Category: Generative AI

With the emergence of generative AI being incorporated into every aspect of how we utilize technology, a common question that customers are asking is how to properly audit generative AI services on AWS, such as Amazon Bedrock, Amazon Sagemaker, Amazon Q Developer, and Amazon Q Business. In this post, we will demonstrate common scenarios that […]

Overview When operating complex, distributed systems in the cloud, quickly identifying the root cause of issues and resolving incidents can be a daunting task. Troubleshooting often involves sifting through metrics, logs, and traces from multiple AWS services, making it challenging to gain a comprehensive understanding of the problem. So how can you streamline this process […]

Amazon Q, is a new generative artificial intelligence- (AI)-powered assistant designed for work that can be tailored to your business. You can use Amazon Q to have conversations, solve problems, generate content, gain insights, and take action by connecting to your company’s information repositories, code, data, and enterprise systems. Amazon Q provides immediate, relevant information […]

The recent rise of generative artificial intelligence (generative AI) solutions presents challenges to migrations that are in flight and to migrations that are just beginning. The business problem is that generative AI complicates cloud migrations by introducing additional risks related to data isolation, data sharing, and service costs. For example, the US Space Force has […]

AWS CloudTrail tracks user and API activities across your AWS environments for governance and auditing purposes. Large enterprises typically use multiple AWS accounts, and many of those accounts might need access to a data lake managed by a single AWS account. By using Lake Formation integration with CloudTrail Lake, you can securely aggregate the data […]

In Part 1 of this series, you learned about Blue/Green testing and deployment on AWS, a key strategy that increases application availability and reduces deployment risk by simplifying the rollback process if a deployment fails. We explored live replication using AWS Application Migration Service (AWS MGN) and introduced prebuilt post-launch actions with AWS Systems Manager […]