Why Agent Monitoring Matters
AI agents are not traditional software. They make decisions, consume varying resources, and can fail in subtle ways that don't trigger typical error handlers. An agent might be "running" but producing poor results, burning through tokens, or stuck in a reasoning loop.
Without proper monitoring, you're flying blind. And with AI agents, flying blind can get expensive fast.
The Three Pillars of Agent Monitoring
1. Health Monitoring (Is it alive?)
The most basic level. Your monitoring system needs to answer: is this agent running, responsive, and able to accept tasks?
- Heartbeat checks: Regular pings to verify the agent process is alive
- Endpoint health: Verify the agent can respond to requests within acceptable latency
- Dependency checks: Confirm external services (LLM APIs, databases, tools) are accessible
- Resource utilization: CPU, memory, disk, and network usage
In ClawHQ, health status is displayed as a simple traffic light on your dashboard — green, yellow, or red for each agent.
2. Performance Monitoring (Is it working well?)
An agent can be "healthy" but performing poorly. Performance monitoring tracks:
- Task completion rate: What percentage of tasks are completed successfully?
- Average task duration: How long do tasks take? Are they getting slower?
- Quality scores: If you have evaluation criteria, track quality over time
- Token efficiency: How many tokens per task? Is the agent being wasteful?
- Error patterns: What types of failures occur most frequently?
3. Cost Monitoring (Is it affordable?)
AI agents consume tokens, API calls, and compute resources. Without cost monitoring, a single misconfigured agent can run up a massive bill overnight.
- Token usage per agent: Track input and output tokens separately
- Cost per task: Know exactly what each task costs
- Budget alerts: Set spending limits and get notified before they're exceeded
- Cost trends: Identify agents or tasks that are becoming more expensive over time
Setting Up Monitoring with ClawHQ
If you're using OpenClaw with ClawHQ, monitoring comes built in. Here's how to configure it effectively:
Step 1: Configure Health Checks
In your agent's openclaw.config.ts:
healthCheck: {
interval: '30s',
timeout: '10s',
retries: 3,
deepCheck: { interval: '5m', validateModel: true },
}
Step 2: Set Up Alerts
Navigate to your ClawHQ dashboard → Alerts → Create Alert Rule. We recommend starting with:
- Agent Down: Alert immediately when an agent goes offline
- High Error Rate: Alert when error rate exceeds 10% in a 15-minute window
- Cost Spike: Alert when hourly cost exceeds 2x the daily average
- Task Queue Backup: Alert when pending tasks exceed a threshold
Step 3: Configure Dashboards
ClawHQ provides pre-built dashboard views, but you should customize them for your use case:
- Fleet Overview: All agents, health status, active tasks
- Cost Center: Spending by agent, by task type, trends over time
- Performance: Completion rates, latency, quality metrics
Advanced Monitoring Strategies
Anomaly Detection
Don't just set static thresholds — look for anomalies. An agent that normally completes tasks in 30 seconds suddenly taking 5 minutes is a signal, even if it hasn't technically "failed."
Log Analysis
AI agents generate rich logs — reasoning traces, tool calls, intermediate results. Structured logging makes it possible to debug issues after the fact. ClawHQ aggregates logs across your fleet and makes them searchable.
Comparative Monitoring
If you run multiple agents on similar tasks, compare their performance. Which agent is more efficient? More accurate? More cost-effective? This data helps you optimize your fleet composition.
Monitoring Anti-Patterns
- Alert fatigue: Too many alerts = ignored alerts. Be selective about what triggers notifications.
- Checking only uptime: An agent that's "up" but producing garbage output is worse than one that's clearly down.
- Ignoring costs until the bill arrives: Set budget alerts proactively.
- Manual monitoring: If you're SSH-ing into servers to check logs, you need a better system.
Monitoring Checklist
Use this checklist to ensure your monitoring is comprehensive:
- ✅ Health checks configured with appropriate intervals
- ✅ Alert rules for downtime, errors, and cost spikes
- ✅ Dashboard showing fleet-wide status at a glance
- ✅ Cost tracking enabled per agent and per task type
- ✅ Structured logging for debugging
- ✅ Regular review of monitoring metrics
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