AZ-305 Question 147
Single answerA data analytics company needs to process large volumes of data on-demand using containerized applications. The workloads are sporadic and short-lived, and the team wants to avoid managing complex orchestration or underlying infrastructure. Which Azure compute service is most appropriate for this scenario?
- A
Azure Container Instances (ACI)
- B
Azure Kubernetes Service (AKS)
- C
Virtual Machine Scale Sets
- D
Azure App Service
Show answer and explanation
Correct answer: A
Explanation
For processing short-lived, bursty tasks in containers, Azure Container Instances is the most straightforward choice. It eliminates the need to manage infrastructure or orchestration overhead, billing only for active container runtime. Documentation reference: https://docs.microsoft.com/azure/container-instances/overview for best practices and usage scenarios.
- A. Correct.
Azure Container Instances (ACI) is correct because it allows you to run containers on-demand without managing virtual machines or a full orchestration system. You pay only for the compute resources used while the containers are running, making it suitable for sporadic and short-lived tasks.
- B. Incorrect.
Azure Kubernetes Service (AKS) is incorrect because, while it manages container orchestration, it also requires cluster management and node configuration. This adds more complexity than necessary for short-lived, sporadic workloads that do not need advanced orchestration features.
- C. Incorrect.
Virtual Machine Scale Sets is incorrect because it focuses on dynamically scaling a set of Virtual Machines, which still involves managing the underlying OS, patching, and capacity planning. This is more management overhead than needed for short-running container workloads.
- D. Incorrect.
Azure App Service is incorrect because it is primarily designed for web applications and APIs. While it can run containers, it is not as well-suited for purely ephemeral data processing tasks compared to ACI, which offers direct container execution without additional overhead.