Category: Enterprise Strategy

This is a three-part series in which we discuss the end-to-end process of building a data lake from a legacy SQL Server database. In this post, we show you how to build data pipelines to replicate data from Microsoft SQL Server to a data lake in Amazon S3 using AWS DMS. You can extend the solution presented in this post to other database engines like PostgreSQL, MySQL, and Oracle.

This is the third post in a series where we dive deep into performance testing of MySQL environments being migrated from on premises. In Part 1, we compared the query playback and traffic mirroring approaches at a high level. In Part 2, we showed how to set up and configure query playback. In this post, we show you how to set up and configure traffic mirroring.

This is the second post in a series where we dive deep into performance testing MySQL environments being migrated from on premises. In Part 1, we compared the query playback and traffic mirroring approaches at a high level. In this post, we dive into the setup and configuration of query playback.

In this series of posts, we dive deep into performance testing of MySQL environments being migrated from on-premises to AWS. In this post, we review two different approaches to testing migrated environments with traffic that is representative of real production traffic: capturing and replaying traffic using a playback application, and mirroring traffic as it comes in using a proxy. This means you’re validating your environment using realistic data access patterns.

In this post, we show you how to migrate an Oracle database to an Amazon RDS for Oracle DB instance. The solution uses Oracle Data Pump for initial data load and Oracle GoldenGate Microservices Architecture installed on an Amazon Elastic Compute Cloud (Amazon EC2) instance as the Oracle GoldenGate hub for change data capture.

In this post, we discuss how Phreesia used AWS DMS to replicate their on-premises database to AWS in an effective and cost-optimized manner. Because of the database’s large size and complex data structure, properly tuning the AWS DMS configuration was critical to minimize the migration duration and cost. We outline the fine-tuning techniques that were applied to optimize the AWS DMS task settings, instance size, IOPS provisioning, and table mappings. Applying these performance optimizations allowed Phreesia to develop a migration strategy to move this 30 TB database to Amazon S3 in just 2 days without disruption to production workloads.

With AWS DMS homogenous migration, you can migrate data from your source database to an equivalent engine on AWS using native database tools. In this post, we show you an example of a complete homogeneous migration process and provide troubleshooting steps for migrating from PostgreSQL to Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL.

In this post, we show you how to use advanced replication features between MySQL-compatible databases such as Amazon Aurora MySQL-Compatible Edition clusters or Amazon Relational Database Service (Amazon RDS) for MySQL instances. We discuss two replication capabilities in Amazon RDS and Amazon Aurora: multi-source replication and replication filtering. Multi-source replication is supported only in Amazon […]

Cloud computing has changed almost every business and industry by changing the delivery and consumption model. With the Cloud, businesses no longer need to plan for and procure servers and other IT infrastructure weeks or months in advance. This allows more flexibility and reliability, increased performance and efficiency, and helps to lower IT costs. The […]

This is the first in a two-part series of posts on how to migrate a multi-TB database to Amazon Relational Database Services (Amazon RDS) Custom for SQL Server. Amazon RDS Custom for SQL Server is a managed database service that automates setup, operation, backups, high availability, and scaling of databases while granting access to the […]