DRAG DROP (Drag and Drop is not supported)
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.
Select and Place:
- See Explanation section for answer.
Answer(s): A
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/