Develop for Azure Storage¶

Overview¶

This domain covers developing solutions using Azure Cosmos DB and Azure Blob Storage. It represents 15-20% of the exam and focuses on data storage operations, SDK usage, and storage management strategies.

📖 Azure Storage Documentation - Complete Azure Storage documentation 📖 Azure Cosmos DB Documentation - Official Cosmos DB documentation and guides

Key Topics¶

Cosmos DB Storage Solutions¶

• API and SDK selection for different scenarios
• Partitioning schemes and partition key implementation
• Data and container operations using SDKs
• Consistency level configuration for operations
• Change feed notification management

📖 Cosmos DB Partitioning - Partitioning and partition key strategies 📖 Cosmos DB Consistency Levels - Understanding consistency trade-offs 📖 Cosmos DB Change Feed - Change feed processing patterns

Blob Storage Solutions¶

• Moving items between storage accounts and containers
• Setting and retrieving properties and metadata
• Data operations using appropriate SDKs
• Storage policies and data lifecycle management
• Data archiving and retention implementation

📖 Azure Blob Storage Documentation - Complete Blob Storage guide 📖 Blob Storage Lifecycle Management - Automated lifecycle policies 📖 Blob Storage Access Tiers - Hot, Cool, and Archive tier optimization

Services Reference¶

Core Services¶

• Azure Cosmos DB (SQL, MongoDB, Cassandra, Gremlin, Table APIs)
• Azure Blob Storage
• Azure Storage SDK for .NET, Python, JavaScript, Java

📖 Cosmos DB .NET SDK - .NET SDK v3 for Cosmos DB 📖 Azure Storage Blobs Client Library - Blob Storage SDK for .NET

Supporting Services¶

• Azure Storage Explorer
• Azure Data Lake Storage Gen2
• Azure Content Delivery Network (CDN)

📖 Azure Data Lake Storage Gen2 - Hierarchical namespace for big data analytics

Best Practices¶

Cosmos DB Development¶

• Choose appropriate consistency level based on requirements
• Design effective partition keys to avoid hot partitions
• Use point reads when possible for best performance
• Implement retry logic for transient failures
• Monitor RU consumption and optimize queries

Blob Storage Management¶

• Use appropriate storage tier (Hot, Cool, Archive)
• Implement lifecycle management policies for cost optimization
• Use SAS tokens for secure, time-limited access
• Enable soft delete for data protection
• Leverage blob indexing for efficient searching

Performance Optimization¶

• Use async operations for better throughput
• Batch operations when possible
• Implement proper connection pooling
• Cache frequently accessed data
• Choose appropriate consistency level for Cosmos DB

Common Scenarios¶

Data Storage Patterns¶

• Document storage with Cosmos DB SQL API
• Time-series data with appropriate partition keys
• Large file storage and retrieval with Blob Storage
• Hierarchical data storage with Data Lake Storage Gen2

Integration Scenarios¶

• Change feed processing for real-time updates
• Blob trigger functions for automated processing
• Data replication across regions for disaster recovery
• CDN integration for static content delivery

Study Tips¶

• Practice using Cosmos DB SDKs for CRUD operations
• Understand partition key selection and impact on performance
• Learn the five consistency levels and trade-offs
• Hands-on experience with blob lifecycle management policies
• Understand different blob types (Block, Append, Page)
• Practice SAS token generation and usage
• Study change feed implementation patterns
• Learn blob metadata and properties management