/docs/deployment/20-deployment.yaml
You can optionally install the
kubectl kudo plugin, which provides a convenient set of commands that make using KUDO even easier. To do so, please follow the CLI plugin installation instructions.
Deploy your first Operator
Follow the instructions in the Apache Kafka example to deploy a Kafka cluster along with its dependency Zookeeper.
Create your first operator
To see the powers of KUDO unleashed in full, you should try creating your own operator.
Notes on Minikube
If you plan on developing and testing KUDO locally via Minikube, you'll need to launch your cluster with a reasonable amount of memory allocated. By default, Minikube runs with 2GB - we recommend at least 10GB, especially if you're working with applications such as Kafka. You can start Minikube with some suitable resource adjustments as follows:
minikube start --cpus=4 --memory=10240 --disk-size=40g