AWS Database Blog
Category: Best Practices
Help prevent out-of-memory restarts on Aurora MySQL 8.4
Out-of-memory restarts drop every connection and force an Aurora MySQL cluster restart. Learn how Aurora MySQL 8.4’s automatic memory management prevents them: confirm protection is active, read the signals during a memory-pressure event, monitor OOM avoidance with CloudWatch, and decide when to take manual control.
Diagnose Amazon Aurora MySQL performance using CloudWatch Database Insights
When an Aurora MySQL or Amazon RDS for MySQL database slows down, it can be hard to tell why. This post shows how to read DB load in Amazon CloudWatch Database Insights, interpret the most common MySQL wait events, and turn each into a concrete action, so you can fix the real bottleneck instead of scaling up to a larger instance.
Multi-tenancy with Amazon ElastiCache: Choosing the right isolation model
Choosing a multi-tenancy isolation model for Amazon ElastiCache for Valkey comes up in nearly every SaaS architecture review. This post walks through the options, from dedicated clusters to shared infrastructure with per-tenant encryption, and shows how to match each model to your blast radius and compliance requirements.
Reducing storage initialization impact in Amazon RDS for PostgreSQL after snapshot restore
When you restore an Amazon RDS for PostgreSQL instance from a snapshot, the Amazon EBS volume hydrates lazily, so early queries can run 10x to 15x slower. This post walks through PostgreSQL-native prewarming techniques (pg_prewarm, VACUUM ANALYZE, and full table scans) and new monitoring fields to restore predictable performance faster after restore.
Storage layout and best practices for Amazon RDS Custom for SQL Server
Amazon RDS Custom for SQL Server gives you OS-level access, which also exposes internal storage volumes where the W: drive looks like a raw, uninitialized disk. This post explains the C:, D:, and W: drive architecture, how the drives map to Amazon EBS, and the safe disk operations and verification checks that keep you from accidentally destroying your data.
Understanding the differences between PgBouncer and Amazon RDS Proxy for PostgreSQL connection pooling
Compare Amazon RDS Proxy and PgBouncer for PostgreSQL connection pooling on AWS. This post explains how each pooler handles pooling modes, authentication, failover, and session-state pinning, and gives you a framework to choose between a fully managed service and a self-managed pooler.
A decision framework for Amazon Neptune availability
When an Amazon Neptune workload needs resilience beyond a single cluster, this post presents a decision framework that maps availability targets to Neptune architectural patterns, from Multi-AZ and Global Database to write-ahead logs and caching, based on your RTO, RPO, and budget.
Resolving PostgreSQL replication lag with heartbeat tables in change data capture scenarios
Replication lag during a change data capture (CDC) migration can be counterintuitive: the source is busy, yet replication falls behind and WAL piles up. This post shows how to resolve PostgreSQL replication lag with heartbeat tables using AWS DMS or Debezium, and how to monitor replication slot health with Amazon CloudWatch and SQL diagnostics.
Resolving query plan regressions after a MySQL engine upgrade
After a major or minor version upgrade on Amazon Aurora MySQL or Amazon RDS for MySQL, some queries regress because the optimizer’s cost models, defaults, and execution strategies change. This post walks through a diagnostic workflow that traces each regression to the specific version change behind it and applies the right fix.
From noise to signal: Monitoring Amazon DocumentDB like a pro
Learn how to build a tiered alerting strategy for Amazon DocumentDB by organizing CloudWatch metrics into Critical, Warning, and Advisory tiers, diagnosing slow queries through three complementary lenses, and monitoring garbage collection health before it becomes a cluster-wide incident.









