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Difficulty: HardContainer-Based Workloads

A financial technology (fintech) corporation is designing a container-based credit scoring engine. The engine will run as regional microservices deployed in both the Azure North Europe and US East regions to process local credit profiles.

The design must satisfy the following requirements:
* The compute platform must automatically scale replicas based on CPU utilization and must scale down to zero replicas during off-peak hours to minimize idle costs.
* The administrative effort required to manage host operating systems, Kubernetes control planes, and orchestrator upgrades must be minimized.
* Container logs must be collected and segregated to comply with strict regional data sovereignty regulations, ensuring that European credit profile logs are never stored in or co-mingled with US-based logs.

Which solution should you recommend?

  1. Deploy the regional microservices to internal Azure Container Apps environments in their respective regions. Configure separate Log Analytics workspaces in each region to store and isolate the container logs.Answer
  2. B
    Deploy the regional microservices to Azure Kubernetes Service (AKS) clusters in each region. Configure a single centralized Log Analytics workspace in the primary region to consolidate all container logs.
  3. C
    Deploy the regional microservices to internal Azure Container Apps environments in their respective regions. Configure a single centralized Log Analytics workspace in the primary region with Table-level Role-Based Access Control (RBAC) to restrict access.
  4. D
    Deploy the regional microservices to Azure Container Instances (ACI) mapped to private virtual networks in each region. Configure separate Log Analytics workspaces in each region to store and isolate the container logs.

Answer

Deploy the regional microservices to internal Azure Container Apps environments in their respective regions and configure separate Log Analytics workspaces in each region to store and isolate the container logs.
Deploying the microservices to internal Azure Container Apps (ACA) environments in their respective regions combined with separate regional Log Analytics workspaces meets all design constraints. ACA is a serverless hosting platform that minimizes administrative overhead by eliminating Kubernetes control plane and VM host management, and natively supports scaling to zero based on CPU utilization. Regional Log Analytics workspaces ensure that European logs are kept completely separate from US logs, satisfying data sovereignty requirements.

Step-by-Step Solution

1
Evaluate the compute hosting requirements.
Identify that the solution requires microservices hosting with automatic scaling based on CPU utilization, scale-to-zero capability, and minimal administrative overhead (no VM host or control plane patching).
This rules out Azure Kubernetes Service (AKS) due to high management overhead, and rules out Azure Container Instances (ACI) since it lacks native metric-based scaling to zero.
2
Evaluate the regulatory and compliance logging requirements.
Identify that data sovereignty regulations prohibit co-mingling or storing European logs in the US region (or vice versa).
This mandates the use of separate Log Analytics workspaces in each region rather than a centralized single workspace, regardless of access control mechanisms like RBAC.
3
Synthesize the compute and logging components to select the best option.
Select the combination of regional internal Azure Container Apps environments and separate regional Log Analytics workspaces.
This combination satisfies both the serverless compute scaling requirements and the strict regional log segregation compliance requirements.

Key Concept

Selecting container hosting platforms and designing regional monitoring boundaries for compliance and operational efficiency.
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Topics

Container-Based Workloads

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