Distributed Agent Fleet Heartbeat & Liveness Watchdog
by alphaparkinc
README.md
# genpark-distributed-agent-heartbeat-liveness-watchdog-skill
[](https://genpark.ai)
[](LICENSE)
[-brightgreen.svg)](requirements.txt)
[](mcp_server.py)
Distributed Agent Fleet Heartbeat & Liveness Watchdog. Monitors heartbeat signals across distributed autonomous agent nodes, dynamically computes jitter-aware failover deadlines ($T_{\text{timeout}} = \mu + 3\sigma$), isolates zombie/stalled workers, and coordinates state checkpoint hydration and failover rerouting.
---
## 🌟 Key Features
- **100% Zero External Dependencies**: Runs entirely on the Python 3.9+ standard library.
- **Model Context Protocol (MCP) Standard**: Native support for JSON-RPC 2.0 `initialize`, `tools/list`, and `tools/call`.
- **Industrial-Grade Determinism**: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
- **Dual Deployment Ecosystem**: Verified across `alphaparkinc` and `Alpha-Park` organizations with multi-account validation.
---
## 🚀 Quick Start
### 1. Direct Python SDK Usage
```python
"""Example usage for DistributedAgentHeartbeatLivenessWatchdog."""
import sys
import json
import time
from client import DistributedAgentHeartbeatLivenessWatchdog
sys.stdout.reconfigure(encoding='utf-8')
def main():
print("=== Distributed Agent Fleet Liveness & Failover Watchdog Demo ===")
watchdog = DistributedAgentHeartbeatLivenessWatchdog(baseline_timeout_seconds=5.0)
# 1. Register fleet workers with regular heartbeat pulses
print("\n--- 1. Ingesting Agent Heartbeat Pulses ---")
watchdog.record_heartbeat("workbuddy_worker_01", "HEALTHY", cpu_load_pct=22.5, active_task_id="TASK-EXPORT-PPT")
watchdog.record_heartbeat("workbuddy_worker_02", "HEALTHY", cpu_load_pct=34.1, active_task_id="TASK-AUDIT-MERKLE")
print(f"Registered {len(watchdog.workers)} active fleet workers.")
# 2. Audit fleet health (all operational)
print("\n--- 2. Auditing Fleet Health Status ---")
health = watchdog.audit_fleet_health()
print(f"Fleet Status: {health['fleet_status']} (Healthy: {health['healthy_workers_count']}/{health['total_workers']})")
# 3. Simulate sudden unresponsiveness on worker 01
print("\n--- 3. Simulating Node Timeout / Zombie Worker ---")
watchdog.workers["workbuddy_worker_01"]["last_heartbeat"] = time.time() - 15.0
degraded_health = watchdog.audit_fleet_health()
print(f"Fleet Status: {degraded_health['fleet_status']} | Stalled Workers: {degraded_health['zombie_workers_count']}")
for z in degraded_health["zombie_workers"]:
print(f" [Zombie Alert]: Node @{z['agent_id']} stalled for {z['elapsed_since_heartbeat_seconds']}s (Task: {z['stalled_task_id']})")
# 4. Trigger automated failover task migration
print("\n--- 4. Executing Failover Lease Migration ---")
failover = watchdog.trigger_worker_failover("workbuddy_worker_01", backup_agent_id="workbuddy_worker_02")
print(f"Failover Token: {failover['failover_token']}")
print(f"Migrated Task '{failover['migrated_task_id']}' to Worker @{failover['assigned_backup_agent_id']}")
if __name__ == "__main__":
main()
```
### 2. Run as Model Context Protocol (MCP) Server
Start standard JSON-RPC 2.0 server over `stdio`:
```bash
python mcp_server.py
```
Execute embedded test harness:
```bash
python mcp_server.py --test
```
---
## 🛠️ MCP Tool Specification
Inspect [`skill.json`](skill.json) for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.
---
## 📜 License
Licensed under the [MIT License](LICENSE). Copyright © 2026 GenPark AI.
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