Category: Intermediate (200)

Amazon Q Developer, a generative artificial intelligence (AI) assistant, can help accelerate the development of applications on AWS. In this post, we create a DynamoDB table using IaC then perform create, read, update, and delete (CRUD) operations on the table using Python and Boto3 (with additional observations for JavaScript and Java at the end of the post). We demonstrate how Amazon Q can improve your speed of development for these tasks.

Amazon DynamoDB is a serverless, NoSQL, fully managed database service that delivers single-digit millisecond latency at any scale. AWS recently announced the limited preview of attribute-based access control (ABAC) for Amazon DynamoDB. ABAC is an authorization strategy that defines permissions based on attributes. In AWS, these attributes are called tags. You can attach tags to […]

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.

Customers migrating Oracle databases to Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL might encounter the challenge of scheduling jobs that require precise sub-minute scheduling to avoid workflow disruptions and maintain business operations. In this post, we demonstrate how you can use Trusted Language Extensions (TLEs) for PostgreSQL to install and use pg_dbms_job on Amazon Aurora and Amazon RDS. pg_dbms_jobs allows you to manage scheduled sub-minute jobs.

A primary reason companies move their workloads to AWS is because of cost. With AWS, cloud migration and application modernization plans are based on your business needs and not agreements or licensing. You can acquire technology on an as-needed basis, only paying for the resources you use. You can build modern, scalable applications on AWS […]

In this post, we explore approaches that address operating Amazon Neptune in a multi-tenant SaaS environment, as well as the considerations that may influence how and when to apply these strategies depending on your tenant needs.

Amazon Neptune Analytics now supports openCypher queries over RDF graphs. When you build an application that uses a graph database such as Amazon Neptune, you’re typically faced with a technology choice at the start: There are two different types of graphs, Resource Description Framework (RDF) graphs and labeled property graphs (LPGs), and your choice of […]

Amazon DynamoDB continuously sends metrics about its behavior to Amazon CloudWatch. Something I’ve heard customers ask for is how to get a count of successful requests of each operation type (for example, how many GetItem or DeleteItem calls were made) in order to better understand usage and costs. In this post, I show you how to retrieve this metric.

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.

Prowler for AWS provides hundreds of security configuration checks across services such as Amazon Redshift, Amazon ElasticCache, Amazon API Gateway, Amazon CloudFront, and many more. In this post, we focus on these new and expanded Amazon RDS security checks, their integration with AWS Security Hub, and the benefits they offer AWS users.