What best practices should be followed when managing compute resources using service plans? (Select two.)

Question

Options

• ADefining multiple service plans based on workload requirements
• BAssigning service plans based on performance needs
• CRestricting all users from modifying instance sizes
• DPreventing service plans from being modified after deployment

• A
  70% (16)
• C
  22% (5)
• D
  9% (2)

Explanation

Defining multiple service plans (A) allows you to right-size compute resources for different workloads - a batch job shouldn't share the same plan as a real-time API. Assigning plans based on performance needs (B) ensures cost efficiency and appropriate throughput by matching resource allocation to actual demand. Together, these two practices form the foundation of flexible, scalable resource management.

Why C and D are wrong: Restricting all users from modifying instance sizes (C) is overly rigid - authorized users often need to scale in response to changing demand, and blanket restrictions become an operational bottleneck. Preventing service plan modification after deployment (D) directly contradicts elasticity, one of the core benefits of cloud compute; workloads evolve, and plans must be able to change with them.

Memory tip: Think "Match and Multiply" - match plans to performance needs (B), and multiply plans to cover different workload types (A). Anything that locks or restricts change (C, D) works against the cloud's fundamental value proposition of elasticity.

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