How One Team Cut CPU Spikes on an 18 TB Azure SQL Hyperscale Database

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An engineering team managing an 18 TB Azure SQL Hyperscale database tackled excessive CPU usage by addressing both an uneven baseline load and sharp periodic spikes. A key fix involved introducing a queue pattern for heavy calculations running millions of times daily, which smoothed out bursts that occasionally hit 100–200k operations per minute. With the baseline stabilized, the team could more clearly identify and prioritize the remaining spike sources tied to scheduled jobs and batch processes. Read-heavy clients, including a third-party external client and an internal Data Analytics Team, were shifted to read-only replicas to reduce pressure on the primary database. These targeted changes reduced the need for repeated vCore scaling, which had been the default response to growing compute demand.

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ProgrammingDEV Community ·

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