Typesense-Kubernetes-Operator

An operator for Typesense written in Python. Provides a way to manage Typesense in various deployment configurations. It is currently being worked on to be made production ready.

Please report an issue for improvement suggestions/feedback. This operator is being written with the help of KOPF framework.

Project Scope

The general idea is to make deployment of Tyepsense on kubernetes easy by automating the entire process involved in creation of Typesense cluster

kubectl create -f operator-config.yaml

Quickstart

Use minikube or any other tool to create your own kubernets cluster.
```
cd deploy
```
Deploy the Custom Resource Definition
```
kubectl create -f crd.yaml
```
Deploy rbac
```
kubectl create -f rbac.yaml
```
Deploy the latest operator
```
kubectl create -f operator.yaml
```
Check if operator is up and running
```
kubectl get pods 
```
Once the operator is up and running, define the operator configurations by referring to the section below

Wait for the cluster to be created

# Get Typesense pod status
kubectl get pods -n <namespace>

Operator configuration

Sample configuration can be found in operator-config.yaml
All the configuration must be specified under spec or config
Supported configurations under spec
- replicas : Number of replicas of typesense. default is 3
  NOTE: When the number of replicas are increased the operator automatically handles the peering connection between the replicas.
- namespace: Namespace to be used for deployment. default namespace is typesense
- image : Typesense production ready docker image. List can be found here. By default latest tag will be pulled
- resources : Resources for cpu and memory.
  defaults to below configuration:
```
resources:
  requests:
    memory: 100Mi
    cpu: "64m"
  limits:
    memory: 256Mi
    cpu: "512m"
```
- nodeSelector : Node to which pod has to be scheduled. if not specified, it picks up the node with available resources
- storageClass : Provides a way to administor the storage. Create a storage class with the provider of your choice and add it to the operator config.
  Options available are name and size
  - name : Name of the storageClass that the operator should consider for volume mount.
  - size : Size of the volume to be allocated to each typesense replica.
    NOTE: Supports all k8s Storageclass.
- startupProbe : Protect slow starting containers with startup probes
  Options available are failureThreshold and periodSeconds
  NOTE: k8s startupProbe.
- livenessProbe : Kubernetes provides liveness probes to detect and remedy such situations.
  Options available are failureThreshold and periodSeconds
  NOTE: k8s livenessProbe.
Supported configurations under config
- password : Typesense authentication is done using a password. defaults to 297beb01dd21c
Deploying the configuration
- kubectl create -f operator-config.yaml
- To apply any changes made to the config
  - kubectl apply -f operator-config.yaml

Upgrade

Before performing this upgrade process, it is recommended to:
- Test it out in a dev environment
- Backup the Typesense data
The process of updating TKO is simple:
1. Watch for changes in the CRD file and apply those changes
2. Watch for changes in the RBAC file and apply those changes
3. Apply the new operator.yaml file
4. Once the new operator pod is up and running, re-apply the configuration of the your operator so that the changes (if any) are reflected.
  kubectl apply -f <your operator config file yaml>

Cleanup

When you want to fully remove the cluster operator and associated definitions, you can run:

kubectl delete -f operator-config.yaml
kubectl delete -f deploy/crd.yaml
kubectl delete -f deploy/operator.yaml
kubectl delete -f deploy/rbac.yaml

Getting help

If you encounter any issues while using the operator, you can get help by:

Raise a Github issue

Contributing

You can contribute by:

Raising an issue
Opening Pull Requests
Improving documentation

License

Typesense operator is licensed under the Apache License

fharper / Typesense-Kubernetes-Operator