Answer-first summary for fast verification
Answer: Implement auto-scaling policies that dynamically adjust Fabric capacity based on real-time workload demands, with predefined rules to balance performance and cost.
Option B is the correct answer because it leverages auto-scaling policies to dynamically adjust capacity based on real-time demand, ensuring optimal performance and cost-effectiveness. This approach addresses both immediate needs and long-term scalability without manual intervention. Option A is incorrect because manual adjustments may not respond quickly enough to fluctuating demands, potentially leading to performance issues or unnecessary costs. Option C is incorrect because it fails to address the dynamic nature of workload demands across the entire Fabric environment. Option D is incorrect because it does not actively manage capacity settings to meet changing demands, focusing only on monitoring and cost tracking.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
As a Microsoft Fabric Analytics Engineer Associate, you are responsible for optimizing the Fabric environment to accommodate an increasing demand for data analytics resources. Your organization emphasizes cost-effectiveness, performance, and scalability. You need to evaluate the following strategies to manage Fabric capacity effectively. Choose the option that BEST addresses these requirements by considering both immediate and long-term scalability needs. (Choose one)
A
Continuously monitor Fabric resource usage (CPU, memory, storage) and manually adjust capacity settings based on observed patterns, ensuring no over-provisioning.
B
Implement auto-scaling policies that dynamically adjust Fabric capacity based on real-time workload demands, with predefined rules to balance performance and cost.
C
Allocate fixed, dedicated resources for critical workloads only, ignoring the potential for fluctuating demand across other workloads.
D
Use Azure Monitor and Azure Cost Management solely for tracking usage and costs, without implementing any changes to capacity settings.
No comments yet.