Microsoft Azure Solutions Architect Expert AZ-305 Practice Question
Contoso Bank is migrating its on-premises core banking system to Azure. The production SQL database currently holds 12 TB of data and is growing by about 800 GB per month. During month-end processing, CPU and I/O demands triple for several hours, and management insists that future growth must be accommodated without prolonged downtime for storage or compute scale-up. Which Azure SQL deployment option best meets these scalability requirements?
Azure SQL Database Hyperscale tier with the ability to independently scale compute replicas and auto-grow storage up to 100 TB
Azure SQL Elastic Pool on the General Purpose tier to distribute resources among multiple databases
Azure SQL Managed Instance Business Critical tier with manual vertical scaling
Azure SQL Database serverless tier to automatically pause and resume compute based on utilization
Azure SQL Database Hyperscale is designed for very large OLTP workloads. It supports up to 100 TB per database and uses an architecture that separates compute from storage, so you can add or remove compute replicas in minutes without moving data or causing appreciable downtime. Storage automatically grows in 10 GB increments, allowing the database to expand well beyond the 16 TB limit of Managed Instance Business Critical.
Serverless can pause and resume compute to save cost, but it currently supports only up to 40 vCores and 4 TB of storage, so it cannot meet the long-term capacity requirement. Elastic pools are intended to share resources across many small databases, not to scale a single 12-TB database. Managed Instance Business Critical tops out at 16 TB and requires a service-tier change that causes a brief outage and cannot scale storage independently of compute. Therefore, Hyperscale is the best choice for Contoso's rapidly growing, high-spike workload.
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Microsoft Azure Solutions Architect Expert AZ-305
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