AZ-305 Design data storage solutions Practice Test 15 — 15 Questions

Question 1

A software company hosts multiple small databases for different clients on Azure SQL Database. Each database has low average usage but experiences unpredictable spikes. The company wants to minimize cost by pooling resources across databases while allowing each database to consume resources up to a set limit during spikes. They also need the ability to easily add new databases without manual sizing. Which Azure SQL Database deployment option should they choose?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Azure SQL Database elastic pool. Azure SQL Database elastic pool is the correct choice because it allows multiple databases to share a fixed pool of resources (eDTUs or vCores), which minimizes cost by pooling resources across databases with low average usage and unpredictable spikes. Each database can automatically burst up to a configurable per-database resource limit (e.g., max eDTU per database) during spikes, and new databases can be added to the pool without manual sizing, as they simply consume from the shared pool.

Answer

Azure SQL Database single database with reserved capacity

Answer

Azure SQL Managed Instance

Answer

SQL Server on Azure Virtual Machines

Question 2

A company is building a petabyte-scale data lake for analytics. The workload includes Apache Spark and Hive jobs that read and write large files. The storage solution must support a hierarchical namespace for efficient directory operations, POSIX-like access control lists (ACLs) for fine-grained permissions, and must be accessible via the Azure Blob Storage API for compatibility with existing tools. Furthermore, the solution should be optimized for analytics workloads with high throughput. Which Azure data service should they choose?

Accepted Answer

Azure Data Lake Storage Gen2. Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with POSIX-like ACLs and is accessible via the Azure Blob Storage API. This service is specifically optimized for analytics workloads like Apache Spark and Hive, providing high throughput for petabyte-scale data lakes. The hierarchical namespace enables efficient directory operations, while the Blob Storage API ensures compatibility with existing tools.

Answer

Azure Data Lake Storage Gen1

Answer

Azure Blob Storage

Answer

Azure Files

Question 3

A media company needs to store large volumes of video files that are processed by an application. The files are accessed via REST APIs and are rarely accessed after the first few days. The company wants to minimize storage costs by automatically moving older files to a cheaper storage tier without any manual intervention. Which Azure storage solution should they use, and which feature should they configure?

Accepted Answer

Azure Blob Storage with lifecycle management policies. Azure Blob Storage with lifecycle management policies is the correct solution because it allows you to define rules that automatically move blobs to cooler tiers (e.g., from Hot to Cool to Archive) based on age or last modification time, minimizing storage costs without manual intervention. The REST API access requirement is natively supported by Blob Storage via HTTPS, and the large video file workload fits well within its object storage capabilities.

Answer

Azure Files with tiering

Answer

Azure NetApp Files with capacity pools

Answer

Azure Disk Storage with managed disks

Question 4

A global e-commerce platform uses Azure Cosmos DB for its product catalog. The application requires multi-region writes to provide low-latency updates from any geographic location. Two users may update the same product item concurrently, so the solution must automatically resolve conflicts. For real-time inventory checks, reads must be strongly consistent, while product description reads can be eventually consistent. Which Cosmos DB configuration should they choose?

Accepted Answer

SQL API with multi-region writes, last-writer-wins conflict resolution, and per-request strong consistency. The SQL API in Cosmos DB supports multi-region writes with last-writer-wins (LWW) conflict resolution using a timestamp or custom property, which automatically resolves concurrent updates to the same product item. Per-request strong consistency allows inventory reads to achieve linearizability by setting the consistency level at the request level, while product description reads can use the default session or eventual consistency for performance. This combination meets all requirements: multi-region writes, automatic conflict resolution, and the ability to mix strong and eventual consistency on a per-request basis.

Answer

MongoDB API with multi-region writes and automatic conflict resolution

Answer

Table API with multi-region writes and strong consistency

Answer

Cassandra API with multi-region writes and strong consistency

Question 5

A company wants to migrate its on-premises file server to Azure with minimal application changes. The application accesses files over the SMB protocol and requires identity-based access using the existing on-premises Active Directory Domain Services (AD DS). They need the solution to be fully managed with low latency. Which Azure storage solution should they choose?

Accepted Answer

Azure Files. Azure Files is the correct choice because it provides fully managed SMB file shares that can be accessed over the SMB protocol with identity-based authentication using on-premises AD DS via Azure Files AD DS integration. This allows the application to connect with minimal changes, as it continues to use SMB and existing domain credentials, while Azure Files offers low-latency access when deployed in the same region as the application.

Answer

Azure NetApp Files

Answer

Azure Blob Storage with NFS 3.0

Answer

Azure Disk Storage

Question 6

A company stores log data in Azure Blob Storage. Logs are accessed frequently for the first 30 days, then rarely accessed but must be retained for 7 years for compliance. They want to minimize storage costs. Which storage tier and lifecycle management rule should they use?

Accepted Answer

Use the Hot tier for initial storage, and a lifecycle rule to move to Archive after 30 days.. The Hot tier is optimal for frequent access during the first 30 days, and a lifecycle rule moving directly to Archive after 30 days minimizes costs by immediately transitioning to the lowest-cost storage tier for long-term retention. The Archive tier is the most cost-effective for data that is rarely accessed and must be retained for 7 years, as it offers the lowest storage cost but higher retrieval latency and cost.

Answer

Use the Cool tier for initial storage, and a lifecycle rule to move to Archive after 30 days.

Answer

Use the Hot tier for initial storage, and a lifecycle rule to move to the Cool tier after 30 days, then to Archive after 7 years.

Answer

Use the Archive tier for initial storage, and a lifecycle rule to move to Hot for the first 30 days.

Question 7

A company stores large amounts of log data in Azure Blob Storage. Logs are accessed frequently for the first 30 days, then rarely accessed afterward, but must be retained for 7 years for compliance. The company wants to minimize storage costs. They need to configure automatic data movement and retention policies. Which combination of Azure Blob Storage access tiers and lifecycle management policy should they use?

Accepted Answer

Use Hot tier for 30 days, then use Archive tier for the remaining period, with a lifecycle rule to delete after 7 years.. It uses the Hot tier for the first 30 days to handle frequent access, then automatically moves data to the Archive tier via a lifecycle management rule to minimize costs for rarely accessed data, and finally deletes the blobs after 7 years to meet compliance retention requirements. The Archive tier offers the lowest storage cost for long-term retention, making it ideal for logs that are rarely accessed after the initial period.

Answer

Use Hot tier for 30 days, then use Cool tier for 7 years, with a lifecycle rule to delete after 7 years.

Answer

Use Cool tier for 30 days, then use Archive tier for 7 years, no lifecycle rule needed.

Answer

Use Archive tier immediately, with a lifecycle rule to delete after 7 years.

Question 8

A company is migrating a MongoDB-compatible application to Azure. The application requires low-latency reads and writes globally. It needs to support multi-region writes so that updates can be made from any region with automatic conflict resolution. The data is JSON documents that can vary in schema. The company wants a fully managed database service with native support for MongoDB APIs. Which Azure data service should they choose?

Accepted Answer

Azure Cosmos DB with the API for MongoDB. Azure Cosmos DB with the API for MongoDB is the correct choice because it provides a fully managed, globally distributed database service that natively supports the MongoDB wire protocol. It offers multi-region writes with automatic conflict resolution using last-writer-wins (LWW) or custom conflict resolution policies, ensuring low-latency reads and writes globally. Its schema-agnostic nature handles JSON documents with varying schemas, meeting all stated requirements.

Answer

Azure SQL Database

Answer

Azure Database for MongoDB

Answer

Azure Cache for Redis

Question 9

A company ingests IoT sensor data into Azure Blob Storage. Data is written frequently and is accessed rarely after the first 24 hours. The company must retain the data for exactly 90 days for compliance. They want to minimize storage costs by automatically moving data to the cheapest possible storage tier as soon as possible. Which Azure Blob Storage lifecycle management policy should they implement?

Accepted Answer

Move to Cool tier after 1 day, delete after 90 days. The data is rarely accessed after 24 hours, so moving it to Cool tier after 1 day minimizes cost while still allowing low-latency access. The 90-day deletion aligns with the compliance retention requirement. Cool tier is the cheapest online tier, and moving data there as soon as possible (after 1 day) reduces costs without incurring the early deletion penalty or retrieval latency of Archive tier.

Answer

Move to Archive tier after 1 day, delete after 90 days

Answer

Move to Cool tier after 30 days, delete after 90 days

Answer

Move to Archive tier after 30 days, delete after 90 days

Question 10

A company stores log data in Azure Blob Storage. The logs are accessed frequently for the first 30 days, then only occasionally for up to 1 year, and after that must be retained for 7 years for compliance purposes. The company wants to minimize storage costs by automatically moving data to cheaper tiers. Which Azure Blob Storage lifecycle management policy should they implement?

Accepted Answer

Move to Cool tier after 30 days, move to Archive tier after 365 days, delete after 2555 days. It aligns with the access patterns: move to Cool tier after 30 days (frequent access period), move to Archive tier after 365 days (occasional access period ends), and delete after 2555 days (7 years retention). This minimizes costs by transitioning data to progressively cheaper storage tiers and automatically deleting it when compliance retention expires.

Answer

Move to Cool tier after 30 days, move to Archive tier after 365 days, delete after 7 years

Answer

Move to Cool tier after 30 days, move to Archive tier after 30 days, delete after 2555 days

Answer

Move to Archive tier after 30 days, keep in Archive until deletion after 2555 days

Question 11

A company is building a global real-time collaboration platform. The application data is stored as JSON documents and needs to be available for low-latency reads and writes from multiple geographic regions. The application must support multi-region writes so that users can update data from any region with automatic conflict resolution. The company wants a fully managed database service with a guaranteed SLA for availability and throughput. Which Azure data service should they choose?

Accepted Answer

Azure Cosmos DB with SQL API and multiple write regions. Azure Cosmos DB with SQL API and multiple write regions is the correct choice because it is a fully managed, globally distributed NoSQL database that natively supports multi-region writes with automatic conflict resolution. It provides low-latency reads and writes from any region, a guaranteed SLA for availability (99.999% for multi-region writes) and throughput, and is optimized for JSON document storage, making it ideal for a real-time collaboration platform.

Answer

Azure SQL Database with active geo-replication

Answer

Azure Table Storage

Answer

Azure Cache for Redis

Question 12

A company stores JSON documents for a mobile app backend. The data needs to be accessible from multiple global regions with low latency writes from any region. The app uses a client-side library that supports automatic conflict resolution for concurrent updates. Which Azure data service should they choose?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is correct because it provides multi-region writes with automatic conflict resolution, which directly matches the requirement for low-latency writes from any global region. Its multi-master replication model allows any region to accept writes, and the client-side library can use last-writer-wins (LWW) or custom conflict resolution policies to handle concurrent updates seamlessly.

Answer

Azure SQL Database

Answer

Azure Database for PostgreSQL

Answer

Azure Table Storage

Question 13

A company needs to store sensor data from IoT devices. Each device sends a message every second. The data is time-series and will be queried for real-time dashboards and historical analysis. The solution must support high ingestion rates and low-latency queries on recent data. Which Azure service should they use?

Accepted Answer

Azure Event Hubs and Azure Data Explorer. Azure Event Hubs is designed for high-throughput data ingestion from millions of IoT devices, capable of handling millions of events per second. Azure Data Explorer (ADX) is optimized for time-series data, providing sub-second query latency on recent data and efficient historical analysis. Together, they form a serverless pipeline that ingests sensor data via Event Hubs and stores it in ADX for real-time dashboards and long-term analytics.

Answer

Azure Blob Storage with Azure Data Lake Storage Gen2

Answer

Azure Cosmos DB with SQL API

Answer

Azure Table Storage

Question 14

A company manages a fleet of millions of IoT devices that send telemetry data every minute. The data must be stored for 10 years to meet compliance requirements. For the first 30 days, data is accessed frequently for real-time dashboards and alerting. After 30 days, data is only accessed occasionally for historical analysis and reporting. The solution must be cost-effective and support high ingestion rates. Which Azure service should the company use to store and query this data?

Accepted Answer

Azure Data Explorer. Azure Data Explorer (ADX) is designed for high-ingestion, time-series telemetry data and supports real-time dashboards and alerting on fresh data, while also providing cost-effective long-term storage for historical queries. Its columnar storage and indexing enable fast analytics on billions of records, making it ideal for IoT scenarios with millions of devices sending data every minute and a 10-year retention requirement.

Answer

Azure Blob Storage with Azure Data Lake Storage Gen2

Answer

Azure SQL Database

Answer

Azure Cosmos DB with SQL API

Question 15

A global e-commerce company uses Azure Cosmos DB to store its product catalog. The catalog is read-heavy, with users worldwide expecting consistent reads with a 99th percentile latency under 10 ms. Writes to the catalog are performed by a central admin team in one region. The company needs to minimize write latency and cost while ensuring that users always see the same data within a single session. Which Cosmos DB configuration should the company choose?

Accepted Answer

Single-master write region with Session consistency and multiple read regions. Session consistency provides the required 'read your own writes' guarantee within a single session, which ensures users always see the same data during their session without the latency and cost penalties of Strong consistency. Single-master writes minimize write latency by directing all writes to one region (the central admin team's region), while multiple read regions allow global users to read from the nearest region with sub-10 ms latency. This configuration balances cost, performance, and consistency needs for a read-heavy catalog with centralized writes.

Answer

Single-master write region with Strong consistency and multiple read regions

Answer

Multi-master write with Eventual consistency and all regions enabled for writes

Answer

Multi-master write with Strong consistency and two regions