Category: Best Practices

On October 22, 2024, we announced the availability of the Aurora Global Database writer endpoint, a highly available and fully managed endpoint for your global database that Aurora automatically updates to point to the current writer instance in your global cluster after a cross-Region switchover or failover, alleviating the need for application changes and simplifying routing requests to the writer instance. In this post, we dive deep into the new Global Database writer endpoint, covering its benefits and key considerations for using it with your applications.

Modern applications are built as a group of microservices, and the latency for one component can impact the performance of the entire system. Monitoring latency is critical for maintaining optimal performance, enhancing user experience, and maintaining system reliability. In this post, we explore ways to monitor latency, detect anomalies, and troubleshoot high-latency issues effectively for your self-designed (node-based) ElastiCache clusters.

Amazon MemoryDB is a Valkey– and Redis OSS-compatible, durable, in-memory database service that delivers ultra-fast performance. With MemoryDB, data is stored in memory with Multi-AZ durability, which enables you to achieve microsecond read and single-digit millisecond write latency and high throughput. MemoryDB is often used for building durable microservices and latency-sensitive database workloads such as […]

In this post, we provide details on two PostgreSQL plugins available for use by AWS DMS. We compare these plugin options and share test results to help database administrators understand the best practices and benefits of each plugin when working on migrations.

In this post, we discuss temporary tablespace and Flash Cache features with local NVMe SSD-based instance storage, configuration options, typical use cases, and feature availability by engine and storage configuration. We dive deep into the tiered cache capability and how it can improve the query performance of latency-sensitive workloads. We also provide an overview of the temporary object capability.

In this post, we provide a comprehensive guide for addressing performance considerations when migrating Oracle databases from Exadata to Amazon RDS for Oracle. We explore methods to analyze Exadata workload characteristics, including determining Smart IO usage, examining database-level I/O patterns, and identifying SQLs that utilize Exadata-specific features. We also discuss various alternatives available on RDS for Oracle to mitigate potential performance impacts.

Recently, Amazon RDS launched the ability to shrink storage volumes using Amazon RDS Blue/Green Deployments – a nice addition to the list of new use cases that Blue/Green Deployments now supports. In this post, we cover how to use the new storage volume shrink feature in Amazon RDS Blue/Green Deployments to minimize the downtime required to perform the storage size reduction operation. We also review various mechanisms to monitor the progress of storage shrink and best practices on how to arrive at the optimal storage size for your shrink storage task.

You can create an Amazon RDS for Db2 instance by using the AWS Management Console, AWS Command Line Interface (AWS CLI), AWS CloudFormation, Terraform by Hashicorp, AWS Lambda functions, or other methods. One of the prerequisites for creating an RDS for Db2 instance is to configure the virtual private cloud (VPC) appropriately. This post shows how to create a VPC with best practices for any Amazon RDS database in general and Amazon RDS for Db2 in particular through a one-click automated deployment.

With the recent addition of physical replication as an option for RDS Blue/Green Deployments, you can overcome most of the limitations of logical replication. This makes physical replication particularly well-suited for use cases like minor version upgrades, schema changes (DDL operations) in the blue environment, and storage adjustments. In this post, we delve into the advantages of using physical replication in RDS for PostgreSQL blue/green deployments to simplify database operations and scale with application demands. We explore the key benefits of physical replication and provide a step-by-step guide to help you get started with this new capability.

Flo is the largest app in the Health and Fitness category worldwide, with 70 million monthly active users. In this post, we explain best practices Flo implemented to scale to more than 70 million monthly active users while achieving 60% cost efficiency with Amazon DynamoDB.