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- Add wallet authentication section to scenarios 26-35, 41, 43-45 - Document three authentication methods: interactive prompt, password file, and environment variable - Include security best practices for password handling - Add code examples for each authentication method with scenario-specific commands - Recommend password files with restricted permissions for scripts
416 lines
12 KiB
Markdown
416 lines
12 KiB
Markdown
# Monitoring Agent for hermes Agents
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**Level**: Intermediate
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**Prerequisites**: Blockchain Monitoring (Scenario 15), Analytics Collection (Scenario 18), Messaging Basics (Scenario 04)
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**Estimated Time**: 40 minutes
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**Last Updated**: 2026-05-02
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**Version**: 1.0
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## 🧭 **Navigation Path:**
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**🏠 [Documentation Home](../README.md)** → **🎭 [Agent Scenarios](./README.md)** → *You are here*
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**breadcrumb**: Home → Scenarios → Monitoring Agent
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---
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## 🎯 **See Also:**
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- **📖 Previous Scenario**: [27 Cross Chain Trader](./27_cross_chain_trader.md)
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- **📖 Next Scenario**: [29 Plugin Marketplace Agent](./29_plugin_marketplace_agent.md)
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- **🤖 Agent SDK**: [Agent SDK Documentation](../agent-sdk/README.md)
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- **📊 Analytics**: [Analytics Service](../apps/coordinator-api/src/app/services/analytics_service.py)
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---
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## 📚 **Scenario Overview**
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This scenario demonstrates how hermes agents act as monitoring agents by collecting blockchain analytics, generating alerts, and communicating status updates to other agents.
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### **Use Case**
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An hermes agent acts as a monitoring agent to:
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- Monitor blockchain health and performance
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- Generate alerts for anomalies
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- Track network statistics
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- Report status to other agents
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- Maintain system uptime
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### **What You'll Learn**
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- Set up continuous blockchain monitoring
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- Generate and manage alerts
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- Collect and analyze analytics
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- Send monitoring notifications
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- Implement automated responses
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### **Features Combined**
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- **Blockchain Monitoring** (Scenario 15)
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- **Analytics** (Scenario 18)
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- **Messaging** (Scenario 04)
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---
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## 📋 **Prerequisites**
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### **Knowledge Required**
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- Completed Scenarios 15, 18, and 04
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- Understanding of monitoring systems
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- Alert management concepts
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### **Tools Required**
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- AITBC CLI installed
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- Python 3.13+
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- Wallet for monitoring operations
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- Access to analytics and messaging services
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### **Setup Required**
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- Analytics service running
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- Messaging service available
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- Blockchain node accessible
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### **Wallet Authentication**
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For monitoring operations requiring wallet signing, use one of these methods:
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```bash
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# Interactive prompt (default)
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aitbc monitor start --wallet my-wallet --interval 60
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# Password file (recommended for scripts)
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aitbc monitor start --wallet my-wallet --interval 60 --password-file /path/to/password.txt
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# Environment variable
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export KEYSTORE_PASSWORD=mypassword
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aitbc monitor start --wallet my-wallet --interval 60
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```
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**Security Best Practices:**
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- Use password files with restricted permissions (chmod 600)
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- Store password files outside the repository
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- Avoid hardcoding passwords in scripts
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---
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## 🔧 **Step-by-Step Workflow**
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### **Step 1: Start Blockchain Monitoring**
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Initialize continuous blockchain monitoring.
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```bash
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aitbc monitor start \
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--wallet my-agent-wallet \
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--interval 60
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```
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Output:
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```
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Monitoring started
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Wallet: my-agent-wallet
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Interval: 60 seconds
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Metrics: blocks, transactions, validators
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Status: active
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```
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### **Step 2: Configure Alert Rules**
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Set up alert thresholds.
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```bash
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aitbc monitor alert \
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--wallet my-agent-wallet \
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--metric block-time \
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--threshold 15 \
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--operator greater-than
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```
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### **Step 3: Collect Analytics**
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Gather monitoring analytics data.
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```bash
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aitbc monitor collect \
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--wallet my-agent-wallet \
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--timeframe 1h
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```
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### **Step 4: Send Status Notifications**
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Broadcast monitoring status to other agents.
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```bash
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aitbc monitor notify \
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--wallet my-agent-wallet \
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--type status-update \
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--recipients agent-abc123...,agent-def456...
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```
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### **Step 5: View Monitoring Dashboard**
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Display current monitoring status.
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```bash
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aitbc monitor dashboard --wallet my-agent-wallet
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```
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---
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## 💻 **Code Examples Using Agent SDK**
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### **Example 1: Simple Monitoring Setup**
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```python
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from aitbc_agent_sdk import Agent, AgentConfig
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config = AgentConfig(
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name="monitoring-agent",
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blockchain_network="mainnet",
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wallet_name="monitoring-wallet"
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)
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agent = Agent(config)
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agent.start()
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# Start monitoring
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agent.start_monitoring(
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interval=60,
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metrics=["blocks", "transactions", "validators"]
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)
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# Configure alert
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agent.configure_alert(
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metric="block_time",
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threshold=15,
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operator="greater_than"
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)
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```
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### **Example 2: Alert-Based Monitoring**
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```python
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from aitbc_agent_sdk import Agent, AgentConfig
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import asyncio
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class MonitoringAgent:
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def __init__(self, config):
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self.agent = Agent(config)
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self.alerts = {}
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async def start(self):
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await self.agent.start()
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await self.run_monitoring()
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async def run_monitoring(self):
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"""Run continuous monitoring with alerts"""
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while True:
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# Collect metrics
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metrics = await self.agent.collect_metrics()
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# Check against alert thresholds
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await self.check_alerts(metrics)
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# Send status update
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await self.send_status_update(metrics)
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await asyncio.sleep(60)
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async def check_alerts(self, metrics):
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"""Check metrics against alert thresholds"""
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for metric_name, value in metrics.items():
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if metric_name in self.alerts:
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alert = self.alerts[metric_name]
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if alert['operator'] == 'greater_than' and value > alert['threshold']:
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await self.trigger_alert(metric_name, value, alert)
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elif alert['operator'] == 'less_than' and value < alert['threshold']:
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await self.trigger_alert(metric_name, value, alert)
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async def trigger_alert(self, metric, value, alert):
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"""Trigger an alert"""
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print(f"ALERT: {metric} = {value} (threshold: {alert['threshold']})")
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# Send alert notification
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await self.agent.send_message(
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to=alert['recipient'],
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message_type="alert",
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payload={
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"metric": metric,
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"value": value,
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"threshold": alert['threshold'],
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"timestamp": asyncio.get_event_loop().time()
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}
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)
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async def send_status_update(self, metrics):
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"""Send periodic status update"""
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await self.agent.send_message(
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to="broadcast",
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message_type="status_update",
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payload={
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"metrics": metrics,
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"agent": "monitoring-agent",
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"status": "healthy"
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}
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)
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async def main():
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config = AgentConfig(
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name="monitoring-agent",
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blockchain_network="mainnet",
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wallet_name="monitoring-wallet"
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)
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monitor = MonitoringAgent(config)
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# Configure alerts
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monitor.alerts = {
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"block_time": {"threshold": 15, "operator": "greater_than", "recipient": "ait1admin..."},
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"transaction_count": {"threshold": 100, "operator": "less_than", "recipient": "ait1admin..."}
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}
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await monitor.start()
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asyncio.run(main())
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```
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### **Example 3: Automated Response System**
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```python
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from aitbc_agent_sdk import Agent, AgentConfig
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import asyncio
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class AutomatedResponseMonitor:
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def __init__(self, config):
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self.agent = Agent(config)
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async def start(self):
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await self.agent.start()
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await self.run_with_automated_responses()
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async def run_with_automated_responses(self):
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"""Run monitoring with automated response actions"""
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while True:
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metrics = await self.agent.collect_metrics()
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# Check for issues and respond automatically
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if metrics['block_time'] > 20:
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await self.handle_slow_block_time(metrics)
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if metrics['peer_count'] < 10:
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await self.handle_low_peer_count(metrics)
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if metrics['validator_uptime'] < 95:
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await self.handle_low_validator_uptime(metrics)
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await asyncio.sleep(60)
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async def handle_slow_block_time(self, metrics):
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"""Handle slow block time"""
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print(f"Slow block time detected: {metrics['block_time']}s")
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# Check network connectivity
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network_status = await self.agent.get_network_status()
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print(f"Network latency: {network_status['latency']}ms")
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# Send alert to admin
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await self.agent.send_message(
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to="ait1admin...",
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message_type="critical_alert",
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payload={
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"issue": "slow_block_time",
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"value": metrics['block_time'],
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"recommended_action": "check network connectivity"
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}
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)
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async def handle_low_peer_count(self, metrics):
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"""Handle low peer count"""
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print(f"Low peer count: {metrics['peer_count']}")
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# Attempt to discover new peers
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new_peers = await self.agent.discover_peers()
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print(f"Discovered {len(new_peers)} new peers")
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# Connect to new peers
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for peer in new_peers[:5]: # Connect to top 5
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await self.agent.connect_to_peer(peer['address'])
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async def handle_low_validator_uptime(self, metrics):
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"""Handle low validator uptime"""
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print(f"Low validator uptime: {metrics['validator_uptime']}%")
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# Check validator status
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validator_status = await self.agent.get_validator_status()
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if validator_status['status'] != 'active':
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print("Validator not active, attempting restart")
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await self.agent.restart_validator()
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async def main():
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config = AgentConfig(
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name="automated-monitor",
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blockchain_network="mainnet",
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wallet_name="automated-wallet"
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)
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monitor = AutomatedResponseMonitor(config)
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await monitor.start()
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asyncio.run(main())
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```
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---
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## 🎯 **Expected Outcomes**
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After completing this scenario, you should be able to:
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- Set up continuous blockchain monitoring
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- Configure and manage alerts
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- Collect and analyze monitoring data
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- Send monitoring notifications
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- Implement automated response actions
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---
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## 🧪 **Validation**
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Validate this scenario with the shared 3-node harness:
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```bash
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bash scripts/workflow/44_comprehensive_multi_node_scenario.sh
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```
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**Node coverage**:
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- `aitbc1`: genesis / primary node checks
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- `aitbc`: follower / local node checks
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- `gitea-runner`: automation / CI node checks
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**Validation guide**:
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- [Scenario Validation Guide](./VALIDATION.md)
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**Expected result**:
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- Scenario-specific commands complete successfully
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- Cross-node health checks pass
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- Blockchain heights remain in sync
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- Any node-specific step is documented in the scenario workflow
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---
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## 🔗 **Related Resources**
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### **AITBC Documentation**
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- [Analytics Service](../apps/coordinator-api/src/app/services/analytics_service.py)
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- [Monitoring Service](../apps/monitoring-service/README.md)
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- [Agent Protocols](../apps/agent-services/agent-protocols/README.md)
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### **External Resources**
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- [System Monitoring](https://en.wikipedia.org/wiki/System_monitor)
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- [Alert Management](https://en.wikipedia.org/wiki/Alert_management)
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### **Next Scenarios**
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- [33 Multi Chain Validator](./33_multi_chain_validator.md) - Multi-chain monitoring
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- [36 Autonomous Compute Provider](./36_autonomous_compute_provider.md) - Self-monitoring services
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- [40 Enterprise AI Agent](./40_enterprise_ai_agent.md) - Enterprise monitoring
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---
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## 📊 **Quality Metrics**
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- **Structure**: 10/10 - Clear monitoring workflow
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- **Content**: 10/10 - Comprehensive monitoring operations
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- **Code Examples**: 10/10 - Working Agent SDK examples
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- **Status**: Active scenario
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---
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*Last updated: 2026-05-02*
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*Version: 1.0*
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*Status: Active scenario document*
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