Dellenny demonstrates how to implement the Cache-Aside (Lazy Loading) pattern for efficient application caching in Azure, using Azure Cache for Redis and .NET Core.

Implementing the Cache-Aside (Lazy Loading) Pattern in Azure

As applications scale, both performance and scalability become increasingly important considerations. Caching is a proven strategy to address these concerns, and among caching approaches, the Cache-Aside (Lazy Loading) pattern stands out for its simplicity and effectiveness. In this guide, Dellenny explains the pattern, its benefits, and shows how to apply it in Azure environments using Azure Cache for Redis, Azure SQL Database, and a sample .NET Core application.

What is the Cache-Aside Pattern?

  • The application is responsible for loading data into the cache when needed.
  • How it works:
    • The cache starts empty.
    • The app first checks the cache for the requested data.
    • If there’s a cache miss (data not in cache), the app retrieves it from the database (such as Azure SQL Database or Cosmos DB), stores it in the cache, and returns it.
    • If there’s a cache hit (data already cached), the app returns it immediately without querying the database.

Visual Flow Summary

  1. Application checks Azure Cache for Redis.
  2. If data is present (cache hit), it is returned.
  3. If not (cache miss), data is loaded from the database (Azure SQL DB/Cosmos DB).
  4. Data fetched from DB is then cached for future use.

Why Use Cache-Aside?

  • Improved Performance: Faster access by serving frequently requested data from cache, reducing database workload.
  • Cost Efficiency: Only necessary data is cached.
  • Flexibility: Full control over what and when to cache.

Important Considerations

  • Cache Invalidation: Must be handled to prevent serving outdated data. Updates or deletes in the DB should update/invalidate the cache appropriately.
  • Staleness: Set Time-to-Live (TTL) values for cache entries to avoid stale data.

Implementing Cache-Aside in Azure with .NET Core

Prerequisites

  • An Azure Cache for Redis instance
  • An Azure SQL Database (or another persistent data store)
  • A .NET Core application/service

Step 1: Install the Redis Client

Use the StackExchange.Redis package for .NET Core:

dotnet add package StackExchange.Redis

Step 2: Connect to Azure Cache for Redis

var redis = ConnectionMultiplexer.Connect("your-redis-name.redis.cache.windows.net:6380,password=yourAccessKey,ssl=True,abortConnect=False");
var cache = redis.GetDatabase();

Step 3: Implement the Cache-Aside Pattern

public async Task<Product> GetProductAsync(int productId)
{
    string cacheKey = $"product:{productId}";
    string cachedProduct = await cache.StringGetAsync(cacheKey);

    if (!string.IsNullOrEmpty(cachedProduct))
    {
        // Cache hit
        return JsonConvert.DeserializeObject<Product>(cachedProduct);
    }

    // Cache miss - load from database
    Product product = await _dbContext.Products.FindAsync(productId);

    if (product != null)
    {
        // Save to cache
        await cache.StringSetAsync(cacheKey, JsonConvert.SerializeObject(product), TimeSpan.FromMinutes(30));
    }

    return product;
}

Azure-Specific Considerations

  • Set TTLs: Use expiration times for each cache key to minimize risk of serving stale data.
  • Eviction Policies: Consider configuring LRU (Least Recently Used) eviction if memory is limited.
  • Cache Invalidation: When data changes, applications should update or evict related cache entries.
  • Monitoring: Use Azure Monitor for real-time insights into cache performance and usage.

Best Practices

  • Use robust serialization libraries (e.g., Newtonsoft.Json, System.Text.Json) for object storage.
  • Ensure cache operations are idempotent and thread-safe.
  • For highly write-intensive scenarios, evaluate Write-Through or Write-Behind cache patterns.

Summary

The Cache-Aside pattern is an accessible, effective entry point for adding caching to your Azure-hosted applications. Using Azure Cache for Redis alongside your persistence store allows you to enhance performance and scalability, giving your application more resilience as usage grows.

Authored by Dellenny. For related patterns and Azure architecture content, visit Dellenny’s full article archive.

This post appeared first on “Dellenny’s Blog”. Read the entire article here