Integration & Automation

In this post, we explore a comprehensive AWS architecture that transforms smart inhaler data into actionable clinical insights through real-time monitoring and advanced analytics. Healthcare organizations can leverage AWS IoT Core, Amazon MSK, and Amazon Redshift to build secure, scalable solutions that enable proactive respiratory care management and improved patient outcomes.

In this post, AWS and Ziff Davis collaborated to tackle server management challenges by implementing an automated solution using EC2 Image Builder and AWS Systems Manager. The solution addressed issues of inconsistent configurations, undocumented processes, and manual patching, resulting in improved efficiency, consistency, and disaster recovery capabilities for Ziff Davis’s virtual phone number services.

In this post, we demonstrate how to optimize message delivery to third-party services using AWS Lambda and AWS Step Functions by implementing adaptive scaling strategies based on throttling patterns. We describe how YOOX, a leading online fashion retailer, improved their product update delivery system by using AWS Serverless services to achieve a 95% success rate within 10 minutes of job start while maintaining efficient message processing.

In this post, we show how to implement automated reporting for AWS Backup Vault Lock status across accounts in your organization. The solution uses AWS Organizations, the AWS Command Line Interface (AWS CLI), and cross-account access to create vault lock compliance reports.

In this post, we highlight how Fortra partnered with AWS to develop an innovative approach for automating security compliance checks and remediation across complex, multi-account, multi-Region organizations.

In this post, we demonstrate how to build an enterprise AI assistant solution that uses LLMs in Amazon Bedrock with the precision of enterprise knowledge bases using the RAG approach. By integrating AWS services such as Lambda and Amazon Bedrock, our solution enables organizations to securely access and retrieve proprietary data, providing contextually relevant and accurate responses. The RAG approach not only enhances the assistant’s ability to provide tailored responses within specific enterprise data domains, but also mitigates the risk of hallucinations. By injecting the latest enterprise proprietary knowledge into the response generation context, our solution makes sure that the assistant remains up-to-date and adaptable to evolving specific business needs. The sample code repository and CloudFormation template can enable organizations to streamline the development and deployment of their RAG-based AI assistant solutions.

Deploying AWS Elastic Disaster Recovery at scale provides robust protection for your infrastructure. The DRS Settings Tool is an invaluable resource for updating settings across your infrastructure efficiently. In this post, we show you how to setup and use the DRS Settings Tool to update all your Elastic Disaster Recovery source server settings in bulk.

In this post, we detail the concepts, processes, and steps to get started with policy as code (PaC) and adopt this into your software development lifecycle. PaC can improve your overall security posture, improve consistency of service usage across your organization, and reduce rework or workloads deployed to your AWS accounts.

As organizations increasingly adopt Amazon Elastic Kubernetes Service (Amazon EKS) to manage their containerized applications, implementing robust security measures and maintaining compliance become critical. The scalable and flexible nature of Amazon EKS has made it a popular choice for businesses seeking to streamline their application deployment and management processes. However, with this adoption comes the […]

This blog post guides you through implementing a generative AI intelligent chatbot using Amazon Bedrock and AWS services, including developer lifecycle changes. It covers creating a scalable chatbot infrastructure with Terraform, using services like Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, OpenSearch Service, Lambda, Amazon S3, and IAM. The focus on IaC and automation brings key DevOps benefits: version control, consistent deployments, reduced errors, faster provisioning, and improved collaboration.