Microsoft Certified Azure Cosmos DB Developer Practice Exams

About this course

The Microsoft Certified Azure Cosmos DB Developer Specialty certification is designed for developers who have expertise in designing, implementing, and monitoring cloud-native applications that use Azure Cosmos DB as their database. Cosmos DB is Microsoft's globally distributed, multi-model database service, and this certification validates a developer's ability to leverage its full potential. It is intended for database developers and architects who build solutions that require massive scale, low latency, and global distribution.A core focus of this certification is data modeling and partitioning. In Cosmos DB, proper partitioning is the single most important factor for performance and scalability. The exam thoroughly tests a candidate's ability to choose an appropriate partition key for different data access patterns and workloads. They must understand the concepts of logical and physical partitions and how partition key selection affects query performance, transaction support, and storage limits. This requires a deep understanding of the application's query patterns and data characteristics.The exam also covers the various APIs and SDKs available for Cosmos DB. While Cosmos DB is a core database engine, it exposes data through multiple APIs, including Core (SQL), MongoDB, Cassandra, Gremlin (graph), and Table. Candidates need to understand the use cases for each API and be proficient in using the relevant SDK (e.g., .NET, Java, Python) to perform data operations. This includes implementing point reads, queries, and stored procedures, as well as handling concurrency using optimistic concurrency control with ETags.Finally, the Azure Cosmos DB Developer exam focuses on performance optimization and global distribution. Candidates must know how to configure multi-region writes and read replicas to ensure low latency for globally distributed users. They need to understand how to measure request unit (RU) consumption, optimize queries and indexing policies to minimize cost, and implement chang