Exam AZ-305 topic 4 question 87 discussion

AE is the answer. https://learn.microsoft.com/en-us/azure/aks/concepts-scale#horizontal-pod-autoscaler Kubernetes uses the horizontal pod autoscaler (HPA) to monitor the resource demand and automatically scale the number of replicas. By default, the horizontal pod autoscaler checks the Metrics API every 15 seconds for any required changes in replica count, but the Metrics API retrieves data from the Kubelet every 60 seconds. Effectively, the HPA is updated every 60 seconds. When changes are required, the number of replicas is increased or decreased accordingly. Horizontal pod autoscaler works with AKS clusters that have deployed the Metrics Server for Kubernetes 1.8+. https://learn.microsoft.com/en-us/azure/aks/keda-about Kubernetes Event-driven Autoscaling (KEDA) is a single-purpose and lightweight component that strives to make application autoscaling simple and is a CNCF Incubation project. It applies event-driven autoscaling to scale your application to meet demand in a sustainable and cost-efficient manner with scale-to-zero.

A. Configure the horizontal pod autoscaler. E. Install Kubernetes-based Event Driven Autoscaling (KEDA). In order to replicate the same scaling mechanism as the Azure Function Consumption plan (which scales based on the number of incoming events), you need to implement Kubernetes-based Event Driven Autoscaling (KEDA). KEDA allows for fine-grained autoscaling (including to/from zero) for event-driven Kubernetes workloads. KEDA serves as a Kubernetes Metrics Server and allows users to define autoscaling rules using a dedicated Kubernetes custom resource definition. Horizontal Pod Autoscaler (HPA) is a Kubernetes component that automatically scales the number of pods in a replication controller, deployment, replica set, or stateful set based on observed CPU utilization or with custom metrics support. You need the HPA to work with KEDA for autoscaling your pods.

A & E are correct

I finally agree with AE as i initially though CE, none of the links provided by others really confirm the answer, so i did more digging and digging til i came cross this article which really explained it well "" Kubernetes-based Functions provides the Functions runtime in a Docker container with event-driven scaling through KEDA. KEDA can scale in to 0 instances (when no events are occurring) and out to n instances. It does this by exposing custom metrics for the Kubernetes autoscaler (Horizontal Pod Autoscaler). Using Functions containers with KEDA makes it possible to replicate serverless function capabilities in any Kubernetes cluster. These functions can also be deployed using Azure Kubernetes Services (AKS) virtual nodes feature for serverless infrastructure.""" https://learn.microsoft.com/en-us/azure/azure-functions/functions-kubernetes-keda Really Microsoft get real - expect us to know all this BS!!

"KEDA works by horizontally scaling a Kubernetes Deployment or a Job. It is built on top of the Kubernetes Horizontal Pod Autoscaler and allows the user to leverage External Metrics in Kubernetes to define autoscaling criteria based on information from any event source, such as a Kafka topic lag, length of an Azure Queue, or metrics obtained from a Prometheus query." https://cloudblogs.microsoft.com/opensource/2020/05/12/scaling-kubernetes-keda-intro-kubernetes-based-event-driven-autoscaling/

• Support kubenet and Azure Container Networking Interface (CNI) networking. With Azure Container Networking Interface (CNI), every pod gets an IP address from the subnet and can be accessed directly. Systems in the same virtual network as the AKS cluster see the pod IP as the source address for any traffic from the pod. Therefore, Pods level autoscaler is required. Which means AE would be the answer.

ans is correct

To prepare the AKS cluster to support App1 and meet the requirements you specified, you should perform two actions: Configure the horizontal pod autoscaler and Install Kubernetes-based Event Driven Autoscaling (KEDA). The horizontal pod autoscaler will allow you to use the same scaling mechanism as the current deployment by automatically scaling the number of pods based on CPU utilization or other application-provided metrics. KEDA will enable event-driven autoscaling by allowing you to scale based on events in Azure Queue Storage.

apps can be part of only pods not the nodes.. hence it should be hpa.

Got this on 14-Apr-2023

each choice represent part of solution. A and E do the same action . it's wrong . For me it's A & C

Even A looks good, I vote for: C. AKS cluster autoscaler E. KEDA

just wondering why there are no AKS node scaling involved? which is C. A and E are both pod level scaling.

Answers are correct