Category: Intermediate (200)

In this post, you will learn how CRED built an automated orchestration framework around Amazon RDS blue/green deployments. The framework performs engine upgrades, instance scaling, storage optimization, and Change Data Capture (CDC) pipeline migration across their entire fleet. This approach achieved zero data loss incidents and zero production incidents.

In this post, you learn how to design and implement a user authentication service with session management on Amazon Aurora DSQL. You see the full request flow from client to database and back, explore the design considerations specific to Amazon Aurora DSQL, and discover practical lessons from building and testing against a live cluster.

Amazon ElastiCache now supports Valkey 9.1, bringing the latest community-driven innovations from the Valkey open source project to customers running latency-sensitive, high-throughput, and operationally demanding in-memory workloads on ElastiCache. In this post, we discuss how Valkey 9.1 helps you get more throughput and memory efficiency from demanding workloads while providing stronger isolation for multi-tenant and shared-cluster deployments. We also cover new commands that simplify common application and operational workflows, new observability features that give operators better visibility into engine behavior, and how ElastiCache continues to deliver the latest Valkey open source innovations in a fully managed service.

In this post, we share how Securonix migrated hundreds of Amazon ElastiCache clusters from Redis OSS to Valkey, achieving a 20% reduction in caching costs. This amounts to over $100,000 in annualized savings. The migration also improved CPU utilization and overall throughput across Securonix’s global SIEM platform, which processes hundreds of terabyte data volumes daily for enterprise security teams worldwide.

This is Part 1 of a two-part series covering the key features in PostgreSQL 18. In this post, we focus on performance enhancements: skip scan optimization for multicolumn indexes, enhanced EXPLAIN output, automatic removal of unnecessary self-joins, and several vacuum and autovacuum improvements that help keep your database running efficiently.

In Part 1 of this series, we explored the performance enhancements in PostgreSQL 18, including skip scan optimization, enhanced EXPLAIN output, automatic self-join removal, and vacuum/autovacuum improvements. In this second part, we focus on security, monitoring, developer productivity, and logical replication enhancements that improve operational efficiency and the overall developer experience.

Amazon RDS for SQL Server recently launched Bring Your Own Media (BYOM), so you can use your existing SQL Server licenses with fully managed RDS instances. This is particularly valuable if you have existing Microsoft licensing agreements and want to optimize your cloud spending by using those investments on AWS. If you’re already running RDS for SQL Server with the license-included (LI) model, you can now convert those instances to BYOM in place, no database migration required. In this post, we walk you through the end-to-end conversion process: preparing your installation media, creating a BYOM engine version, and performing the in-place license model change.

Managing Aurora PostgreSQL-Compatible Edition upgrades across multiple database clusters can be time-consuming and error-prone when done manually. In this post, we show you how to automate Amazon Aurora PostgreSQL upgrades across your entire database fleet through consistent, repeatable procedures.

In this post, you learn three pagination techniques for Aurora DSQL: OFFSET/LIMIT, cursor-based (keyset), and temporal. You implement keyset pagination in SQL and Python, build it into an API layer, optimize with composite indexes, handle batch processing within the 3,000-row transaction limit, and avoid five common anti-patterns. By the end, you can choose the right pagination method for your workload and implement it with confidence.

In this post, we explore the key reasons why Oracle Database@AWS is a strong fit for organizations running Oracle workloads on AWS. We cover the business, technical, and licensing advantages it brings, and how it complements the existing AWS options you already know, such as Amazon RDS for Oracle and Amazon EC2.