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Get per-identity Amazon Bedrock cost visibility and enforceable spend limits using only AWS-native features, with no application code for the common case. Attribute spend with IAM principal tags, report with CUR 2.0 or Cost Explorer, and enforce with AWS Budgets actions that apply a Deny policy when a threshold is crossed.
Build a self-service LLM gateway with LiteLLM on AWS Fargate that puts Amazon Bedrock foundation models behind an OpenAI-compatible API. Developers get instant access through a single API key, while platform teams gain per-user cost controls, quota isolation, and observability.
The migration guide in the amazon-bedrock skill helps you migrate a customer-managed Amazon Bedrock knowledge base to a Managed Knowledge Base. Your coding agent plans the move with read-only discovery, creates the new knowledge base or an infrastructure-as-code template alongside the original, and validates retrieval before you cut over.
Build a composable, interoperable multi-agent system on AWS with the Agent-to-Agent (A2A) protocol. A LangChain orchestrator on Amazon ECS communicates with a Strands agent on Amazon Bedrock AgentCore across organizational boundaries, using bidirectional, OAuth-authenticated calls, with neither side depending on the other's framework or SDK.
Learn how to expose an Amazon Bedrock Managed Knowledge Base to AI agents as MCP tools through Amazon Bedrock AgentCore Gateway while keeping per-user access control. A request interceptor injects verified identity, Policy in AgentCore validates it independently, and a resource-based policy restricts direct access to the knowledge base.
Agents stall between demo and release when teams lack a repeatable way to measure how good an agent is and whether the last change helped. This post covers three agent properties that break traditional CI/CD, a measured case where an aggregate metric hides a coverage gap, and Agent DLC: one lifecycle, two loops, and one explicit standard for judging every…
Language model (LM) alignment improves model outputs to reflect human preferences while preserving the capabilities of the base model. The most common alignment approaches are (i) reinforcement learning, which maximizes the expected reward under a KL-divergence constraint, and (ii) best-of-NNN alignment, which selects the highest-reward output among NNN independent samples. Despite their widespread use, the fundamental limits of reward improvement…
A practical guide for enterprises rolling out OpenAI Codex to developers on AWS, with Amazon Bedrock as the model backend, covering the access, governance, and cost decisions that platform, security, and finance teams need to align on.
A textual diff of two formal policies flags every cosmetic change and hides the one that alters behavior. This post shows how to compute a symbolic, deterministic semantic diff with an open-source anti-unification engine, so reviewers see only the genuine disagreements between two candidate authorization policies.
AWS re:Invent 2026 includes more than 140 AI/ML track sessions. This attendee's guide helps you find the breakouts, chalk talks, workshops, and builders' sessions that fit your role and goals, spanning AI chips, models and inference, agents, agent trust, and sustainability, so you can build a smarter re:Invent schedule.
Every generative AI team keeps rebuilding the same components: RAG pipelines, document processors, and agent scaffolding. This post shows how to access a curated catalog of 23 production-ready, open source reusable assets from the AWS Generative AI Innovation Center, with real delivery results from DoorDash, Lyft, and Ricoh.
Learn how to build an AI-driven product development lifecycle (AI-PDLC) with a suite of six AWS Quick agents that take you from scattered customer signals to a validated prototype across Discover, Decide, Design, and Prototype, with human approval at every gate and a specification ready to hand to coding agents like Kiro.
The Universal Agent Evaluation Framework (UAEF) is a framework-agnostic system for evaluating AI agents. UAEF converts each framework's traces into one canonical format, scores them with 36 built-in metrics across 7 dimensions, and stores results so teams can compare agent versions and catch regressions.
AWS Marketplace now supports usage-based metering for Amazon SageMaker bidirectional streaming inference, so model providers can charge for what customers actually consume during a live stream. Deepgram is the launch partner, bringing usage-based speech-to-text and text-to-speech billing to AWS Marketplace.
