AWS published a step-by-step implementation guide for accessing Claude Platform on AWS (CPonAWS) from three environments: AWS workloads, developer laptops, and external CI/CD or other-cloud services. It uses a dedicated AI Services account, cross-account SigV4, workspace-scoped API keys, and OIDC federation, all sharing one subscription with workspace-level isolation between production and development traffic.
Anthropic introduced Claude apps gateway, a self-hosted governance layer for Claude Code and Claude Desktop on AWS, providing centralized controls over authentication, model access, cost attribution, and spend enforcement. It integrates with Amazon Bedrock and Claude Platform on AWS, reducing operational overhead for enterprise administrators.
Anthropic introduced Claude apps gateway, a self-hosted governance layer for Claude Code and Claude Desktop on AWS, providing centralized controls over authentication, model access, cost attribution, and spend enforcement. It integrates with Amazon Bedrock and Claude Platform on AWS, reducing operational overhead for enterprise administrators.
CleanPrompt is a single-page web utility that automatically masks secrets like API keys, JWTs, emails, and IPs in text before developers paste it into ChatGPT or Claude. It runs entirely client-side in the browser with no backend, so sensitive data never leaves the user's machine. It solves the risk of accidentally leaking credentials or private data when sharing code and logs with LLMs.
CleanPrompt is a single-page web utility that automatically masks secrets like API keys, JWTs, emails, and IPs in text before developers paste it into ChatGPT or Claude. It runs entirely client-side in the browser with no backend, so sensitive data never leaves the user's machine. It solves the risk of accidentally leaking credentials or private data when sharing code and logs with LLMs.
A US-headquartered global organization required Claude Code on Amazon Bedrock to process all inference in London (eu-west-2), not just be called from there. The team tried Anthropic's Mantle endpoint first but hit a limitation, then fell back to an alternative approach. The post details how they achieved single-Region data residency for Claude Code.
A US-headquartered global organization required Claude Code on Amazon Bedrock to process all inference in London (eu-west-2), not just be called from there. The team tried Anthropic's Mantle endpoint first but hit a limitation, then fell back to an alternative approach. The post details how they achieved single-Region data residency for Claude Code.
An AWS Machine Learning blog post presents two implementation paths for activating AWS Marketplace Private Pricing Offer (MPPO) entitlements in AWS License Manager, so organizations can subscribe once from a central account and distribute third-party model access on Amazon Bedrock across many accounts. It matters to platform teams managing multi-account Bedrock deployments, since negotiated pricing does not apply until grants are activated.
An AWS Machine Learning blog post presents two implementation paths for activating AWS Marketplace Private Pricing Offer (MPPO) entitlements in AWS License Manager, so organizations can subscribe once from a central account and distribute third-party model access on Amazon Bedrock across many accounts. It matters to platform teams managing multi-account Bedrock deployments, since negotiated pricing does not apply until grants are activated.
AWS published a setup guide combining OpenAI Codex, LiteLLM, Amazon ECS, and Amazon Bedrock to give enterprises centralized controls over AI coding agents. The pattern addresses managed adoption needs: model-access control, budget and rate-limit enforcement, consumption attribution, and observability. Codex agents run their task loop on the developer workstation while the LiteLLM layer centralizes governance.
AWS published a setup guide combining OpenAI Codex, LiteLLM, Amazon ECS, and Amazon Bedrock to give enterprises centralized controls over AI coding agents. The pattern addresses managed adoption needs: model-access control, budget and rate-limit enforcement, consumption attribution, and observability. Codex agents run their task loop on the developer workstation while the LiteLLM layer centralizes governance.