Assets

• 1: Introduction
• 2: Kubernetes clusters
• 3: Buckets
• 4: Databases

1 - Introduction

An Asset is any kind of platform, technology or service that can be imported into the operator to improve its resiliency. Assets can include Kubernetes clusters and databases.

Asset types

Kubernetes Cluster

While the system is designed to be compatible with all kinds of Kubernetes clusters, official support and testing are limited to a specific list of Kubernetes distributions. This ensures that the synchronization process is reliable, consistent, and well-supported.

This is the list of officially supported Kubernetes distributions:

Buckets

Public cloud storage containers for objects stored in simple storage service.

Databases

2 - Kubernetes clusters

Any kind of KubernetesCluster can be imported in the operator. Credentials are stored in Kubernetes secrets from which the KubernetesCluster collection access to connect to the clusters.

Requirements

• The kubeconfig file to access the cluster

Process

1. Create secret

Get the kubeconfig file that can be used to access the cluster, and save it as kubeconfig.yaml.

Then create the Secret with the following command:

kubectl create secret generic source --from-file=kubeconfig.yaml=kubeconfig.yaml

2. Create resource

Define the KubernetesCluster resource with the following YAML, and save it as cluster.yaml:

apiVersion: assets.astronetes.io/v1alpha1
kind: KubernetesCluster
metadata:
  name: cluster-1
spec:
  secretName: <secret_name>

Deploy the resource with the following command:

kubectl create -f cluster.yaml

3 - Buckets

Buckets can be imported in the operator. Credentials are stored in Kubernetes secrets from which the KubernetesCluster collection access to connect to the clusters.

Requirements

• The access key and the secret key to access the bucket

Process

1. Create secret

Store the following file as secret.yaml and substitute the template parameters with real ones.

apiVersion: v1
kind: Secret
metadata:
  name: bucket-credentials
stringData:
  accessKeyID: <access_key_id>
  secretAccessKey: <secret_access_key>

Then create the Secret with the following command:

kubectl -n <namespace_name> apply -f secret.yaml

2. Create resource

Store the following file as bucket.yaml and substitute the template parameters with real ones.

apiVersion: assets.astronetes.io/v1alpha1
kind: Bucket
metadata:
  name: <name>
  namespace: <namespace>
spec:
  generic:
    endpoint: storage.googleapis.com
    name: <bucket_name>
    useSSL: true
    secretName: bucket-credentials

Deploy the resource with the following command:

kubectl create -f bucket.yaml

Examples

AWS S3

Secret:

apiVersion: v1
kind: Secret
metadata:
  name: bucket-credentials
stringData:
  accessKeyID: <access_key_id>
  secretAccessKey: <secret_access_key>

Bucket:

apiVersion: assets.astronetes.io/v1alpha1
kind: Bucket
metadata:
  name: gcp
spec:
  generic:
    endpoint: s3.<bucket-region>.amazonaws.com
    name: <bucket-name>
    useSSL: true
    secretName: bucket-credentials

Google Cloud Storage

Secret:

apiVersion: v1
kind: Secret
metadata:
  name: bucket-credentials
stringData:
  accessKeyID: <access_key_id>
  secretAccessKey: <secret_access_key>

Bucket:

apiVersion: assets.astronetes.io/v1alpha1
kind: Bucket
metadata:
  name: gcp-bucket
spec:
  generic:
    endpoint: storage.googleapis.com
    name: <bucket-name>
    useSSL: true
    secretName: bucket-credentials

4 - Databases

Databases can be imported in the operator. Credentials are stored in Kubernetes secrets from which the KubernetesCluster collection access to connect to the clusters.

Requirements

• The database credentials

Process

Zookeeper

1. Create resource

Define the Database resource with the following YAML, and save it as database.yaml:

apiVersion: assets.astronetes.io/v1alpha1
kind: Database
metadata:
  name: zookeeper
spec:
  zookeeper:
    client:
      servers:
        - 172.18.0.4:30181
        - 172.18.0.5:30181
        - 172.18.0.6:30181

Deploy the resource with the following command:

kubectl create -f database.yaml