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3 posts about A2A. Every summary links to the original.
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A2A lets agents discover each other and hand off tasks over JSON-RPC 2.0. This guide walks through exposing an Agent Card, sending typed messages, connecting a remote service, and routing failures to a human review checkpoint.
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Agent sprawl arises when many AI agents on Red Hat OpenShift become redundant, insecure, and untraceable, using static API keys over HTTP and lacking visibility into reasoning failures. Rossoctl, a Kubernetes-native controller, automates discovery by declaring AgentRuntime resources that fetch metadata to create AgentCard custom resources, and uses a two-phase Helm deployment to resolve the URL dependency between routes and AgentCards. It adopts the A2A protocol, which standardizes agent interaction through a machine-readable AgentCard at /.well-known/agent-card.json and a JSON-RPC interface for consistent payloads. Security follows a six-layer zero-trust model: SPIRE issues short-lived certificates, Istio enforces mTLS, AgentCards are signed with JWS, and AuthBridge provides scoped OAuth2 tokens. Observability uses opt-in MLflow tracing that captures orchestration flow, tool calls, and model latency, enabling diagnosis of semantic failures such as hallucinations or data leaks that standard metrics miss.
The post presents a contract-compliance pipeline in which a Python agent uses Gemini to extract contract terms and a Go service applies deterministic corporate-policy checks. It connects the services with the Agent2Agent (A2A) protocol and uses Google's Agent Development Kit (ADK), including RemoteA2aAgent, to expose the remote validator as a local sub-agent in a SequentialAgent. A2A supplies discovery through Agent Cards at /.well-known/agent.json, JSON-RPC 2.0 messaging through message/send, typed Message Parts, and task states such as submitted, working, completed, and failed. Pipeline state is shared through ADK's ToolContext.state, with failures transitioning to MANUAL_REVIEW for human legal review when the Go service is unavailable. The accompanying open-source application demonstrates live handoffs, policy verdicts, and simulated network faults, while the conclusion emphasizes language independence, decoupling, resilience, and deterministic auditing.
A2A, launched one year before this June 18, 2026 update, is presented as a common language for conversational, dynamic agents that need to collaborate and hand off tasks securely rather than behave like stateless tools. The protocol uses black-box handoffs to keep sensitive data and proprietary processes encapsulated, prevent context pollution, support clarifying exchanges, and distribute specialized workloads across teams or services. Foldrun demonstrates this model by exposing protein-structure prediction as a standalone agentic interface that manages long-running tasks, adjusts parameters based on prediction confidence, and selects among AlphaFold 2, OpenFold 3, and Boltz-2 depending on the molecule. In an A2A-compliant environment, users can register Foldrun and delegate work in natural language without custom glue code, while a primary agent handles other research tasks. The post also cites applications in commerce, streaming, IT operations, and regulated telecom, while Python and Go SDKs are 1.0 GA.
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