A sophisticated deployment management skill for executing feature-flagged dark launches with automated performance monitoring and promotion gates.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dark-launch-controller
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install dark-launch-controller using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Dark Launch Controller?
The Dark Launch Controller is a comprehensive tool designed for high-stakes production environments where safety and stability are paramount. By leveraging Openclaw Skills, developers can deploy code silently—completely hidden from end-users—and gate visibility behind specific user segments or percentage-based rollouts. Unlike simple shadow traffic, this skill manages the lifecycle of actual code paths, ensuring that new features are tested under real load with minimal risk.
This skill bridges the gap between deployment and release, providing a structured framework for dark launches. It automates the detection of integration points, generates configuration specifications for feature flags, and establishes rigorous success criteria for promotion. Using these Openclaw Skills, teams can transition from internal testing to full global availability with confidence, backed by real-time data and instant rollback capabilities.
Dark Launch Controller Use Cases
- Deploying high-risk backend changes hidden behind feature gates for initial production validation.
- Running internal-only beta tests for employees before publicizing a new feature.
- Implementing gradual traffic ramps (e.g., 1%, 5%, 25%, 100%) based on system stability metrics.
- Managing emergency kill-switches to disable malfunctioning features in under 30 seconds without a full redeploy.
How Dark Launch Controller Works
- The skill analyzes the current feature branch against the main codebase to inventory scope and detect existing flag patterns.
- It generates a detailed JSON specification for the feature flag, including environment-specific rules and promotion gate criteria.
- Kubernetes deployment strategies are proposed, utilizing either ConfigMaps or environment variables to control feature visibility.
- During the launch, it queries Prometheus metrics to compare the latency and error rates of the new feature code path against the system baseline.
- Upon meeting performance thresholds, it generates the necessary CLI commands to promote the feature to the next traffic segment or perform a final cleanup.
Dark Launch Controller Setup
To integrate this capability into your workflow, ensure your environment has access to the target Kubernetes cluster and Prometheus metrics server. Install the necessary CLI dependencies:
# Ensure required tools are installed
sudo apt-get install jq ripgrep curl
# Verify Kubernetes access
kubectl cluster-info
# Configure Prometheus URL environment variable
export PROMETHEUS_URL="http://prometheus.monitoring.svc:9090"
Dark Launch Controller Data Schema & Taxonomy
The skill organizes deployment data using a structured metadata approach to ensure visibility throughout the launch lifecycle:
| Data Component | Format | Description |
|---|---|---|
| Flag Specification | JSON | Defines flag keys, default values, and environment-specific rollout rules. |
| Launch Plan | Markdown | A human-readable roadmap detailing phases, audience, and success criteria. |
| Monitoring Report | Markdown | A comparison table of baseline vs. feature performance metrics (p99 latency, error rates). |
| Promotion Gates | Object | A set of boolean conditions and thresholds that must be met to advance phases. |
| Deployment Manifest | YAML | Kubernetes-ready configuration for ConfigMaps or Deployment environment variables. |
Dark Launch Controller Advanced Features
- Multi-environment targeting support (Development, Staging, Production).
- Automated internal audience segmenting using attribute-based rules (e.g., email domain matching).
- Real-time Prometheus integration for delta-based performance assessment.
- Hot-reload configuration support for sub-30-second emergency rollbacks.
- Feature cleanup automation to identify and remove legacy flag code after successful GA.
SKILL.md
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