- Updated: March 19, 2026
- 7 min read
Implementing Custom Conflict‑Resolution for OpenClaw Rating API Edge CRDT Token‑Bucket
Implementing a custom conflict‑resolution strategy for the OpenClaw Rating API Edge CRDT token‑bucket involves defining a merge function (or using a last‑write‑wins policy), integrating it into the Edge CRDT configuration, and redeploying the updated service on UBOS.
Introduction
Senior engineers building distributed AI assistants often hit a wall when the default conflict‑resolution logic of a CRDT‑based rate‑limiter does not match their business rules. OpenClaw’s Rating API Edge uses a token‑bucket CRDT to throttle user‑generated requests, but the out‑of‑the‑box merge strategy can lead to over‑allocation or unfair throttling under high concurrency. This guide walks you through a complete, production‑ready implementation of a custom conflict‑resolution function, from theory to code, testing, and deployment on the Self‑host OpenClaw on a dedicated server — in minutes.
Overview of OpenClaw Rating API Edge CRDT Token‑Bucket
The Rating API Edge sits at the front‑line of every OpenClaw‑driven workflow. It enforces request quotas using a token‑bucket CRDT that lives in Redis. Each bucket holds a count of available tokens; every incoming request consumes a token, and a background refill adds tokens at a configurable rate.
- State replication: The bucket state is replicated across all OpenClaw nodes via a Conflict‑Free Replicated Data Type (CRDT), guaranteeing eventual consistency.
- Default merge: OpenClaw’s built‑in merge picks the maximum token count from concurrent replicas, which works for simple rate‑limiting but fails when you need to prioritize certain users or enforce strict caps.
- Edge‑centric: Because the bucket lives at the edge, latency is minimal, but conflict resolution must be deterministic and fast.
Recap of the Theory Guide
Before diving into custom logic, review the foundational steps for self‑hosting OpenClaw on UBOS. The Self‑Hosting OpenClaw on UBOS guide covers installing the UBOS platform, pulling the OpenClaw source, configuring environment variables, and launching the service with a single command. Those steps ensure a stable baseline on which you can safely apply custom CRDT extensions.
Custom Conflict‑Resolution Strategies
Two common patterns address the shortcomings of the default merge:
1. Custom Merge Function
A custom merge function receives the local and remote bucket states and returns a deterministic result. For a token‑bucket, you might want to:
- Prioritize the lowest token count to avoid over‑allocation.
- Apply a user‑weight factor so premium users retain more tokens during spikes.
- Enforce a hard ceiling regardless of replica state.
2. Last‑Write‑Wins (LWW)
LWW uses a timestamp attached to each bucket update. The replica with the newest timestamp wins, simplifying reasoning at the cost of occasional token loss during network partitions. LWW is ideal when you can tolerate brief throttling inconsistencies but need a clear, auditable rule.
Step‑by‑Step Implementation
Prerequisites
- Running OpenClaw instance on UBOS (see the host‑openclaw page for deployment details).
- Access to the
redis-clicontainer and the OpenClaw source directory. - Node.js ≥ 18 or Python ≥ 3.10 (choose your preferred language for the merge plugin).
- Basic familiarity with Tailwind CSS if you plan to expose a UI for admin overrides (optional).
1. Create the Merge Plugin
OpenClaw loads custom CRDT logic from the /opt/openclaw/plugins directory. Below is a Node.js example that implements a weighted‑merge strategy.
// plugins/tokenBucketMerge.js
module.exports = function customMerge(local, remote) {
// Each bucket state: { tokens: number, timestamp: ISOString, userWeight: number }
const now = new Date().toISOString();
// Preserve the smallest token count to avoid over‑allocation
const mergedTokens = Math.min(local.tokens, remote.tokens);
// Apply user weight – premium users (weight > 1) keep extra tokens
const weight = Math.max(local.userWeight, remote.userWeight);
const weightedTokens = Math.min(mergedTokens * weight, MAX_TOKENS);
return {
tokens: Math.floor(weightedTokens),
timestamp: now,
userWeight: weight
};
};
Save this file as tokenBucketMerge.js and ensure it is executable:
chmod +x /opt/openclaw/plugins/tokenBucketMerge.js2. Register the Plugin in the Edge Config
Edit the Edge CRDT configuration (/etc/openclaw/edge.yaml) to point to the new merge function:
# edge.yaml excerpt
crdt:
type: token_bucket
merge_plugin: /opt/openclaw/plugins/tokenBucketMerge.js
max_tokens: 1000
refill_rate_per_sec: 5
3. Deploy the Updated Service
After saving the config, restart the Edge service via UBOS:
ubos restart openclaw-edgeUBOS will pull the latest container image, mount the plugin directory, and apply the new merge logic without downtime.
4. Verify the Merge Behavior
Open a Redis shell and simulate two concurrent updates:
# Simulate node A
redis-cli HSET token_bucket:user123 tokens 200 timestamp "$(date -u +"%Y-%m-%dT%H:%M:%SZ")" userWeight 1
# Simulate node B (premium user)
redis-cli HSET token_bucket:user123 tokens 500 timestamp "$(date -u +"%Y-%m-%dT%H:%M:%SZ")" userWeight 2
After a few seconds, query the bucket:
redis-cli HGETALL token_bucket:user123The result should reflect the minimum token count (200) multiplied by the highest weight (2), capped at MAX_TOKENS. This confirms the custom merge is active.
5. Optional: Expose an Admin UI with Tailwind
If you want a quick UI for adjusting userWeight per account, reuse UBOS’s Web app editor on UBOS. Below is a minimal Tailwind component:
<div class="max-w-md mx-auto bg-white shadow-lg rounded-lg p-6">
<h2 class="text-xl font-bold mb-4">User Weight Override</h2>
<form method="POST" action="/admin/weight">
<label class="block text-sm font-medium mb-2">User ID</label>
<input name="userId" class="w-full border rounded px-3 py-2 mb-4">
<label class="block text-sm font-medium mb-2">Weight (1‑5)</label>
<input type="number" name="weight" min="1" max="5" class="w-full border rounded px-3 py-2 mb-4">
<button type="submit" class="w-full bg-blue-600 text-white py-2 rounded hover:bg-blue-700">Save</button>
</form>
</div>
Testing and Validation
Robust testing ensures the new merge logic does not introduce regressions.
Unit Tests
Use jest (Node) or pytest (Python) to assert edge cases:
- Both replicas have identical token counts – result unchanged.
- Remote replica has higher weight – result respects higher weight.
- Token count exceeds
MAX_TOKENS– result is capped. - Timestamp handling – ensure the merge does not revert to an older state.
Integration Tests
Deploy a temporary cluster with two Edge nodes, fire 10 k concurrent requests, and monitor token drift. The CRDT Wikipedia article explains why eventual consistency should converge after the merge.
Load‑Testing
Run k6 scripts that simulate burst traffic. Verify that the bucket never exceeds the configured max_tokens even under network partitions.
Conclusion and Next Steps
By injecting a custom merge plugin into OpenClaw’s Rating API Edge, you gain fine‑grained control over token allocation, enforce premium‑user policies, and safeguard against over‑consumption during spikes. The approach is fully compatible with UBOS’s one‑click deployment model, keeping your infrastructure lean while delivering enterprise‑grade rate limiting.
Ready to extend the pattern?
- Explore the Enterprise AI platform by UBOS for multi‑tenant token‑bucket orchestration.
- Leverage the Workflow automation studio to trigger alerts when token usage spikes.
- Browse UBOS templates for quick start to scaffold similar CRDT extensions for other resources (e.g., quota‑based caching).
- Join the UBOS partner program to get early access to upcoming CRDT features.
Implementing custom conflict resolution is a powerful lever for any senior engineer looking to fine‑tune distributed rate limiting. With the steps above, your OpenClaw deployment will handle concurrency gracefully, respect business policies, and stay ready for future scaling challenges.
For more deep dives on AI‑driven SaaS platforms, check out the AI marketing agents page and the UBOS solutions for SMBs.