Plan and implement data platform resources

Your company runs SQL Server workloads across on-premises data centers and a third-party cloud provider. Management wants a single control plane in Azure to apply consistent governance, automated backups, and point-in-time restore to these SQL instances without migrating the databases into Azure SQL Database or Managed Instance. They also require the ability to run the service where the data currently resides for data residency reasons. Which solution should you recommend?

Your organization requires that all Azure SQL Database deployments be fully automated, version-controlled in a Git repository, and repeatable so that redeploying the same template does not create duplicate resources or fail if the resources already exist. The DevOps team wants a native Azure infrastructure-as-code approach that integrates with Azure Pipelines and produces a declarative definition of the database and its logical server. Which deployment method should you recommend?

A financial services company runs a mission-critical OLTP application on Azure SQL Database. The application requires the lowest possible I/O latency and must offload heavy reporting queries to a read-only replica without impacting write performance. The reporting queries must connect to a replica in the same region with in-memory OLTP support. Which service tier should you recommend?

A retail company runs a legacy line-of-business application on SQL Server 2008 R2 hosted on-premises. The database is 300 GB and is used only during store hours (7 AM to 9 PM). Management has approved a scheduled overnight maintenance window and wants to migrate the database to Azure SQL Managed Instance with the least operational complexity. You must recommend the migration approach that meets these requirements while minimizing cost and effort. Which approach should you recommend?

You are deploying an Azure SQL Managed Instance to host a mission-critical order-processing application. The business requires that the database survive a single datacenter failure within the primary Azure region without any manual intervention or geo-failover to a secondary region. You must minimize cost while meeting this resiliency requirement. Which configuration should you choose?

You manage an Azure SQL Database supporting a reporting workload. A large fact table (2 billion rows) is queried almost exclusively with analytical scans that read wide ranges of rows; the table is rarely updated after nightly bulk loads. Storage costs are rising and you notice heavy I/O pressure during report execution. You want to reduce storage footprint and physical I/O while keeping CPU overhead acceptable for this read-mostly, scan-heavy pattern. Which data compression option should you apply to the fact table?

A financial services company runs a mission-critical application on Azure SQL Managed Instance in the East US region. Compliance requires that the database remain readable and available for reporting even if the primary region experiences an outage, and that failover to a secondary region can occur with minimal manual intervention while preserving the same connection endpoint for the application. Which capability should you implement to meet these requirements?

A company currently runs a 250 GB database on an Azure SQL Managed Instance that was originally chosen for SQL Server Agent and cross-database queries. Those instance-level features are no longer used. To reduce cost, the team wants to move this single database to Azure SQL Database (Hyperscale) with the least possible downtime, keeping the application online during most of the migration. Which migration approach should you use?

Your company runs a 4 TB SQL Server 2016 database on-premises supporting a 24/7 e-commerce platform. Management requires migrating to Azure SQL Managed Instance with the least possible downtime, and the source database uses features not supported by Azure SQL Database. Which migration approach should you use?

A company is migrating a 900 GB SQL Server 2019 database from an on-premises server to Azure SQL Managed Instance. The business requires that application downtime be limited to a short cutover window, with the source database remaining available and continuously synchronized until the final switchover. Which migration approach should you use?

You manage an Azure SQL Managed Instance hosting a 2 TB sales database. The Orders table contains eight years of data and grows by roughly 20 million rows per month. Analysts run reports that almost always filter on an OrderDate range covering a single quarter, but queries currently scan the entire table, causing high I/O and slow response times. You must reduce query I/O for these date-filtered reports while keeping the ability to efficiently remove data older than seven years each year. Which approach should you implement?

A SaaS company hosts 60 separate Azure SQL databases, one per customer. Each database has unpredictable, sporadic activity: typically only 5-8 databases are busy at any given moment, while the rest are nearly idle, and peak times differ per customer. The finance team wants to reduce the cost of provisioning dedicated compute for every database while still allowing any individual database to burst to higher performance when its customer becomes active. Which deployment approach should you recommend?

You are planning a new Azure SQL Database deployment for a SaaS application. The single database is expected to grow from 500 GB to over 20 TB within two years. The business requires near-instantaneous point-in-time restore regardless of database size, the ability to add read-only replicas to offload reporting workloads, and rapid autoscaling of compute without long storage migration windows. Which service tier should you recommend?

A retail company is deploying a new order-processing database on Azure SQL Database. The database is expected to grow rapidly to several terabytes within a year. Traffic is highly unpredictable, with long idle periods overnight and sudden spikes during flash-sale events. The architecture team wants automatic scaling of compute during spikes, the ability to pause compute during idle periods to reduce cost, and support for databases that can grow beyond 4 TB without a full data reload. Which deployment configuration should you recommend?

A startup is deploying a new customer-facing web application. The single relational database will have unpredictable, spiky traffic and must be highly available. The team has no dedicated DBA and wants Microsoft to fully manage patching, backups, and high availability with the least possible administrative overhead. Cross-database queries and SQL Agent jobs are not required. Which Azure SQL deployment option should you recommend?

A retail company is migrating an on-premises SQL Server 2019 database to Azure. The application relies heavily on SQL Server Agent jobs, cross-database queries against three databases on the same instance, Service Broker, and the Common Language Runtime (CLR). The team wants to minimize application code changes and avoid managing the operating system or applying SQL Server patches. Which Azure SQL deployment option should you recommend?

A development team runs an Azure SQL Database that is used unpredictably: heavy activity for a few hours during working days, and long idle periods overnight and on weekends. The team wants to minimize compute cost during idle time without manually starting and stopping the database, while still tolerating a short warm-up delay when queries resume. Which compute configuration should you recommend?

You are designing the data platform for a multitenant SaaS application on Azure SQL Database. The application currently serves 200 tenants, but the business expects rapid growth to several thousand tenants over the next two years. Each tenant's data must be isolated, individual tenants can vary greatly in size and activity, and the platform must scale horizontally without a single database becoming a bottleneck. The development team wants a Microsoft-supported way to manage tenant-to-database mapping and route queries to the correct database. Which approach should you recommend?

A company runs a mission-critical application on an Azure SQL Database in the Business Critical service tier. The reporting team runs heavy analytical queries that are currently competing for resources with the OLTP workload, causing latency for transactional users. The team wants to offload the reporting queries to a separate replica without provisioning any additional databases, incurring extra licensing cost, or changing the service tier. What should you do?

Your company runs a transactional workload on an Azure SQL Database that supports an e-commerce site. The analytics team wants to run large aggregate and reporting queries against near-real-time operational data without adding load to the production OLTP database or writing custom ETL pipelines. Management wants the data to land in Microsoft Fabric OneLake so it can be joined with other datasets using T-SQL and Spark. Which approach best meets these requirements with the least operational overhead?