Category: RDS for SQL Server

In our previous post, Capture and tune resource utilization metrics for Amazon RDS for SQL Server,’ we demonstrated how to use Amazon RDS Enhanced Monitoring and Amazon RDS Performance Insights to diagnose and debug CPU utilization bottlenecks for Amazon Relational Database Service (Amazon RDS) for SQL Server. Aside from CPU and memory, I/O performance is critical for overall database performance. It’s important to understand the I/O requirements of a SQL Server workload, which is dependent on various factors like query access patterns, database schema, and state of database maintenance. Understanding your workload’s, I/O patterns can guide you in selecting the optimal storage type for your RDS instance, balancing performance needs with cost-effectiveness. In this post, we demonstrate how you can use Amazon RDS monitoring tools along with SQL Server monitoring capabilities to capture, diagnose, and resolve I/O issues on an RDS for SQL Server instance.

Customers who host their transactional database on Amazon Relational Database Service (Amazon RDS) often seek architecture guidance on building streaming extract, transform, load (ETL) pipelines to destination targets such as Amazon Redshift. This post outlines the architecture pattern for creating a streaming data pipeline using Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon MSK offers a fully managed Apache Kafka service, enabling you to ingest and process streaming data in real time.

In Part 1 of this post, we covered how Retrieval Augmented Generation (RAG) can be used to enhance responses in generative AI applications by combining domain-specific information with a foundation model (FM). However, we stayed focused on the semantic search aspect of the solution, assuming that our vector store was already built and fully populated. In this post, we explore how to generate vector embeddings on Wikipedia data stored in a SQL Server database hosted on Amazon RDS. We also use Amazon Bedrock to invoke the appropriate FM APIs and an Amazon SageMaker Jupyter Notebook to help us orchestrate the overall process.

Scopely is a global games developer, operator, and publisher with operations across North America, Central America, EMEA, and Asia, and additional studio partners spanning four continents. Over the past year, Scopely has served more than 500 million players with major titles such as “MONOPOLY GO!,” “Stumble Guys,” “MARVEL Strike Force,” “Star Trek Fleet Command,” and “Scrabble GO.” In this post, we showcase how Scopely used CloudBasix to enable migration of “Stumble Guys” high-volume backend transactional databases with minimal downtime from Azure SQL database to Amazon RDS for Server.

Amazon RDS Custom for SQL Server now allows you to directly join your DB instances to the domains of Microsoft Active Directory (AD). In this post, we show how to join RDS Custom DB instances to an AD for Windows Authentication. This applies to AD domains running in a self-managed environment either on premises or Amazon Elastic Compute Cloud (Amazon EC2) and AWS Managed Microsoft AD.

In this post, we discuss how to determine the causes of an INCOMPATIBLE_CREATE state of an RDS Custom instance because of incorrect instance profile permissions.

Amazon Relational Database Service (Amazon RDS) for SQL Server makes it straightforward to set up, operate, and scale SQL Server deployments in the AWS Cloud. The service allows DBAs to focus on high-value tasks such as query optimization, query construction, and schema design rather than time-consuming database administration tasks including provisioning, backups, software patching, monitoring, […]

Amazon RDS Custom for SQL Server allows up to 5,000 databases per instance. However, the number of databases that can be restored to a specific point in time using point-in-time recovery (PITR) depends on the instance class type. In this post, we show how to use native backup and restore commands to achieve PITR for databases that aren’t eligible because of the instance type limitation. We present two solutions: one applicable to all versions of RDS Custom for SQL Server and the other for RDS Custom for SQL Server version 2022.

In this post, we explain how to perform a database minor version upgrade (patch) with Multi-AZ on CEV instance, where RDS Custom performs rolling upgrades, so you have an outage only for failover period and the time needed for post-upgrade scripts until the instance is fully operational.

As businesses strive to integrate AI/ML capabilities into their customer-facing services and solutions, they often face the challenge of leveraging massive amounts of relational data hosted on on-premises SQL Server databases. This post showcases how Amazon Relational Database Service (Amazon RDS) for SQL Server and Amazon SageMaker Canvas can work together to address this challenge. By leveraging the native integration points between these managed services, you can develop integrated solutions that use existing relational database workloads to source predictive AI/ML models with minimal effort and no coding required.