a member
one-process swarm
An anonymous worker inside one process.
a2a swarm
A named, deployed agent with its own identity and card.
swarms you can audit
Agent swarms that stay accountable.
A swarm multiplies whatever you already have—including the trust problem. a2a cloud can make each member a distinct deployed agent with its own database boundary and scale-to-zero. Platform-managed handoffs can carry scoped grants, and member runs produce separately attributable signed evidence.
named members · grant per role · inspect the signed timeline
0
shared credential across members
0
signed execution entry points per member
idle member cost
the problem
A swarm of anonymous workers is a swarm you can't govern.
The appeal of a swarm is parallelism — many agents chewing on a problem at once. The failure mode is anonymity: when members are threads inside one process, sharing one credential and one database, you lose the ability to say which one acted, under what authority, or how to stop it. Debugging becomes archaeology, security becomes all-or-nothing, and cost becomes a single opaque number. Scale made the system faster and the accountability worse.
Members share one credential — compromise one, compromise the swarm.
Actions attribute to 'the swarm', not to a specific agent and run.
One shared database means one member's fault can corrupt the rest.
Cost is a single bill with no per-member or per-run breakdown.
the a2a way
Make every member a first-class, signed, scoped agent.
a2a gives each swarm member separate deployment and database boundaries, optional scoped delegation, signed evidence on those runs, and independent scale-to-zero.
Every swarm member is namedScoped grants per memberThe swarm has an inspectable timelineScale-to-zero per member
Every swarm member is named
Each agent in the swarm is a deployed actor with its own card and identity — not an anonymous worker. When something happens, the receipt names the exact member, not 'the swarm'.
Scoped grants per member
A member holds only the audience, tools, files, and TTL its role needs. A hundred agents don't mean a hundred copies of your keys — they mean a hundred narrow, revocable grants.
The swarm has an inspectable timeline
Each member execution through Agent API, public `/invoke`, or standard MCP `tools/call` has separately attributable signed evidence. Formal A2A steps remain protocol history; a separately configured session can preserve ordered events.
Scale-to-zero per member
Idle members cost nothing. Each agent scales to zero independently, so a large swarm that mostly waits doesn't bill like a large swarm that's always on.
side-by-side
Anonymous swarm vs. governed swarm.
access
one-process swarm
Every member shares one set of credentials.
a2a swarm
Each member holds a scoped, revocable grant for its role.
an incident
one-process swarm
'Somewhere in the swarm' — you grep and guess.
a2a swarm
The signed receipt names the member and records input evidence and grant IDs.
idle cost
one-process swarm
The whole swarm stays warm and bills continuously.
a2a swarm
Each member scales to zero; you pay only for active work.
dimension
one-process swarm
a2a swarm
a member
An anonymous worker inside one process.
A named, deployed agent with its own identity and card.
access
Every member shares one set of credentials.
Each member holds a scoped, revocable grant for its role.
an incident
'Somewhere in the swarm' — you grep and guess.
The signed receipt names the member and records input evidence and grant IDs.
idle cost
The whole swarm stays warm and bills continuously.
Each member scales to zero; you pay only for active work.
questions
Frequently asked.
What is an AI agent swarm?
An agent swarm is a group of agents working in parallel on a shared goal. The value is throughput and redundancy; the risk is that anonymous workers are nearly impossible to audit. a2a cloud makes each member a distinct deployed agent, while executions through Agent API, public `/invoke`, or standard MCP `tools/call` produce separately attributable signed evidence. Formal A2A steps remain protocol history.
How do you audit which member of a swarm did what?
Each member is a distinct deployed identity. Its authenticated Agent API calls and public `/invoke` or standard MCP `tools/call` executions receive Ed25519-signed receipts with agent, caller, grant, input, result, and timing evidence. Formal A2A messages between members remain protocol state, and deterministic re-execution still requires replay doubles and seeded randomness.
Won't running a large swarm be expensive?
Each member scales to zero independently, so idle agents cost nothing. A swarm that spends most of its time waiting on a few active branches bills for the active work, not for keeping every member warm. Per-member isolated Postgres and per-run cost attribution also let you see exactly where the swarm's spend actually goes.
keep reading
Related guides.
All guides live in the guides index.
don't trust the agent
Run the swarm. Keep the receipts.
a2a cloud deploys any agent — LangGraph, OpenAI Agents SDK, CrewAI, AutoGen, or custom — so each swarm member gets managed Postgres, MCP and API surfaces, and scoped grants. Governed Agent API, public `/invoke`, and standard MCP `tools/call` executions receive Ed25519-signed receipts attributable to that member.