Azure Performance Best Practices

Introduction to Performance Optimization

Achieving optimal performance in Azure is crucial for delivering a responsive, reliable, and cost-effective user experience. This guide outlines key best practices for developers working with various Azure services.

Performance optimization is an ongoing process, not a one-time task. Regularly monitor your application's performance, identify bottlenecks, and implement these practices to ensure your solutions scale effectively with demand.

Azure App Service

Azure App Service is a powerful platform for hosting web applications, mobile backends, and APIs. Optimizing its performance involves several key strategies:

Scaling Strategies

• Autoscaling: Configure your App Service Plan to automatically scale up (add more instances) or scale out (increase compute resources) based on metrics like CPU usage, memory, or HTTP queue length. This ensures your application can handle traffic spikes.
• Manual Scaling: For predictable workloads, manual scaling allows you to set a fixed number of instances.
• Instance Size: Choose an App Service Plan tier that provides sufficient CPU, memory, and network bandwidth for your application's needs.

Caching

• Output Caching: Cache entire HTTP responses to reduce server load and improve response times for frequently accessed, non-dynamic content.
• Data Caching: Utilize in-memory caches like Azure Cache for Redis to store frequently accessed data, reducing database load.
• CDN Integration: Use Azure CDN to cache static assets (images, CSS, JavaScript) closer to your users, significantly reducing latency.

Deployment Slots

• Staging Environments: Use deployment slots to deploy new versions of your application to a staging slot. Test thoroughly before swapping it with the production slot. This minimizes downtime and reduces the risk of introducing performance regressions.

Azure Functions

Azure Functions is a serverless compute service that enables you to run small pieces of code ("functions") without explicitly provisioning or managing infrastructure. Performance considerations include:

Triggers and Bindings

• Efficient Triggers: Choose triggers that align with your event-driven architecture. For high-throughput scenarios, consider event-driven triggers like Event Hubs or Service Bus.
• Optimized Bindings: Use input and output bindings effectively to reduce boilerplate code and simplify data interaction.

Consumption Plan Performance

• Cold Starts: Be aware of "cold starts" where a function might take longer to initialize if it hasn't been invoked recently. This is inherent to the consumption model.
• Concurrency: Understand the concurrency limits of the consumption plan.

Premium/Dedicated Plan Performance

• Pre-warmed Instances: For latency-sensitive applications, the Premium or Dedicated (App Service) plans offer pre-warmed instances, eliminating cold starts.
• VNet Integration: For secure access to resources within a virtual network, integrate your functions with a VNet.
• Provisioned Throughput: The Premium plan offers provisioned throughput, guaranteeing a certain level of performance.

Azure SQL Database

Azure SQL Database is a fully managed relational database service. Performance tuning is critical for application responsiveness.

Indexing

• Clustered and Non-Clustered Indexes: Ensure appropriate indexes are created on columns used in WHERE clauses, JOIN conditions, and ORDER BY clauses.
• Index Maintenance: Regularly maintain indexes (reorganize and rebuild) to combat fragmentation and keep them efficient.
• Columnstore Indexes: For analytical workloads, consider columnstore indexes which can significantly improve query performance.

Query Optimization

• Execution Plans: Analyze query execution plans in SQL Server Management Studio (SSMS) or Azure Data Studio to identify bottlenecks.
• Parameterization: Use parameterized queries to improve plan caching and prevent SQL injection.
• Avoid Cursors: Where possible, rewrite cursor-based logic using set-based operations for better performance.

Service Tiers

• Choose the Right Tier: Select a service tier (e.g., Basic, Standard, Premium, Business Critical) and compute size that meets your performance and scalability requirements. Monitor DTU or vCore utilization.
• Elastic Pools: For applications with variable or unpredictable resource needs, elastic pools can provide a cost-effective way to share resources.

Azure Cosmos DB

Azure Cosmos DB is a globally distributed, multi-model database service. Performance is closely tied to its distributed nature and provisioning.

Partitioning (Sharding)

• Choose a Good Partition Key: Select a partition key that distributes requests evenly across partitions to avoid hot partitions and maximize throughput. High cardinality keys are generally better.
• Understand Partition Limits: Be aware of the physical partition limits and how they affect scalability.

Indexing Policies

• Efficient Indexing: Configure indexing policies to only index the properties that are frequently queried. Avoid indexing everything if not necessary, as it impacts write performance and storage.
• Composite Indexes: Consider composite indexes for queries that filter on multiple properties.

Request Units (RUs)

• Provisioned Throughput: Understand how Request Units (RUs) work and provision sufficient throughput (either manual or autoscale) for your workload.
• Monitor RU Consumption: Track RU consumption to identify if you are over-provisioning (wasting money) or under-provisioning (experiencing throttling).
• Optimize Queries: Write efficient queries. Cosmos DB's query optimizer works best with well-defined queries.

Azure Storage

Azure Storage offers highly scalable, durable, and available storage solutions for various data types.

Blob Access Patterns

• Blob Tiering: Utilize hot, cool, and archive tiers based on data access frequency to optimize costs.
• Blob Indexing: Use blob indexing to tag blobs and query them efficiently without downloading metadata.
• Asynchronous Operations: For large data transfers, use asynchronous operations to avoid blocking your application threads.

Content Delivery Network (CDN)

• Cache Static Assets: Serve static content (images, CSS, JavaScript, videos) from Azure CDN to dramatically reduce latency for global users and offload your origin servers.

Data Lifecycle Management

• Automated Management: Configure lifecycle management policies to automatically move data between access tiers or delete it based on defined rules (e.g., age, last modified date).

Networking Performance

Network latency and bandwidth can significantly impact application performance. Optimizing network configuration is key.

Virtual Networks (VNet)

• Proximity Placement: Deploy resources within the same VNet and subnet for lower latency.
• Service Endpoints & Private Endpoints: Use VNet service endpoints to securely connect to Azure services from your VNet. Private Endpoints provide dedicated private IP addresses for services, further enhancing security and performance.

Azure CDN

• Global Distribution: Azure CDN caches content at edge locations worldwide, bringing data closer to users and reducing latency for static assets.

Private Endpoints

• Secure and Fast Access: Leverage Private Endpoints to access Azure PaaS services (like Storage, SQL Database, Key Vault) over a private connection within your VNet, bypassing the public internet. This improves security and can reduce latency.