AZ-204 Develop Azure compute solutions Practice Question
You are developing a solution that uses Azure Container Instances to run a batch job. The job requires 8 GB of memory and 4 vCPUs. You need to minimize costs. Which container group configuration should you choose?
⚠ Common exam trap
Many candidates think splitting resources across multiple containers or groups reduces cost, but Azure bills per container group as a whole, so consolidating into a single group with the required resources is the most cost-effective approach.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Linux container with 8 GB and 4 vCPUs in a single container group
Azure Container Instances bills per container group, not per container within the group. A single Linux container with 8 GB and 4 vCPUs in one container group meets the job's requirements with the lowest cost, as it avoids the overhead of multiple containers or groups. Splitting resources across containers or using separate groups would increase costs without benefit.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Linux containers split into two containers (4 GB each) in the same group
Why it's wrong here
Splitting a single workload requiring 8 GB and 4 vCPUs into two separate Linux containers, each with 4 GB and 2 vCPUs, within the *same* container group introduces unnecessary complexity and potential performance bottlenecks. While containers in the same group share a network and lifecycle, the application itself would need to be designed to distribute its workload across two instances, which is often not feasible for monolithic applications. This setup also incurs the overhead of managing two separate container processes instead of one optimized instance, potentially leading to increased resource consumption and management effort without a clear benefit.
- ✓
Linux container with 8 GB and 4 vCPUs in a single container group
Why this is correct
This configuration represents the most cost-effective and efficient solution for a workload requiring 8 GB of memory and 4 vCPUs. Utilizing a Linux container is inherently more economical in Azure Container Instances compared to Windows containers, as it avoids additional licensing costs. Furthermore, consolidating the entire workload into a single container within a single container group minimizes operational overhead and ensures that resources are allocated directly to the application without the complexities or additional billing associated with multiple groups or inter-container communication.
- ✗
Windows container with 8 GB memory and 4 vCPUs
Why it's wrong here
Opting for a Windows container with 8 GB memory and 4 vCPUs, while functionally capable, is generally a less cost-efficient choice for Azure Container Instances unless there's a specific dependency on Windows-based applications or frameworks. Windows containers in ACI typically incur higher billing rates compared to their Linux counterparts due to the underlying Windows Server licensing costs. This makes them a more expensive option for general-purpose containerized workloads where Linux compatibility is sufficient, directly impacting the overall operational expenditure.
- ✗
Linux container with 8 GB and 4 vCPUs, but using two separate container groups
Why it's wrong here
Deploying a single workload requiring 8 GB and 4 vCPUs across two *separate* Linux container groups, even if each group only contains a portion of the total resources, significantly increases the overall cost. Each Azure Container Instance group is a distinct billing unit, meaning you would be charged for two separate deployments, each with its own base resource allocation and associated overhead. This approach unnecessarily duplicates management and billing entities, making it less economical than consolidating the workload into a single, appropriately sized container group.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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