Best practices for AWS ElastiCache and caching strategies that a junior cloud engineer should focus on

Published Mar 24, 2025

Here's a table with best practices for AWS ElastiCache and caching strategies that a junior cloud engineer should focus on. I'll break down the practices in a sequence of learning and execution order, from most critical to less critical.

Best Practice	Description	Priority
Understand Cache Types (Redis vs Memcached)	Before implementing, you should know the differences and when to use each cache type. Redis offers advanced features like persistence, pub/sub, and clustering, while Memcached is simpler and faster for basic caching needs.	Critical
Identify Cacheable Data	Understand which data should be cached. Focus on high-read, low-write data like product catalogs, session data, or commonly accessed database queries.	Critical
Set Appropriate TTL (Time to Live)	Caching too long can serve stale data; too short wastes resources. Learn to balance TTL settings for different data types.	Critical
Use Cache Invalidation	Plan for cache invalidation or expiration strategies to ensure that data is updated properly after changes, ensuring accuracy.	Critical
Auto-Discovery for Cluster Nodes	Use ElastiCache's auto-discovery feature in applications to manage Redis or Memcached nodes dynamically, so you don't need to manually update endpoints.	High
Use Cluster Mode in Redis	Learn how to enable Redis Cluster mode to horizontally scale across multiple nodes, improving performance and availability.	High
Consider Persistence in Redis	If you're using Redis, consider enabling persistence for critical data, but weigh the performance impact of RDB and AOF persistence options.	High
Monitor and Optimize Performance	Use Amazon CloudWatch metrics to monitor cache hit/miss ratios, eviction rates, CPU usage, and other relevant metrics to optimize cache performance.	High
Choose the Right Instance Type	Select appropriate instance sizes for your workload. Small instances may work for low-traffic apps, while high-traffic apps require larger or more instances.	Medium
Leverage Multi-AZ Deployments for High Availability	Ensure that your ElastiCache setup spans multiple availability zones (AZs) for higher fault tolerance and better disaster recovery.	Medium
Use Application-Level Caching	Implement caching at the application layer (e.g., local in-memory caches) alongside ElastiCache to reduce the load on the ElastiCache cluster and database.	Medium
Cache Write-Through vs Write-Behind	Learn the strategies for data consistency between cache and database: Write-Through writes both to cache and database simultaneously, while Write-Behind writes to the cache and updates the database asynchronously.	Medium
Eviction Policy Management	ElastiCache provides eviction policies like LRU (Least Recently Used) and TTL-based eviction. Understand which one to use for your data.	Medium
Implement Sharding in Memcached	If using Memcached, learn to implement sharding (splitting cache data across multiple nodes) for better scalability.	Low
Cost Optimization Strategies	Use Auto Scaling and cost-effective instance types to optimize for cost. Use Reserved Instances where possible to reduce costs for predictable workloads.	Low

Order of Learning

Critical Concepts First (Cache Types, Identifying Cacheable Data, TTL, Invalidation)
Implementation Practices (Auto-Discovery, Redis Cluster, Persistence)
Optimization and Scaling (Monitoring, Instance Types, Multi-AZ, Application-level Caching)
Advanced Techniques (Write-Through/Behind, Sharding, Eviction Policies)
Cost Optimization (Reserved Instances, Auto Scaling)

Explanation of Critical Best Practices

Understanding Cache Types: Knowing when to use Redis vs Memcached is crucial. Redis offers more features, but Memcached may be faster for simple caching needs. This helps you make informed decisions when setting up ElastiCache.
Identifying Cacheable Data: Before diving into caching, focus on which data should be cached. It’s typically high-read, low-write data. Knowing this will guide your caching strategy and prevent unnecessary cache storage.
TTL (Time to Live): Setting proper TTL values is a fundamental caching practice. TTL dictates how long cached data should be kept before it is discarded or refreshed. Too short TTL values can lead to frequent cache misses, while too long can serve stale data.
Cache Invalidation: Cache invalidation is essential to ensure data consistency. ElastiCache doesn’t automatically update the cache when your underlying data changes, so you must manage cache invalidation or expiration to avoid stale data.

AWS ElastiCache Best Practices

Jose Burgos

Full Stack Developer

Onboard Journey to Amazon Web Services