Category: Advanced (300)

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.

SQL Server stored procedures can return multiple result sets from one call, but PostgreSQL cannot. This post presents two PostgreSQL-native alternatives to refcursors, session-scoped temporary tables and JSON aggregation, compares both against a refcursor baseline, and shows how to implement and validate each in .NET and Npgsql.

This post shows how to compose a Bloom filter with an exact-match cache and a relational source of truth into a three-tier, correctness-safe membership lookup using Amazon ElastiCache for Valkey and Amazon Aurora PostgreSQL, serving sub-millisecond decisions at peak throughput without false-positive risk.

Learn how Intuit and AWS validated Amazon ElastiCache resilience under a real Availability Zone impairment using AWS Fault Injection Service, cutting recovery from over 50 minutes to under 2 minutes with no manual intervention and reducing customer impact to effectively zero.

Part 1 showed how row lock contention degrades Amazon Aurora PostgreSQL throughput. In Part 2, use Amazon CloudWatch Database Insights and its Lock Tree to pinpoint blocking sessions, then resolve contention with query termination, timeout parameters, and architectural patterns such as SKIP LOCKED and row splitting that restore throughput.

Row lock contention can collapse database throughput during a flash sale even when CPU and I/O look healthy. In Part 1 of this series, learn how PostgreSQL row locking works and how to monitor lock contention in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL using system views, the pgrowlocks extension, and the log_lock_waits parameter.

Run ad hoc SQL analytics on your Amazon DynamoDB data with DuckDB. A zero-ETL integration replicates your table into Apache Iceberg tables on Amazon S3 Tables, and an AWS Lambda function running DuckDB serves SQL queries through an IAM-authorized function URL.

Build a high-concurrency async Python rideshare application with Tortoise ORM and Amazon Aurora DSQL. This post walks through the key adaptations: UUID primary keys, IAM-authenticated asyncpg connections with a connection-pool patch, individual DDL execution, and optimistic concurrency control (OCC) retry logic.

Configuring the AWS Advanced JDBC Wrapper for Amazon Aurora Global Database with write forwarding requires Region-specific settings, and misconfiguration causes latency spikes and connection failures. This post walks through the correct dialect, plugins, host patterns, and write forwarding settings for the primary and secondary Regions.

Announcing strands-dynamodb-storage, an open source Amazon DynamoDB storage backend for the Strands Agents SDK. Back a Strands agent’s session state, long-term memories, and transcripts with one DynamoDB table in your own account, and give the agent semantic recall with a vector index on that same table.