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Difficulty: MediumContainer-Based Workloads

A smart utilities company is designing a production telemetry processing system on Azure. The system will ingest continuous data streams from regional water meters and place them in an Azure Service Bus queue. A containerized backend application will retrieve the messages and perform complex data analysis.

The system must meet the following requirements:
* Scale container instances dynamically based on the queue length using Kubernetes Event-driven Autoscaling (KEDA).
* Support execution times of up to 25 minutes per data analysis task.
* Maintain continuous availability for this critical workload without risk of unexpected eviction.
* Minimize administrative and operational infrastructure overhead.

Which compute solution should you recommend?

  1. A
    Azure Functions on a Consumption plan
  2. B
    A self-managed Kubernetes cluster on Azure Spot Virtual Machines
  3. Azure Container AppsAnswer
  4. D
    Azure Kubernetes Service (AKS)

Answer

Azure Container Apps
Azure Container Apps is the ideal solution because it is a serverless container platform that natively supports Kubernetes Event-driven Autoscaling (KEDA) out of the box, allowing container instances to scale dynamically based on the queue length. It minimizes administrative and operational overhead by removing the need to manage nodes, control planes, or cluster upgrades. It also supports long-running execution times beyond 10 minutes and provides stable, continuous availability suitable for production workloads without the eviction risks associated with Spot VM priority.

Step-by-Step Solution

1
Analyze the scaling and infrastructure management requirements.
Identify that the solution must scale based on queue length using KEDA and minimize operational overhead.
This narrows the candidate services to managed container platforms that support event-driven scaling via KEDA.
2
Evaluate the execution timeout constraint against serverless options.
Determine that Azure Functions on a Consumption plan is ruled out due to its 10-minute maximum timeout since tasks can take up to 25 minutes.
Ensures the selected service can support long-running tasks without interruption.
3
Assess availability requirements and SLA constraints.
Rule out Azure Spot Virtual Machines because they do not guarantee continuous availability and are subject to eviction.
Ensures the workload is hosted on stable compute resources appropriate for production workloads.
4
Select the compute service that minimizes administrative overhead while meeting all technical requirements.
Azure Container Apps is selected over Azure Kubernetes Service (AKS) because AKS introduces excessive management overhead.
Aligns with Microsoft best practices for serverless container workloads when custom Kubernetes API access is not required.

Key Concept

Selecting container-based hosting solutions based on operational overhead, scaling, and execution duration
Estimated Time:1m 30s
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Topics

Container-Based Workloads

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