Tag: technical how-to

In this post, we demonstrate how to use the advanced malware detection features of Amazon GuardDuty to uncover malicious and suspicious files compromising your Amazon Elastic Compute Cloud (Amazon EC2) instances. We use the investigative capabilities of Amazon Detective to gain deeper insights into the security event. After the key questions about the security event are addressed, we outline steps to remediate the potentially compromised EC2 instance.

In this blog, we will guide you through the process of setting up a secure multi-account AWS environment using AWS Control Tower, AWS IAM Identity Center, AWS Organizations and will show you how to secure your environment using AWS Config, AWS Security Hub, and Amazon GuardDuty.

This post demonstrates how to enhance security and compliance in an isolated SageMaker JupyterLab environment by implementing two key customizations: configuring download restrictions and implementing secure Python package installation through AWS CodeArtifact.

This post demonstrates how to build serverless workflows on AWS that process such data using AWS Step Functions and integrate with downstream systems that have concurrency limitations.

In this post, we demonstrate how to use the generative AI capabilities of Amazon Bedrock to streamline the creation of AWS Fault Injection Service (FIS) experiments.

Organizations adopting modern software development activities continue to embrace the advantages of AI and large language models (LLMs), maximizing the productivity of developers. Amazon Q Developer provides you with an AI coding companion that delivers direct access for developers to the AI companion within the integrated development environment (IDE). In this post, we walk you through an example you can use leveraging the power of Amazon Bedrock to provide a coding assistant in your IDE.

In this blog, we provide deployment guidance that is intended to help you get started quickly with Wickr Enterprise for capability testing.

Many government agencies, like the National Oceanic and Atmospheric Administration (NOAA), participate in the AWS Open Data Sponsorship Program. In this post, we discuss how to use NOAA datasets in the Registry of Open Data on AWS using Amazon Bedrock Knowledge Bases.

Many organizations validate their generative AI–based workloads on their emotional reaction to a foundation model’s output instead of real testing criteria. In this post, we show you how you can move away from vibe testing and effectively evaluate your Amazon Bedrock workloads for production.

As more and more healthcare companies use their data to remain competitive, protecting patient data is as critical than ever. With increasing adoption of AI/ML models in healthcare, making sure that these technologies comply with privacy regulations such as HIPAA and GDPR has become a top priority. Amazon Bedrock is a fully managed service that provides unified access to a diverse selection of high-performance foundation models from industry-leading AI companies. In this post, we walk you through the importance of healthcare data privacy and how to use Amazon Bedrock Guardrails to safeguard sensitive information in AI-driven healthcare solutions.