Category: Amazon Aurora

Standard upgrade paths break active Debezium CDC replication slots on Amazon Aurora PostgreSQL, forcing hours-long re-snapshots. This post shows how to use native PostgreSQL logical replication to bridge a source and target cluster and cut your Debezium connectors over to the new major version with a brief, measured write pause and no re-snapshot.

When an Amazon RDS or Amazon Aurora PostgreSQL certificate expires and client trust stores aren’t updated, connections fail without warning. This post shows how to enforce TLS for all PostgreSQL connections, configure client-side certificate verification, and deploy automated monitoring that alerts you before certificate rotation events.

Learn how to configure connection pooling for the AWS Advanced JDBC Wrapper on Amazon Aurora and Amazon RDS. This post explains how the wrapper’s external and internal pooling differ, how to choose between them, and how the JDBC-WRAPPER-CONFIGURATION-ASSISTANT helps you build the right configuration.

Learn how to set up the Amazon Aurora DSQL MCP server and use it from your AI coding assistant to run queries, evolve schemas, and check Aurora DSQL compatibility without leaving your IDE. This post walks through installation, the available MCP tools, practical integration patterns, and the security model.

Learn how to use the calling services feature in Amazon CloudWatch Database Insights to identify which applications are calling your databases and view their performance metrics, so you can pinpoint root causes and contact the right team in minutes rather than hours.

In this post, we provide practical guidance for designing applications that scale effectively with the Amazon Aurora DSQL distributed architecture. You will learn how to identify common patterns that limit scalability, apply proven design patterns that distribute workload efficiently, and implement transaction strategies optimized for Aurora DSQL. We cover primary key selection, schema design principles, indexing strategies, and multi-Region optimization, while maintaining full ACID (atomicity, consistency, isolation, and durability) compliance across AWS Regions.

In this post, we show how you can build a multi-Region active-active API using Prisma ORM and Amazon Aurora DSQL.

In this post, we demonstrate a serverless approach to continuous forensic artifact collection for Amazon RDS and Amazon Aurora databases. By capturing point-in-time snapshots of database internals on a cadence and storing them in Amazon S3, you create a time-series record that AI tools can analyze in seconds. This turns what was hours of manual investigation into an instant conversation.

Managing payment infrastructure at scale presents unique challenges that impact both performance and operational efficiency. In this post, we share the technical and operational challenges Nubank faced with self-managed PostgreSQL, the evaluation criteria they established for selecting database solutions, and the results from their successful migration to Amazon Aurora PostgreSQL-Compatible Edition. Nubank achieved up to 1,900x query performance improvements in specific cases.

In this post, you’ll learn four concrete strategies that help you reduce Aurora DSQL connection overhead, stay within the 100-connections-per-second rate limit, and avoid thundering-herd reconnection storms. By the end, you’ll have a production-ready checklist for configuring connection pools that support reliable performance at scale.