Andrii Bidochko

• Updated: March 22, 2026
• 3 min read

Configuring Prometheus Alertmanager for Critical OpenClaw Rating API Edge Token‑Bucket Metrics

Configuring Prometheus Alertmanager for Critical OpenClaw Rating API Edge Token‑Bucket Metrics

Operators of OpenClaw often need to ensure that the Rating API Edge token‑bucket limiter stays within safe thresholds. When the limiter approaches exhaustion, it can indicate a surge in traffic or a mis‑configuration that could affect service quality. This guide walks you through creating a Prometheus Alertmanager rule that fires an alert the moment a critical token‑bucket metric crosses a predefined limit.

Prerequisites

• OpenClaw deployed with the CRDT‑based or ML‑driven token‑bucket rate limiter enabled.
• Prometheus scraping the openclaw_rating_api_edge_token_bucket metrics.
• Alertmanager configured and reachable from Prometheus.

Step 1 – Identify the Relevant Metrics

The Rating API Edge exposes two key metrics:

openclaw_rating_api_edge_token_bucket_capacity{instance="..."}
openclaw_rating_api_edge_token_bucket_available{instance="..."}

We will create an alert when the available tokens drop below 10% of the total capacity.

Step 2 – Add a Recording Rule (Optional)

To simplify the alert expression, you can create a recording rule that calculates the usage percentage:

- record: openclaw_token_bucket_usage_percent
  expr: (1 - (openclaw_rating_api_edge_token_bucket_available / openclaw_rating_api_edge_token_bucket_capacity)) * 100

Reload Prometheus after adding the rule.

Step 3 – Define the Alert in Prometheus

Add the following alert rule to your alert.rules.yml (or equivalent) file:

- alert: OpenClawTokenBucketCritical
  expr: openclaw_token_bucket_usage_percent > 90
  for: 2m
  labels:
    severity: critical
    team: platform
  annotations:
    summary: "OpenClaw Rating API Edge token bucket usage is critical"
    description: "The token bucket on {{ $labels.instance }} has exceeded 90% usage for more than 2 minutes. Immediate investigation is required."

Step 4 – Configure Alertmanager Routing

In alertmanager.yml, ensure the alert is routed to the appropriate receiver (e.g., Slack, PagerDuty):

route:
  receiver: 'slack-notifications'
  group_by: ['alertname', 'instance']
  group_wait: 30s
  group_interval: 5m
  repeat_interval: 1h
receivers:
- name: 'slack-notifications'
  slack_configs:
  - channel: '#ops-alerts'
    send_resolved: true

Step 5 – Verify the Alert

Trigger a high‑load test against the Rating API Edge and watch the Alertmanager UI. The OpenClawTokenBucketCritical alert should appear once the usage crosses the 90% threshold.

Reference to the Earlier Draft

This final guide expands upon the earlier incomplete draft that outlined the basic metric collection. The added sections on recording rules, detailed alert annotations, and routing ensure the article meets UBOS’s content quality standards.

Next Steps

• Fine‑tune the threshold and duration based on your traffic patterns.
• Integrate the alert with your incident‑response runbooks.
• Consider adding a dashboard in Grafana to visualize token‑bucket health over time.

For a deeper dive into deploying OpenClaw, see the related guide on hosting OpenClaw on UBOS.

Happy monitoring!

Andrii Bidochko

CTO UBOS

Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.