A company has a SaaS solution that uses Azure SQL Database with elastic pools. The solution contains a dedicated database for each customer organization. Customer organizations have peak usage at…

Question

Options

• ANumber of transactions only
• BeDTUs per database only
• CNumber of databases only
• DCPU usage only
• EeDTUs and max data size

• B
  4% (1)
• D
  7% (2)
• E
  89% (24)

Explanation

Configuring eDTUs and max data size (E) directly controls the two levers that determine elastic pool cost: the shared compute/IO/memory capacity (eDTUs) and the total storage ceiling - both of which must be right-sized to avoid over-provisioning while still handling peak loads across staggered customer cycles.

Why the distractors fail:

• (A) Number of transactions - transaction count is a workload metric, not a pool configuration setting you set to control cost.
• (B) eDTUs per database only - setting per-database eDTU limits alone doesn't define the pool's total capacity or storage, leaving cost undefined.
• (C) Number of databases only - the number of databases affects utilization patterns but is not itself a pool configuration option that controls cost.
• (D) CPU usage only - CPU is a monitored metric used to inform sizing decisions, not a configurable pool parameter.

Memory tip: Think of an elastic pool like a shared buffet - you must decide both how much food to put out (eDTUs = shared compute budget) and how big the table is (max data size = storage). If you only set one or neither, you either waste money or run out of capacity.

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