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Difficulty: HardContainer-Based Workloads

A retail company is designing a container-based backend system for real-time inventory updates. The system consists of multiple microservices that process messages from Azure Service Bus queues. The solution must meet the following requirements:
- Scale container instances down to zero when there are no messages in the queue to minimize costs.
- Support event-driven auto-scaling based on the number of messages in the Service Bus queues.
- Prevent developers from managing Kubernetes APIs, control planes, or virtual machine node scaling.
- Consolidate application telemetry into a single repository, while strictly isolating sensitive transaction logs into a separate, dedicated repository for regulatory compliance.

Which architecture should you recommend to meet the requirements with the minimum amount of administrative effort?

  1. Deploy the microservices to Azure Container Apps. Configure the container apps to write telemetry to a shared Log Analytics workspace, and route transaction logs to a dedicated Log Analytics workspace.Answer
  2. B
    Deploy the microservices to Azure Container Apps. Configure the container apps to write both telemetry and transaction logs to a single, consolidated Log Analytics workspace.
  3. C
    Deploy the microservices to an Azure Kubernetes Service (AKS) cluster. Configure the cluster to use KEDA for event-driven scaling, and route telemetry and transaction logs to two separate Log Analytics workspaces.
  4. D
    Deploy the microservices to an Azure Kubernetes Service (AKS) cluster. Configure the cluster to use KEDA for event-driven scaling, and consolidate all logs into a single Log Analytics workspace.

Answer

Deploy the microservices to Azure Container Apps. Configure the container apps to write telemetry to a shared Log Analytics workspace, and route transaction logs to a dedicated Log Analytics workspace.
The correct solution uses Azure Container Apps to host the microservices. This satisfies the event-driven scaling (via KEDA integration) and scale-to-zero requirements while completely abstracting the Kubernetes control plane and VM node scaling. To meet the compliance requirement, the solution isolates sensitive transaction logs into a dedicated Log Analytics workspace, keeping general application telemetry in a shared workspace.

Step-by-Step Solution

1
Evaluate the compute hosting requirements against Azure options.
Azure Container Apps (ACA) is selected over Azure Kubernetes Service (AKS) because it is a serverless platform that natively supports KEDA-based scaling, scales to zero, and hides Kubernetes API/infrastructure management, which directly minimizes administrative effort.
The requirements state that developer management of Kubernetes APIs, control planes, and VM node scaling must be prevented, which rules out AKS.
2
Evaluate the logging and compliance requirements.
Two distinct Log Analytics workspaces are planned: one shared workspace for telemetry logs and one dedicated workspace for sensitive transaction logs.
Regulatory compliance mandates strict isolation of transaction logs from application telemetry, which cannot be achieved with a single consolidated workspace.
3
Synthesize compute and logging designs into a unified solution.
Recommend hosting the microservices on Azure Container Apps and configuring log split routing to two separate Log Analytics workspaces.
This combined architecture satisfies all business, technical, scaling, and compliance requirements with the lowest operational overhead.

Key Concept

Azure Container Apps provides serverless container hosting with native KEDA-based scaling and zero operational overhead compared to AKS, while log isolation requirements must be met by using separate Log Analytics workspaces.
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Topics

Container-Based Workloads

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