What is probably broken
Running multiple AI agents on one machine without process isolation leads to resource contention, crashed agents, and lost context. Each agent needs its own config, workspace, and port.
Multi-agent deployment guide
A single OpenClaw instance is powerful. A fleet of specialized agents: one for code, one for support, one for research: working in parallel is transformative. This guide shows you how to run multiple OpenClaw agents on one VPS using systemd, Docker Compose, and isolated workspaces.
Running multiple AI agents on one machine without process isolation leads to resource contention, crashed agents, and lost context. Each agent needs its own config, workspace, and port.
A fleet of 3-6 specialized OpenClaw agents running 24/7 on a single VPS, each with its own identity, channels, and workspace, auto-restarting on failure.
STEP 01
Decide which agents you need and what each one owns before writing any config.
STEP 02
OpenClaw stores memory, config, and credentials per workspace. Duplicate the structure for each agent.
STEP 03
Define all agents as separate services in one docker-compose.yml for single-command management.
STEP 04
Six agents hitting the same API provider will hit rate limits. Build a failover chain.
STEP 05
An unmonitored multi-agent setup fails silently. Add health checks and alerts.
Quick check
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