Microsoft Azure Documentation

Azure Storage Performance Optimization

Optimizing Performance for Azure Storage

This document provides guidance on how to optimize the performance of your applications using Azure Storage services, including Blob Storage, File Storage, Queue Storage, and Table Storage. Understanding the underlying architecture and available options is crucial for achieving maximum throughput and minimal latency.

Key Performance Considerations

  • Throughput and IOPS: Understand the limits and how to scale your storage accounts.
  • Latency: Minimize network round trips and choose appropriate storage tiers.
  • Concurrency: Efficiently handle multiple requests to your storage.
  • Caching: Leverage client-side and service-side caching mechanisms.
  • Data Structure and Access Patterns: Design your data for optimal retrieval.

Blob Storage Performance

Azure Blob Storage is highly scalable for unstructured data. To optimize blob performance:

  • Choose the right access tier: Hot, Cool, or Archive tiers offer different cost and access performance trade-offs.
  • Use Azure CDN: For globally distributed content, Content Delivery Network (CDN) significantly reduces latency.
  • Parallel Operations: Upload and download multiple blobs or parts of a large blob concurrently.
  • Use Page Blobs for random access: For I/O intensive workloads requiring low latency random reads/writes, consider Page Blobs.
  • Check Partition Keys: For block blobs, consider how you partition your data if you have very high request rates targeting specific groups of blobs.
Note: For optimal performance with large numbers of small objects, consider grouping them into larger blobs.

File Storage Performance

Azure Files offers fully managed file shares in the cloud accessible via SMB and NFS protocols. For performance tuning:

  • Premium File Shares: Use SSD-backed Premium tiers for latency-sensitive workloads.
  • Caching: Azure File Sync and SMB caching can improve performance for frequently accessed files.
  • Throughput Limits: Be aware of the per-share and per-storage-account throughput limits.

Queue Storage Performance

Azure Queue Storage is ideal for decoupling application components. Performance improvements often involve:

  • Batch Operations: Use batching to send and receive multiple messages at once, reducing overhead.
  • Message Size: Keep messages reasonably sized for efficient processing.
  • Visibility Timeout: Configure the visibility timeout appropriately to avoid contention for messages.

Table Storage Performance

Azure Table Storage is a NoSQL key-value store. Optimize its performance by:

  • Partition Key Design: Choose partition keys that distribute your workload evenly and group frequently accessed entities together. This is critical for query performance and scalability.
  • Clustering: Grouping data by partition key implicitly clusters it.
  • Indexed Queries: Design queries to utilize the primary key (PartitionKey + RowKey) for the fastest access.
  • Projection: Select only the properties you need in your queries to reduce data transfer.
Example: 
SELECT PartitionKey, RowKey FROM MyTable WHERE PartitionKey = 'partition1' AND RowKey = 'row1'

General Best Practices

  • Use the latest SDKs: Microsoft continuously updates SDKs to improve performance and add new features.
  • Monitor your metrics: Utilize Azure Monitor to track transaction counts, latency, availability, and ingress/egress data.
  • Apply request throttling: Implement strategies to handle transient errors and back off appropriately.
  • Consider geographic distribution: For latency-sensitive applications, deploy resources closer to your users.
Tip: For high-throughput scenarios, consider using Azure Blob Storage with a Premium account for better performance characteristics.

Further Reading