molecule-core/docs/api-protocol/registry-and-heartbeat.md

Registry & Heartbeat

Every workspace registers with the platform on startup and sends a heartbeat every 30 seconds. This is how the platform knows which workspaces are alive and where to find them.

Registration Flow

When a workspace container starts:

POST /registry/register
Body: { id, url, agent_card }

The platform:

1. Writes the Agent Card to Postgres (workspaces table)
2. Sets Redis key ws:{id} = "online" with TTL 60 seconds
3. Appends a WORKSPACE_ONLINE event to structure_events
4. Broadcasts event via WebSocket — canvas node turns green

Heartbeat Flow

Every 30 seconds:

# workspace-template/heartbeat.py

await platform.post("/registry/heartbeat", json={
    "workspace_id": WORKSPACE_ID,

    # used by platform to make status decisions
    "error_rate": error_tracker.error_rate,      # triggers degraded
    "sample_error": error_tracker.sample_error,  # shown on canvas

    # informational — shown on canvas node tooltip
    "active_tasks": task_counter.current,         # how many tasks running now
    "uptime_seconds": time.time() - START_TIME,   # how long since container start
    "current_task": current_task_description,      # what the agent is working on
})

Five fields. Memory usage, CPU, queue depth — those are infrastructure metrics for Prometheus/Grafana or CloudWatch. The platform registry is a service discovery layer, not a metrics store.

active_tasks is included because the canvas uses it for a busy indicator on the node, and it sets up backpressure for Phase 2 without a schema change.

current_task is a human-readable description of what the agent is currently working on. The platform stores it in workspaces.current_task and broadcasts a TASK_UPDATED WebSocket event only when the value changes (not on every heartbeat). The canvas shows it as an amber banner on the workspace node and side panel header.

The platform:

1. Overwrites heartbeat columns in Postgres (latest snapshot only — no history)
2. Refreshes Redis TTL to 60 seconds
3. Checks error rate for status transitions (see Health Monitoring below)

// platform/internal/registry/heartbeat.go

func HandleHeartbeat(workspaceID string, stats HeartbeatStats) {
    db.Exec(`
        UPDATE workspaces SET
            last_heartbeat_at = now(),
            last_error_rate   = $2,
            last_sample_error = $3,
            active_tasks      = $4,
            uptime_seconds    = $5,
            current_task      = $6
        WHERE id = $1
    `, workspaceID,
       stats.ErrorRate, stats.SampleError,
       stats.ActiveTasks, stats.UptimeSeconds,
       stats.CurrentTask,
    )
    redis.Refresh(workspaceID, 60*time.Second)
    evaluateStatusTransition(workspaceID, stats)
}

No heartbeat history table. Heartbeats arrive every 30 seconds — storing history would be 2880 rows per workspace per day with no practical use. If you need health trends, Langfuse traces capture that at the task level with far more detail.

Health Monitoring

The workspace self-reports its health via the heartbeat payload. The platform decides status transitions based on error rate thresholds:

Condition	Transition	Event
error_rate >= 0.5 and status is online	online -> degraded	WORKSPACE_DEGRADED
error_rate < 0.1 and status is degraded	degraded -> online	WORKSPACE_ONLINE

What counts as an error: Only things that indicate the workspace itself is broken — 5xx responses, timeouts, connection errors. Client errors (400, 403) are the caller's fault and are not counted.

The workspace tracks errors locally using a rolling 60-second window and includes the stats in every heartbeat. The platform doesn't sit in the A2A message path, so it can't monitor response codes directly — self-reporting via heartbeat is the mechanism.

Liveness Detection (No Polling)

Redis keyspace notifications are enabled (notify-keyspace-events = KEA). When ws:{id} TTL expires (workspace missed 2 heartbeats), Redis fires an expiry event automatically.

Workspace starts
      |
      v
POST /registry/register  ->  Platform writes Agent Card to Postgres
                          ->  Platform sets Redis key: ws:{id} = "online" TTL 60s

Every 30s:
POST /registry/heartbeat ->  Platform refreshes Redis TTL

Workspace crashes / goes dark:
      |
      v
Redis TTL expires (60s)
      |
      v
Redis keyspace event fires
      |
      v
Platform marks workspace offline in Postgres
      |
      v
WebSocket broadcast -> canvas node turns gray

On expiry, the platform:

1. Receives Redis keyspace expiry event
2. Writes WORKSPACE_OFFLINE event to Postgres
3. Updates workspaces.status = 'offline'
4. Broadcasts via WebSocket — canvas node turns gray

Heartbeat Delegation Checking

In addition to alive signals, the heartbeat loop checks for completed delegations every 30 seconds:

Every 30s:
1. POST /registry/heartbeat        → alive signal
2. GET /workspaces/:id/delegations → check results
3. If new completions found:
   a. Write to /tmp/delegation_results.jsonl (for context injection)
   b. Send A2A self-message to wake the agent (5-min cooldown)
   c. Push notification to user via POST /notify

Self-message trigger: When the heartbeat detects a completed delegation, it sends an A2A message to its own workspace: "Delegation results are ready. Review them and take appropriate action." This wakes the agent so it can report results back up the chain.

Cooldown: At most one self-message per 5 minutes to prevent infinite loops (agent delegates → completes → self-message → agent delegates again → ...).

Context injection: When the agent receives any message (including the self-message), the CLI executor reads /tmp/delegation_results.jsonl and injects results into the prompt as [Delegation results received while you were idle].

Delegation status lifecycle:

pending → dispatched → received → in_progress → completed | failed

Each transition broadcasts a DELEGATION_STATUS WebSocket event. DELEGATION_COMPLETE and DELEGATION_FAILED are broadcast on terminal states.

Workspace Moves to a New Machine

When a workspace starts on a new machine (e.g. new EC2 instance):

1. Workspace sends POST /registry/register with new URL
2. Platform updates workspaces.url in Postgres
3. Platform busts Redis URL cache key ws:{id}:url
4. All subsequent inter-workspace calls use the new URL automatically

Workspace Forwarding

The forwarded_to column is set when a workspace is retired but a replacement exists. Three scenarios:

1. Workspace replaced by a better version: User deploys a new SEO agent with improved skills and retires the old one. Old workspace gets forwarded_to = new_workspace_id. Any workspace that still has the old URL cached gets a 410 Gone + redirect pointer and updates its reference automatically.

2. Workspace expanded into a team: A single Developer Agent expands into a Developer Team. The original single-agent workspace is retired. forwarded_to = developer_pm_id (the team lead). Anything that was talking to the old Developer Agent now gets redirected to Developer PM.

3. Workspace moved to a different parent: A workspace is reorganized in the hierarchy. Old workspace entry kept for redirect, new one created under the new parent.

In all cases, the forwarding is transparent — callers follow the redirect and update their cached URL.

Querying a Deleted Workspace

When a workspace is queried after being deleted or retired:

1. Platform checks workspaces table — status is removed
2. Platform queries structure_events for the last event on that ID
3. If workspaces.forwarded_to is set, returns 301 with the new workspace URL
4. If no forwarding, returns 410 Gone with the last event payload
5. Canvas removes the node; parent workspace is notified

Related Docs

• Platform API — Full endpoint reference
• Event Log — How events are recorded
• Database Schema — Redis key patterns