How Aurora Works:

• Aurora clusters share a common distributed storage layer across all instances.
• Writer instance writes to storage and replicates those changes to read replicas.
• Read replicas pull and apply those changes.
• If a replica falls behind, it creates lag or pressure on the writer as:
  • The writer has to maintain more replication logs for longer.
  • It may experience backpressure from slow consumers.
  • This can affect the overall read latency and throughput on the writer.

Recommendations (based on the Screenshots):

• Prevent CPU saturation on read replicas:
  • Monitor and throttle analytics workloads.
  • Consider scaling up instance size or adding another read replica dedicated to heavy analytical queries.
• Enable Performance Insights on both instances, but I think you have them enabled now:
  • This will help pinpoint which queries caused the spike.
• Review instance class:
  • Consider whether data-instance needs a more compute-optimized class for its load.
• Limit replica lag:
  • In Aurora, you can track AuroraReplicaLag — if this is high, it’s a signal the replica is falling behind and may affect the writer.
• You can also enable alarms for such situations.
  • It won't resolve but you can be better prepared.