Recently, AWS released Amazon Bedrock API keys to make calls to the Amazon Bedrock API. In this post, we provide practical security guidance on effectively implementing, monitoring, and managing this new option for accessing Amazon Bedrock to help you build a comprehensive strategy for securing these keys. We also provide guidance on the larger family […]| AWS Security Blog
Amazon Bedrock Guardrails provides configurable safeguards to help you safely build generative AI applications at scale. It offers integrated safety and privacy protections that work across multiple foundation models (FMs), including models available in Amazon Bedrock and models hosted outside Amazon Bedrock from other providers. Bedrock Guardrails currently offers six key safeguards to help prevent […]| AWS Security Blog
October 22, 2025: This post was updated to reflect additional IAM permissions necessary for Amazon Bedrock serverless models offered through AWS Marketplace. Amazon Bedrock has simplified how you access foundation models, streamlining the integration of AI capabilities into your applications. Here’s what’s changed and how to maintain control over model access in your organization. What’s […]| AWS Security Blog
Generative AI agents in production environments demand resilience strategies that go beyond traditional software patterns. AI agents make autonomous decisions, consume substantial computational resources, and interact with external systems in unpredictable ways. These characteristics create failure modes that conventional resilience approaches might not address. This post presents a framework for AI agent resilience risk analysis […]| Amazon Web Services
As generative AI becomes foundational across industries—powering everything from conversational agents to real-time media synthesis—it simultaneously creates new opportunities for bad actors to exploit. The complex architectures behind generative AI applications expose a large surface area including public-facing APIs, inference services, custom web applications, and integrations with cloud infrastructure. These systems are not immune to […]| AWS Security Blog
In Part 1 of this series, we explored the fundamental risks and governance considerations. In this part, we examine practical strategies for adapting your enterprise risk management framework (ERMF) to harness generative AI’s power while maintaining robust controls. This part covers: Adapting your ERMF for the cloud Adapting your ERMF for generative AI Sustainable Risk […]| AWS Security Blog
According to BCG research, 84% of executives view responsible AI as a top management responsibility, yet only 25% of them have programs that fully address it. Responsible AI can be achieved through effective governance, and with the rapid adoption of generative AI, this governance has become a business imperative, not just an IT concern. By […]| AWS Security Blog
Reimagine AIOps with Amazon CloudWatch Investigations and Amazon Nova Sonic in Amazon Bedrock to transform how cloud operations teams handle incidents. Traditional monitoring approaches require engineers to navigate multiple complex dashboards, analyze extensive logs, and manually execute remediation steps—a process that becomes particularly challenging during after-hours incidents or when away from workstations. When minutes matter […]| AWS Cloud Operations Blog
As organizations rapidly deploy large language models (LLMs) and generative AI agents to power increasingly intelligent workloads, they struggle to monitor and troubleshoot the complex interactions within their AI applications. Traditional monitoring tools fall short in providing the visibility across components, leading to developers and AI/ML engineers to manually correlate interaction logs or building custom […]| Amazon Web Services
Today, I’m excited to share how we’re bringing this vision to life with new capabilities that address the fundamental aspects of building and deploying agents at scale. These innovations will help you move beyond experiments to production-ready agent systems that can be trusted with your most critical business processes.| Amazon Web Services
In this post, we introduce an automated, GitOps-driven approach to resource optimization in Amazon EKS using AWS services such as Amazon Managed Service for Prometheus and Amazon Bedrock. The solution helps optimize Kubernetes resource allocation through metrics-driven analysis, pattern-aware optimization strategies, and automated pull request generation while maintaining GitOps principles of collaboration, version control, and auditability.| Amazon Web Services
Learn how to vectorize your e-commerce product data using AWS Titan's multimodal model. This practical guide covers generating embeddings for both images and text, and building vector search using cosine and dot product similarity for improved product recommendations| AI Agents That Work Blog
Amazon Bedrock AgentCore enables rapid deployment and scaling of AI agents with enterprise-grade security. It provides memory management, identity controls, and tool integration—streamlining development while working with any open-source framework and foundation model.| Amazon Web Services
In this post, you learn how you can use generative AI services on Amazon Web Services (AWS) to automate your sustainability reporting requirements, reduce manual effort, and improve accuracy. You do this by implementing an automated solution for extracting, processing, and validating data from corporate reports.| AWS Architecture Blog
In this post, we explore the Amazon Bedrock baseline architecture and how you can secure and control network access to your various Amazon Bedrock capabilities within AWS network services and tools. We discuss key design considerations, such as using Amazon VPC Lattice auth policies, Amazon Virtual Private Cloud (Amazon VPC) endpoints, and AWS Identity and Access Management (IAM) to restrict and monitor access to your Amazon Bedrock capabilities.| Amazon Web Services
Organizations managing large audio and video archives face significant challenges in extracting value from their media content. Consider a radio network with thousands of broadcast hours across multiple stations and the challenges they face to efficiently verify ad placements, identify interview segments, and analyze programming patterns. In this post, we demonstrate how you can automatically transform unstructured media files into searchable, analyzable content.| Amazon Web Services
https://hidekazu-konishi.com/entry/amazon_bedrock_models_as_of_2024.html Amazon Bedrock Models as of 2024 - An Analysis of the Comprehensive Model Catalog.| Hidekazu Konishi - Profile / Biography | hidekazu-konishi.com
https://hidekazu-konishi.com/entry/amazon_bedrock_claude_and_textract_ocr_accuracy_evaluation.html Evaluating OCR Accuracy of Claude on Amazon Bedrock and Amazon Textract Using Similarity Metrics.| Hidekazu Konishi - Profile / Biography | hidekazu-konishi.com
Using Claude 3.7 Sonnet Vision Capabilities on Amazon Bedrock to Verify, Regenerate, and Automate Image Generation with Stable Diffusion 3.5 Large.| hidekazu-konishi.com
Ready to level up your AI game and step into the future? Find out how Amazon Bedrock’s RAG Evaluation and LLM-as-a-Judge are setting the stage for a new era in artificial intelligence.| Indium
DeepSeek-R1, a powerful large language model featuring reinforcement learning and chain-of-thought capabilities, is now available for deployment via Amazon Bedrock and Amazon SageMaker AI, enabling users to build and scale their generative AI applications with minimal infrastructure investment to meet diverse business needs.| Amazon Web Services
Using Amazon Nova Pro Vision Capabilities on Amazon Bedrock to Verify, Regenerate, and Automate Image Generation with Amazon Nova Canvas.| hidekazu-konishi.com
Amazon Nova foundation models deliver frontier intelligence and industry leading price-performance, with support for text and multimodal intelligence, multimodal fine-tuning, and high-quality images and videos.| Amazon Web Services
Discover the best AI development tools in Amazon Bedrock Studio to accelerate generative AI development. Click to optimize your workflow now!| Govindhtech
Using Claude 3.5 Sonnet Vision Capabilities on Amazon Bedrock to Verify, Regenerate, and Automate Image Generation with Amazon Titan Image Generator G1.| hidekazu-konishi.com
The tri-party solution built using the Denodo Platform, HCLTech’s clinical data management system, and AWS Cloud provides a breakthrough solution, thus enabling a unified approach to the clinical trial data.| Data Management Blog - Data Integration and Modern Data Management Articles, ...
In September 2023, we announced a strategic collaboration with Anthropic that brought together their respective technology and expertise in safer generative artificial intelligence (AI), to accelerate the development of Anthropic’s Claude foundation models (FMs) and make them widely accessible to AWS customers. You can get early access to unique features of Anthropic’s Claude model in […]| Amazon Web Services
Basic Information about Amazon Bedrock with API Examples - Model Features, Pricing, How to Use, Explanation of Tokens and Inference Parameters.| hidekazu-konishi.com
