Company Packs

DevOps Command Center

Name: DevOps Command Center
Brand: Solo Unicorn
Price: 149 USD
Availability: InStock

Eight agents managing deploys, incidents, and infrastructure health

// First 7 days

What can be running fast.

01

Get a ready-to-run system that replaces blank-page setup.

02

Ship a usable package with 15 included files and working structure.

03

Move from purchase to first setup in about 20 min.

// Included files

What is inside the package.

company.yaml

agents/deploy-manager.md

agents/incident-responder.md

agents/log-analyzer.md

agents/metric-alerter.md

agents/capacity-planner.md

agents/security-scanner.md

agents/runbook-executor.md

agents/sre-manager.md

workflows/deploy-pipeline.yaml

workflows/incident-response.yaml

skills/log-parsing.md

skills/runbook-execution.md

mcp-servers.json

README.md

Description

What is DevOps Command Center?

DevOps/SRE operations center. Deployment management, incident response, log analysis, metric alerting, capacity planning, security scanning, and automated runbook execution.

solo-unicornclaude-code

Upgrade path

01Start with this package and validate the workflow.
02Add specialized skills or bundles once the core system is stable.
03Use the community to sharpen positioning, demos, and feedback loops.

Previewcompany.yaml

# company.yaml
name: devops-command-center
version: "1.0"
description: DevOps/SRE operations center

agents:
  - id: deploy-manager
    role: "Manage deployment pipelines and rollbacks"
    skills: [deploy-orchestration, rollback-strategy]
    mcp_servers: [github, datadog, pagerduty]
    triggers:
      - webhook: github.deployment.created
        action: manage-deploy

  - id: incident-responder
    role: "Classify incidents, page on-call, run playbooks"
    skills: [severity-classification, communication]
    triggers:
      - webhook: pagerduty.incident.triggered
        action: respond-to-incident

// Community acceleration

Use the room after the purchase.

Bring your workflow into the Solo Unicorn community for sharper feedback, operator critique, and more visibility once the system is live.

Discuss implementation

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