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Overview As organizations adopt Generative AI using AWS, managing the underlying infrastructure becomes a critical FinOps challenge. Amazon Bedrock Knowledge Bases provide a powerful way to connect foundation models with your proprietary data using Retrieval-Augmented Generation (RAG). However, a single configuration—the Data Deletion Policy—can introduce significant operational risk and financial waste if overlooked. By default, […]

Overview As enterprises adopt Generative AI, services like Amazon Bedrock have become central to innovation, particularly for Retrieval-Augmented Generation (RAG) workloads. When you create a Knowledge Base in Bedrock, it ingests your proprietary data from sources like S3, processes it, and makes it available for AI models. This process creates temporary, or “transient,” copies of […]

Overview As organizations embrace Generative AI with services like Amazon Bedrock, the complexity of Identity and Access Management (IAM) grows exponentially. Bedrock often needs to interact with other AWS services like Amazon S3 or AWS Lambda, requiring a web of trust relationships built on IAM roles. If not configured with precision, these relationships can expose […]

Overview As organizations rapidly adopt Generative AI using Amazon Bedrock, a critical governance gap often emerges. While the service provides powerful access to foundation models, its default configuration does not log the content of model interactions. This creates a significant blind spot where prompts and responses—the core of your GenAI activity—occur without a detailed audit […]

Overview As enterprises integrate Generative AI into their operations using services like Amazon Bedrock, a new and complex attack surface emerges. A critical component of this ecosystem are Bedrock Guardrails, the policy layers that manage AI interactions to prevent harmful content and data leakage. However, the security of the Guardrails themselves is a frequently overlooked […]