AWS Database Blog
Another Database Migration Playbook goes live—migrate from Microsoft SQL Server to Amazon Aurora MySQL!
We’re excited to present the first edition of the Microsoft SQL Server to Amazon Aurora MySQL Compatibility Migration Playbook. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) help you reduce the effort associated with migration from commercial engines to open-source and Amazon-managed databases. Thus, they help reduce cost and avoid […]
Read MoreMonitor your Microsoft SQL Server using custom metrics with Amazon CloudWatch and AWS Systems Manager
In this blog post, we show you how to configure the CloudWatch agent on Amazon EC2 Windows instances to capture custom metrics for SQL Server from Windows performance monitor. We also show you how to publish those custom metrics and monitor them on Amazon CloudWatch console. We also walk you through on how to store custom configuration in AWS Systems Manager Parameter Store used by CloudWatch agent to capture those metrics and reuse the same configuration across multiple fleets of SQL Server instances where similar kind of metrics are needed.
Read MoreBest practices for securing sensitive data in AWS data stores
This blog post focuses on general data security patterns and corresponding AWS security controls that protect your data. Although I mention Amazon RDS and DynamoDB in this post, I plan to cover the implementation-specific details related to Amazon RDS and DynamoDB in two subsequent posts.
Read MoreAmazon RDS Under the Hood: Single-AZ instance recovery
This post describes Amazon RDS Single-AZ RTO and RPO expectations for MySQL, MariaDB, PostgreSQL, Oracle, and Microsoft SQL Server databases. Amazon Aurora uses a different technology and storage subsystem designed for the cloud. Its single instance recovery process and scenarios are described in the Aurora FAQ.
Read MoreHow to use Amazon DynamoDB global tables to power multiregion architectures
More and more, AWS customers want to make their applications available to globally dispersed users by deploying their application in multiple AWS Regions. These global users expect fast application performance. In this post, I describe how to use Amazon DynamoDB to power the database of a global backend deployed in multiple AWS Regions. I use […]
Read MoreAnalyze user behavior using Amazon Elasticsearch Service, Amazon Kinesis Data Firehose and Kibana
Let’s assume that you work for an ecommerce company and you want to provide the best user experience to your customers. A customer could land on a product page by coming from a recommendation on another page in your application or from a search engine. Whatever the route, you want to ensure that your customers […]
Read MoreHow to use DynamoDB global secondary indexes to improve query performance and reduce costs
In this post, I demonstrate several ways to use global secondary indexes to query your data, accelerate your application’s performance, and reduce your monthly DynamoDB bill.
Read MoreIntuit story: Automate migration from on-premises MySQL to Amazon Aurora
Databases are core to many of our applications at Intuit. The database team has been working out which architecture to standardize on and what run books and tools to build in order to migrate and then operate in the cloud. We realized that the fastest way to resolve our questions would be to take one of our existing on-premises applications and run it through an actual migration to Amazon Aurora.
Read MoreUse virtual partitioning in the AWS Schema Conversion Tool
In this post, we look at how to use virtual partitioning to optimize your data warehouse migrations using AWS SCT. Virtual partitioning speeds up large table extraction using parallel processing. It is a recommended best practice for data warehouse migrations.
Read MoreHow to use the new Amazon DynamoDB key diagnostics library to visualize and understand your application’s traffic patterns
Today, we released the Amazon DynamoDB key diagnostics library, which enables you to view graphs and dashboards of your most accessed database items. A DynamoDB table can be used in two different capacity modes—provisioned and on-demand. DynamoDB automatically supports your access patterns as long as the traffic against a given item does not exceed 3,000 […]
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