Which CRDs should you configure?

Drag and Drop Question

You are a developer for a software as a service (SaaS) company that uses an Azure Function to process orders. The Azure Function currently runs on an Azure Function app that is triggered by an Azure Storage queue.

You are preparing to migrate the Azure Function to Kubernetes using Kubernetes-based Event Driven Autoscaling (KEDA).

You need to configure Kubernetes Custom Resource Definitions (CRD) for the Azure Function.

Which CRDs should you configure? To answer, drag the appropriate CRD types to the correct locations. Each CRD type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.

View Answer

Answer:

Explanation:

Box 1: Deployment

To deploy Azure Functions to Kubernetes use the func kubernetes deploy command has several attributes that directly control how our app scales, once it is deployed to Kubernetes.

Box 2: ScaledObject

With –polling-interval, we can control the interval used by KEDA to check Azure Service Bus Queue for messages.

Example of ScaledObject with polling interval

apiVersion: keda.k8s.io/v1alpha1

kind: ScaledObject

metadata:

name: transformer-fn

namespace: tt

labels:

deploymentName: transformer-fn

spec:

scaleTargetRef:

deploymentName: transformer-fn

pollingInterval: 5

minReplicaCount: 0

maxReplicaCount: 100

Box 3: Secret

Store connection strings in Kubernetes Secrets.

Example: to create the Secret in our demo Namespace:

# create the k8s demo namespace

kubectl create namespace tt

# grab connection string from Azure Service Bus

KEDA_SCALER_CONNECTION_STRING=$(az servicebus queue authorization-rule keys list

-g $RG_NAME

–namespace-name $SBN_NAME

–queue-name inbound

-n keda-scaler

–query "primaryConnectionString"

-o tsv)

# create the kubernetes secret

kubectl create secret generic tt-keda-auth

–from-literal KedaScaler=$KEDA_SCALER_CONNECTION_STRING

–namespace tt

Reference: https://www.thinktecture.com/en/kubernetes/serverless-workloads-with-keda/