SwarmOps
Autonomous Agent
Swarm Orchestration
Deploy multi-agent swarms that coordinate autonomously, make decisions with audit trails, and learn across domains. Human governance at every level.
Architecture
From config to coordinated intelligence.
A swarm config defines colonies and agents. An instance spawns them, distributes work via a priority queue, executes agent tasks, checkpoints state continuously, and feeds learnings back into the knowledge base.
Swarm Config
Define colonies, agent types, max concurrency, autonomy level, and feature flags. Configs are versioned and reusable as templates.
Instance Spawning
SwarmOrchestrator initializes agents from the colony definitions. Auto-scaling between min/max agent bounds based on work queue depth.
Work Queue
Priority-ordered work items with dependencies. Agents pull from the queue, skip blocked items, and self-report completion for downstream unlocking.
Agent Execution
Each agent runs its assigned task with a configurable timeout. Results feed back through the AgentEventBus — spawned, completed, error, and terminated events.
Checkpointing
Ralph Wiggum persistence: state saved at configurable intervals (default 5 min). Long-running swarms survive failures and resume from the last checkpoint.
Knowledge Learning
Completed iterations feed learnings into the swarm_knowledge table with embeddings. Cross-domain signals correlate findings across ProductDomain boundaries.
The 4 autonomy levels
Swarm executes all decisions without human approval. Risk score threshold irrelevant — every action auto-approved. Use for sandboxed, low-stakes automation pipelines.
Actions below the auto-approve threshold (default: 85 risk score) proceed without review. High-risk decisions pause for human approval. Default for production workloads.
Broader approval gates. Production deployments, pricing changes, and feature deprecations always require sign-off regardless of risk score. More checkpoints, slower throughput.
Every consequential action requires human review. Swarm generates work plans and proposals; humans approve each iteration. Ideal for regulated environments or new swarm configurations.
Capabilities
What the swarm does, precisely.
Six core capabilities drawn directly from the 1,546-line SwarmOrchestrator and the 8-table schema that backs it.
Multi-Agent Coordination
Spawn and manage agent colonies with priority-based task distribution. Auto-scaling between configured min/max bounds. Each colony has a defined purpose, agent roster, and max concurrency — all from config, not code.
Autonomous Decision-Making
AI-driven decisions with full explainability and audit trail. Every decision is logged to swarm_decisions with rationale, alternatives considered, confidence score, and the human or threshold that approved it.
State Checkpointing
Ralph Wiggum persistence for long-running task recovery. State saved to swarm_checkpoints at configurable intervals (default 5 min). Swarms that survive 24-hour windows resume from the last verified checkpoint — not from scratch.
Cross-Domain Intelligence
Signal correlation and learning across business domains. domain_signals correlates findings across ProductDomain boundaries. A swarm working on content and one working on sales can share signals — automatically.
Cost-Controlled Execution
Configurable compute budgets per swarm instance. Task timeouts enforced per-agent (default 5 min). Session duration limits (default 24 hours). Cost tracked in swarm_metrics — spend is visible, not discovered after the fact.
Real-Time Monitoring
Live agent health, task progress, and performance metrics via AgentEventBus. Swarm events stream in real time: agent spawned, task completed, checkpoint created, approval required. Visibility without polling.
Who It's For
Teams where coordination overhead costs more than the work itself.
DevOps Teams
Managing complex deployments across multiple services where manual coordination creates bottlenecks. Define the swarm once — let it coordinate service health checks, rollout sequencing, and rollback triggers autonomously.
AI/ML Teams
Running multi-agent pipelines where each stage depends on prior results. Priority queuing, dependency management, and cross-domain signal correlation without custom orchestration code per pipeline.
Product Teams
Automating cross-functional workflows that touch content, sales, and analytics simultaneously. One swarm config spans domains. Governance gates keep humans in the loop for decisions that matter.
Tool Replacement
What SwarmOps replaces — and saves.
| Tool You're Replacing | Typical Cost | What SwarmOps Does Instead |
|---|---|---|
| Manual DevOps coordination tools | $50–$150/user/mo | Swarm colonies coordinate services, health checks, and rollout sequencing — configurable, not scripted per-project |
| Custom orchestration scripts | 100+ hrs/month maintenance | Priority work queue with dependency resolution replaces brittle script chains — changes in config, not code |
| Multiple monitoring dashboards | $30–$80/user/mo | AgentEventBus streams real-time swarm events — agent health, task progress, and checkpoint status in one view |
For a 5-person DevOps team: $4,800–$13,800/year in direct tool savings before accounting for the hundreds of hours eliminated from custom script maintenance.
Before / After
A deployment without SwarmOps. A deployment with it.
- DevOps engineer manually coordinating 10 services in sequence
- Checking 5 separate dashboards for health, metrics, and logs
- Writing and maintaining deployment scripts per environment
- Failure mid-deployment means starting over — no recovery state
- Each run's learnings live in one engineer's head, not the system
- Approval gates tracked in Slack threads and email — no audit trail
- Define swarm config → agents coordinate all 10 services autonomously
- One AgentEventBus stream — all health, progress, and checkpoint events
- Swarm config versioned and reusable — no per-environment script variants
- Failure at step 7 of 10: resume from last checkpoint, not step 1
- Learnings written to swarm_knowledge with embeddings for next run
- Every approval decision logged to swarm_decisions with full rationale
SwarmOps is running in production.
1,546+ lines of orchestration core. 8 database tables. 4 autonomy levels. Real-time checkpointing. Not a roadmap — a working system.