cloudflare·Aug 3, 2026·2 min readCurated summary

Cloudflare Workers and Containers now support inbound TCP connections and gRPC

Cloudflare is expanding Workers to support low-latency, TCP-based applications such as real-time voice AI and gRPC services. New inbound socket handling lets Workers route connections through Durable Objects and Containers, while Cloudflare also enables full-duplex gRPC servers running in containers. Together, these capabilities allow developers to deploy language-agnostic TCP and gRPC services closer to users across Cloudflare’s global network. ## Inbound TCP with `connect(socket)` - Workers can now accept inbound TCP sockets through a new `connect()` handler. - The socket exposes readable and writable streams, allowing Workers to send, receive, and proxy raw bytes. - Connections can be routed: - Between Workers - From Workers to Durable Objects - From Durable Objects to Cloudflare Containers - Developers can pipe data in both directions to preserve full-duplex communication. - Containers can run arbitrary TCP servers written in any language, such as Python services listening on port `8080`. - Cloudflare Spectrum provides the TCP ingress layer and routes incoming connections to the selected Worker. ## Full-Duplex gRPC in Containers - Developers can deploy gRPC servers written in languages such as Go inside Cloudflare Containers. - Bidirectional streaming allows clients and servers to exchange messages over one persistent connection. - This is particularly useful for: - Real-time voice AI - Low-latency inference - Mobile and distributed applications - Streaming RPC workflows - A sample Go server sends an initial connection message, echoes incoming messages, and sends a closing message when the client disconnects. - Cloudflare’s network of more than 330 locations can bring gRPC workloads closer to users, reducing latency. ## gRPC APIs from Workers - Workers can serve unary and server-streaming gRPC APIs. - Workers can also call external gRPC servers. - Developers write the application using gRPC-Web, while Cloudflare automatically converts incoming and outgoing requests to standard gRPC. - This provides a simpler integration path for applications that need gRPC without managing raw protocol translation themselves. ## Availability - The features are being introduced through a private beta. - Interested developers must sign up to gain access. Cloudflare recommends these capabilities for applications requiring persistent, low-latency, bidirectional communication. The combination of Spectrum, Workers, Durable Objects, and Containers provides a flexible path for running raw TCP protocols and gRPC services close to end users.

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Voice AiCloudflare WorkersGrpcDurable Objects+3

aws·Dec 2, 2025Original article

Amazon Bedrock AgentCore adds quality evaluations and policy controls for deploying trusted AI agents (opens in new tab)

AWS has introduced several new capabilities to Amazon Bedrock AgentCore designed to remove the trust and quality barriers that often prevent AI agents from moving into production environments. These updates, which include granular policy controls and sophisticated evaluation tools, allow developers to implement strict operational boundaries and monitor real-world performance at scale. By balancing agent autonomy with centralized verification, AgentCore provides a secure framework for deploying highly capable agents across enterprise workflows. **Governance through Policy in AgentCore** * This feature establishes clear boundaries for agent actions by intercepting tool calls via the AgentCore Gateway before they are executed. * By operating outside of the agent’s internal reasoning loop, the policy layer acts as an independent verification system that treats the agent as an autonomous actor requiring permission. * Developers can define fine-grained permissions to ensure agents do not access sensitive data inappropriately or take unauthorized actions within external systems. **Quality Monitoring with AgentCore Evaluations** * The new evaluation framework allows teams to monitor the quality of AI agents based on actual behavior rather than theoretical simulations. * Built-in evaluators provide standardized metrics for critical dimensions such as helpfulness and correctness. * Organizations can also implement custom evaluators to ensure agents meet specific business-logic requirements and industry-specific compliance standards. **Enhanced Memory and Communication Features** * New episodic functionality in AgentCore Memory introduces a long-term strategy that allows agents to learn from past experiences and apply successful solutions to similar future tasks. * Bidirectional streaming in the AgentCore Runtime supports the deployment of advanced voice agents capable of handling natural, simultaneous conversation flows. * These enhancements focus on improving consistency and user experience, enabling agents to handle complex, multi-turn interactions with higher reliability. **Real-World Application and Performance** * The AgentCore SDK has seen rapid adoption with over 2 million downloads, supporting diverse use cases from content generation at the PGA TOUR to financial data analysis at Workday. * Case studies highlight significant operational gains, such as a 1,000 percent increase in content writing speed and a 50 percent reduction in problem resolution time through improved observability. * The platform emphasizes 100 percent traceability of agent decisions, which is critical for organizations transitioning from reactive to proactive AI-driven operations. To successfully scale AI agents, organizations should transition from simple prompt engineering to a robust agentic architecture. Leveraging these new policy and evaluation tools will allow development teams to maintain the necessary control and visibility required for customer-facing and mission-critical deployments.

Voice AiAIAI AgentsGenerative AI+5