Question: How to use ElastiCache with RDS?


Amazon Web Services (AWS) offers ElastiCache as a fully managed service to deploy and manage an in-memory cache infrastructure, and Amazon RDS (Relational Database Service) for providing managed relational database services. In certain scenarios, it may be beneficial to combine both services and use ElastiCache as a cache layer for RDS.

To use ElastiCache with RDS, follow these steps:

  1. Create an Amazon RDS DB instance - You can create a new DB instance or use an existing one. Make sure that the DB engine and version are compatible with your cache engine.
  2. Create an Amazon ElastiCache cluster - Choose the appropriate cache engine and version that is compatible with your RDS instance. You can also choose the node type and number of nodes based on your workload requirements.
  3. Configure the security group - Add the required inbound rules to allow traffic from your application server to both RDS instance and ElastiCache cluster. You can do this by adding the security groups of the RDS instance and ElastiCache cluster to application server's security group.
  4. Modify your application code - To use ElastiCache with RDS, you need to modify your application code to read data from the cache first, and if it is not available, then retrieve it from the RDS instance. Whenever you update the data in RDS, make sure to invalidate the corresponding cache entry.

Here’s an example of using ElastiCache with RDS in Python using the Redis cache engine:

import redis import psycopg2 # Connect to the ElastiCache cluster cache = redis.Redis(host='your-elasticache-endpoint', port=6379, db=0) # Connect to the RDS instance conn = psycopg2.connect(database='your-db-name', user='your-db-user', password='your-db-password', host='your-db-host', port=your-db-port) # Define a function to retrieve data from cache or RDS def get_data(key): try: # Try to get data from cache data = cache.get(key) if data: return data # If data is not in cache, retrieve it from RDS cur = conn.cursor() cur.execute('SELECT * FROM your-table WHERE id = %s', (key,)) data = cur.fetchone() # Put the data in cache cache.set(key, data) return data except (redis.RedisError, psycopg2.Error) as e: # Handle any errors that might occur print(f"An error occurred: {str(e)}") finally: # Close the connections conn.close() cache.connection_pool.disconnect()

In this example, we first connect to the ElastiCache cluster using the Redis library for Python, and then connect to the RDS instance using the psycopg2 library. We define a get_data function that tries to retrieve data from the cache using the cache.get method, and if it's not available, it retrieves it from RDS using a SQL query. Finally, the retrieved data is stored in the cache using the cache.set method.

Using ElastiCache with RDS can significantly improve the performance of read-heavy workloads by reducing the load on the RDS instance. However, it may also introduce some complexity in managing both services and ensuring consistency between the cache and the database.

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Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.