Introduction
Amazon Bedrock has long been celebrated for its ability to democratize generative AI by providing a unified, low‑code interface to a suite of foundation models. Yet as the AI ecosystem matures, the need for agents that can orchestrate complex workflows and collaborate across disparate frameworks has become increasingly critical. The agent‑to‑agent (A2A) protocol, now supported in Bedrock’s AgentCore Runtime, offers a standardized, interoperable way for AI agents built on different platforms to discover one another, negotiate tasks, and exchange contextual information. In this post we explore how the A2A protocol removes the friction that has traditionally plagued multi‑agent systems, enabling developers to focus on business logic rather than plumbing.
The core idea is simple: each agent publishes a lightweight “agent card” that describes its capabilities, supported intents, and authentication requirements. Other agents can query a discovery service to locate suitable partners, then initiate a secure, authenticated session to delegate a sub‑task. Because the protocol is agnostic to the underlying model or framework—whether it’s a LangChain‑based chatbot, a custom RAG pipeline, or a proprietary rule engine—teams can mix and match components without rewriting integration code. The result is a flexible, modular architecture that scales from a single‑purpose incident‑response bot to a city‑wide emergency coordination platform.
In the following sections we walk through a concrete example: building a multi‑agent incident‑response system that leverages Bedrock’s A2A support. We cover the full request lifecycle—from agent card discovery to task delegation—highlighting the configuration steps required to deploy A2A servers on AgentCore Runtime, set up discovery and authentication, and orchestrate a real‑world workflow. By the end of this article you will understand how standardized protocols can dramatically simplify the complexity of coordinating multiple AI agents.
Main Content
Understanding the Agent‑to‑Agent Protocol
The A2A protocol is built around a RESTful API that exposes two primary endpoints: one for publishing and retrieving agent cards, and another for initiating a task delegation session. An agent card is a JSON document that lists the intents the agent can handle, the required input schema, and any constraints such as rate limits or cost caps. Importantly, the card also contains a public key or OAuth token that other agents can use to verify the agent’s identity.
Because the protocol is standardized, any agent that implements the spec can discover and interact with any other compliant agent. This eliminates the need for custom adapters or middleware that traditionally have been the source of bugs and maintenance overhead. The protocol also defines a negotiation phase where the delegating agent can request a subset of the delegatee’s capabilities, and the delegatee can confirm or deny the request based on its current load or policy.
Deploying A2A Servers on AgentCore Runtime
Deploying an A2A server is straightforward once you have an AgentCore Runtime instance. The runtime exposes a simple command‑line interface that bundles the agent code, its dependencies, and the A2A server configuration into a Docker image. The image is then pushed to Amazon Elastic Container Registry (ECR) and scheduled on Amazon Elastic Kubernetes Service (EKS) or AWS Fargate.
During deployment you must specify the agent card’s URL, the authentication method, and any environment variables that control the agent’s behavior. The AgentCore Runtime automatically registers the agent card with the discovery service, making it visible to other agents in the same namespace. If you need cross‑namespace discovery—for example, when integrating a third‑party incident‑response tool—you can expose the discovery endpoint through an AWS API Gateway and secure it with a custom Cognito user pool.
Configuring Discovery and Authentication
Discovery is the first step in any A2A interaction. Agents query the discovery service with a set of desired intents and receive a list of matching agent cards. The discovery service supports filtering by tags, cost constraints, and even geographic location, which is essential for latency‑sensitive applications.
Authentication follows the OAuth 2.0 standard. Each agent publishes a JSON Web Token (JWT) that encodes its identity and permissions. When a delegating agent initiates a session, it presents its JWT, and the delegatee validates it against the public key listed in the agent card. This mutual authentication ensures that only authorized agents can delegate tasks, preventing malicious actors from hijacking the workflow.
Building a Multi‑Agent Incident Response System
To illustrate the power of A2A, let’s consider an incident‑response scenario. The system consists of three agents: a triage bot that receives alerts from a monitoring platform, a forensic analysis agent that runs deep‑analysis on compromised hosts, and a remediation agent that applies patches or isolates affected systems.
The triage bot publishes an agent card that advertises its ability to parse alert payloads and determine severity. When a new alert arrives, the triage bot queries the discovery service for agents that can handle “forensic‑analysis” intents. It receives the forensic agent’s card, negotiates a task delegation, and hands off the alert data. The forensic agent then returns a detailed report, which the triage bot forwards to the remediation agent. Each step is a lightweight HTTP request that follows the A2A spec, ensuring that the entire workflow is auditable, secure, and resilient.
Because the agents are decoupled, each team can develop, test, and deploy its component independently. The forensic team can upgrade its analysis engine without touching the triage or remediation agents, and the remediation team can swap out its patch‑management tool for a new vendor without rewriting the orchestration logic.
The Full Request Lifecycle
The A2A request lifecycle begins with discovery. The delegating agent sends a GET request to the discovery endpoint, including query parameters that describe the desired intent and any constraints. The discovery service returns a JSON array of matching agent cards. The delegating agent selects the most appropriate card—perhaps based on cost, latency, or policy—and initiates a POST request to the delegatee’s task endpoint.
The POST payload contains the task data, a correlation ID, and a signed JWT that proves the delegator’s identity. The delegatee validates the JWT, checks its current load, and either accepts or rejects the task. If accepted, the delegatee processes the data, writes the result to a temporary storage bucket, and returns a response that includes a URL to the result and a status code. The delegating agent can poll the status endpoint or subscribe to a webhook to receive updates.
Throughout this process, the A2A protocol enforces rate limits, retries, and timeout policies defined in the agent card. If a task fails, the protocol guarantees that the error is propagated back to the delegator in a structured format, allowing the orchestrator to decide whether to retry, fallback, or abort the workflow.
Conclusion
The introduction of agent‑to‑agent protocol support in Amazon Bedrock’s AgentCore Runtime marks a significant milestone for AI‑driven automation. By providing a standardized, secure, and framework‑agnostic way for agents to discover and collaborate, the A2A protocol removes the operational overhead that has historically limited the adoption of multi‑agent systems. Teams can now assemble heterogeneous agents—each optimized for a specific domain—into a cohesive workflow that scales with business needs.
In the incident‑response example we explored, the A2A protocol enabled a seamless handoff between triage, forensic analysis, and remediation agents, all while preserving auditability and compliance. The same pattern can be applied to customer support, content moderation, supply‑chain optimization, or any scenario where multiple specialized AI services must cooperate.
As AI continues to permeate enterprise operations, the ability to orchestrate agents across frameworks will become a differentiator. Bedrock’s A2A protocol gives organizations the tools to build resilient, modular, and secure AI ecosystems without reinventing the wheel.
Call to Action
If you’re ready to elevate your AI architecture, start experimenting with the A2A protocol today. Deploy a simple agent on AgentCore Runtime, publish its card, and discover how quickly you can integrate a third‑party service. For deeper guidance, consult the Bedrock documentation on A2A and explore the sample multi‑agent incident‑response project available on GitHub. By embracing standardized protocols, you’ll unlock the full potential of AI collaboration and position your organization for the next wave of intelligent automation.