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Difficulty: Very hardContainer-Based Workloads

An enterprise is designing a multi-region container-based solution on Azure. The solution requires hosting two distinct workloads:

- Workload 1: A backend service that must scale from zero dynamically based on the volume of messages in an Azure Service Bus queue. The enterprise wants to minimize ongoing administrative overhead and avoid managing container orchestration infrastructure.
- Workload 2: A security monitoring tool that requires direct access to the underlying Kubernetes API, custom daemonsets for host-level network packet inspection, and custom kernel parameter modifications.

Additionally, regulatory compliance policies mandate that log data must be isolated regionally and cannot leave the respective geographic boundaries of each deployment region.

Which two configurations should you include in the design to meet these requirements?

  1. Deploy Workload 1 to Azure Container Apps (ACA).Answer
  2. Deploy Workload 2 to Azure Kubernetes Service (AKS).Answer
  3. C
    Deploy Workload 2 to Azure Container Apps (ACA).
  4. D
    Deploy Workload 1 to Azure Container Instances (ACI).
  5. E
    Configure a single centralized Log Analytics workspace to aggregate all logs from all regions.

Answer

Deploy Workload 1 to Azure Container Apps (ACA) and deploy Workload 2 to Azure Kubernetes Service (AKS).
Deploying the event-driven scaling workload to Azure Container Apps meets the requirement for automatic KEDA-based scaling to zero while minimizing operational overhead. Deploying the security component to Azure Kubernetes Service is necessary because it requires host-level daemonsets, custom kernel parameters, and direct Kubernetes API access, which are not supported in serverless container environments.

Step-by-Step Solution

1
Analyze Workload 1 requirements.
Workload 1 needs event-driven queue scaling to zero and minimum management. Azure Container Apps natively integrates KEDA and abstracts host management, satisfying this requirement.
Matching the serverless scale-to-zero queue requirements with the lowest overhead service.
2
Analyze Workload 2 requirements.
Workload 2 requires deep host integration, custom daemonsets, and Kubernetes API access. This requires Azure Kubernetes Service (AKS), as these features are locked down in serverless container solutions.
Differentiating container runtimes based on administrative control and platform restrictions.
3
Evaluate the logging requirements against regulatory boundaries.
Separate Log Analytics workspaces must be deployed in each region to comply with data sovereignty regulations, ruling out a single centralized workspace.
Ensuring compliance with local geographic data boundaries.

Key Concept

Selecting the appropriate Azure container service based on orchestration complexity, Kubernetes API access, node-level control, and regional logging compliance requirements.
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Topics

Container-Based Workloads

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