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Cache options for Data Layer

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Hussain Mansoor

Cache options for Data Layer

Engineering
1 of 6
Moving towards 100k Orders Version 1.0 Data layer Cache options
Problems to solve 1 Read heavy workloads Bottlenecks on Read Replicas 2 RR scaling limitations RR Cost implications 3 Slow / unoptimized queries 4 Unavailability - Standard cache layer - Architecture patterns like Circuit Breaker
There are only two hard things in Computer Science: cache invalidation and naming things. https://martinfowler.com/bliki/TwoHardThings.html
● TTLs ○ Volatile-lru / volatile-ttl ● 245,000 RPS with R5.xLarge @ 100 connections ● 238,000 RPS @800 connections ● Atomic Operations Cache Layer Universal truth! ● Messaging Queues / Pub-Sub model ● Native Sorting! (Sorted Sets) ● Lists ● 500MB objects ● Single Threaded https://d0.awsstatic.com/whitepapers/performance-at-scale-with-amazon-elasticache.pdf
Caching Strategies Write-through Synchronous Updates Lazy Loading Check cache, if empty then fill Write Behind Write in Cache first Read Replica Copy via Enterprise Bus
Other Solutions ● Purpose built Databases ● S3 + CloudFront as cache for LLOs ● Perfectly optimized SQL queries ● GraphQL https://aws.amazon.com/getting-started/hands-on/purpose-built-databases/

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Cache options for Data Layer

  • 1. Moving towards 100k Orders Version 1.0 Data layer Cache options
  • 2. Problems to solve 1 Read heavy workloads Bottlenecks on Read Replicas 2 RR scaling limitations RR Cost implications 3 Slow / unoptimized queries 4 Unavailability - Standard cache layer - Architecture patterns like Circuit Breaker
  • 3. There are only two hard things in Computer Science: cache invalidation and naming things. https://martinfowler.com/bliki/TwoHardThings.html
  • 4. ● TTLs ○ Volatile-lru / volatile-ttl ● 245,000 RPS with R5.xLarge @ 100 connections ● 238,000 RPS @800 connections ● Atomic Operations Cache Layer Universal truth! ● Messaging Queues / Pub-Sub model ● Native Sorting! (Sorted Sets) ● Lists ● 500MB objects ● Single Threaded https://d0.awsstatic.com/whitepapers/performance-at-scale-with-amazon-elasticache.pdf
  • 5. Caching Strategies Write-through Synchronous Updates Lazy Loading Check cache, if empty then fill Write Behind Write in Cache first Read Replica Copy via Enterprise Bus
  • 6. Other Solutions ● Purpose built Databases ● S3 + CloudFront as cache for LLOs ● Perfectly optimized SQL queries ● GraphQL https://aws.amazon.com/getting-started/hands-on/purpose-built-databases/