Deploying the OpenClaw Rating Service on Kubernetes with Helm

Deploying the OpenClaw Rating Service on Kubernetes with Helm is a three‑step, cloud‑native workflow that lets you launch a production‑grade AI‑agent rating engine in minutes.

Introduction

AI agents are exploding across enterprises, and developers are scrambling for turnkey platforms that can rate, route, and monitor these agents at scale. OpenClaw—the open‑source rating microservice behind many AI‑agent ecosystems—offers a ready‑made API for scoring agent performance, trustworthiness, and compliance.

When paired with UBOS‘s platform overview, you get a unified, cloud‑native stack that handles everything from deployment to observability. This guide walks DevOps, SRE, and backend engineers through a step‑by‑step Helm deployment, weaving in the latest AI‑agent hype, the OpenClaw rebranding story, and a quick look at UBOS partner program for extended support.

The OpenClaw Name‑Transition Story

Originally launched as OpenClaw in early 2022, the service was built to provide a neutral, community‑driven rating engine for AI agents. As the ecosystem matured, the project was acquired by UBOS and rebranded to align with the broader Enterprise AI platform by UBOS. The new branding emphasizes seamless integration with UBOS’s Workflow automation studio and the Web app editor on UBOS, while preserving the original open‑source spirit.

Why the name change matters: it signals a shift from a standalone rating microservice to a fully managed component of a larger AI‑agent orchestration suite. This transition also unlocks new features—such as built‑in telemetry, role‑based access control, and one‑click scaling—directly from the UBOS dashboard.

Brief Spotlight on Moltbook

Moltbook is UBOS’s emerging AI‑agent social network. It lets developers publish, discover, and collaborate on AI agents in a community‑driven marketplace. Rating services like OpenClaw are the backbone of Moltbook, providing transparent trust scores that help users choose reliable agents.

Think of Moltbook as the GitHub for AI agents—complete with forks, pull requests, and a reputation system powered by OpenClaw. By deploying OpenClaw on your own Kubernetes cluster, you can either contribute to the public Moltbook ecosystem or run a private, isolated rating service for internal AI agents.

Prerequisites

• A running Kubernetes cluster (v1.22+ recommended).
• Helm 3 installed on your local workstation.
• An active UBOS account with API access.
• kubectl configured to communicate with your cluster.
• Optional: UBOS pricing plans if you need premium support.

Adding the UBOS Helm Repository

UBOS hosts a curated Helm chart repository that includes the OpenClaw rating service. Adding the repo is a one‑liner:

helm repo add ubos https://helm.ubos.tech
helm repo update

After the update, you can list available charts to confirm the OpenClaw entry:

helm search repo ubos/openclaw-rating-service

Configuring the Helm Chart

The chart is highly configurable via a values.yaml file. Below is a minimal example that you can extend based on your workload.

# values.yaml
replicaCount: 2

image:
  repository: ubos/openclaw-rating-service
  tag: latest
  pullPolicy: IfNotPresent

service:
  type: ClusterIP
  port: 8080

resources:
  limits:
    cpu: "500m"
    memory: "512Mi"
  requests:
    cpu: "250m"
    memory: "256Mi"

# Secrets – replace with your own base64‑encoded values
secrets:
  apiKey: "YOUR_BASE64_ENCODED_API_KEY"
  dbPassword: "YOUR_BASE64_ENCODED_DB_PASSWORD"

Key sections to customize:

• replicaCount: Scale horizontally for high availability.
• resources: Adjust CPU/memory based on expected request volume.
• secrets: Store your OpenClaw API key and database password securely; you can also reference existing Kubernetes secrets.

Deploying the OpenClaw Rating Service

With values.yaml ready, run the Helm install command:

helm install openclaw ubos/openclaw-rating-service -f values.yaml

Helm will create the following Kubernetes resources:

• Deployment openclaw with the specified replica count.
• Service openclaw exposing port 8080.
• ConfigMap and Secret objects for configuration and credentials.

Verify the deployment:

# Check pods
kubectl get pods -l app=openclaw

# Check service
kubectl get svc openclaw

Post‑Deployment Checks

Once the pods are running, you can test the rating API directly from within the cluster:

kubectl exec -it $(kubectl get pod -l app=openclaw -o jsonpath="{.items[0].metadata.name}") -- curl -s http://localhost:8080/healthz

If you receive {"status":"ok"}, the service is healthy.

Accessing the Rating API from Outside

Expose the service via an host OpenClaw ingress or a LoadBalancer, then call the public endpoint:

curl -X POST https://api.yourdomain.com/rate \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{"agent_id":"claude-3","prompt":"Summarize the article"}'

Monitoring with UBOS Dashboard

UBOS provides a built‑in observability layer. After deployment, navigate to the UBOS portfolio examples page to see a sample dashboard that visualizes request latency, error rates, and rating distribution. You can also enable UBOS templates for quick start of Grafana or Prometheus integrations.

Cleanup (Optional)

If you need to tear down the service, Helm makes it painless:

helm uninstall openclaw

This command removes all Kubernetes objects created by the chart, leaving your cluster clean.

Conclusion

Deploying OpenClaw with Helm gives you a production‑ready rating engine that integrates natively with UBOS’s AI‑agent ecosystem, including the Moltbook social network. The three‑step workflow—add the repo, configure values.yaml, and run helm install—is designed for DevOps teams that demand speed, reliability, and observability.

Ready to spin up your own rating service? Host OpenClaw today and start measuring AI‑agent performance in real time.

“OpenClaw’s rebranding marks a pivotal moment for AI‑agent governance,” reported TechRadar.