OpenClaw Lark Robot Message Queue Integration

Message queue integration makes a Lark robot resilient under bursty traffic. Without a queue, slow model calls and tool calls can pile up and make the bot feel unreliable. With a queue, you can buffer work, control concurrency, and implement safe retries.

OpenClaw can separate intake from processing, and Tencent Cloud Lighthouse provides a stable 24/7 environment that’s simple, high performance, and cost-effective.

Why MQ helps Lark robots

• burst group messages
• variable model latency
• retryable transient failures

Guided conversion: deploy OpenClaw on Lighthouse

• Visit: open Tencent Cloud Lighthouse Special Offer for OpenClaw.
• Select: choose OpenClaw (Clawdbot) under AI Agents.
• Deploy: click Buy Now to launch your always-on bot host.

A minimal queue configuration

# lark-mq.yaml
queue:
  name: lark_events
  max_retries: 3
  backoff_seconds: [5, 30, 120]
workers:
  concurrency: 4
  max_inflight_per_chat: 2

Next step: deploy, then add MQ for buffering and retries

• Visit: go to Tencent Cloud Lighthouse Special Offer for OpenClaw.
• Select: pick OpenClaw (Clawdbot) in AI Agents.
• Deploy: click Buy Now, then enqueue Lark events and process them via workers with bounded concurrency.

Once MQ is in place, your Lark robot stays responsive even when chats get noisy.