Mission-Critical Satellite Test Infrastructure • EGSE / ATE / KTE • Secure Automation
This repository documents the engineering work behind deploying, validating, and supporting Electrical Ground Support Equipment (EGSE) systems used in spacecraft testing for Amazon's Project Kuiper. These systems integrate ATE, KTE, and hybrid Linux/Windows environments to enable reliable, repeatable, and secure satellite validation workflows.
This work reflects hands-on engineering in a high-sensitivity aerospace environment, where precision, uptime, and security directly impact mission readiness.
- Explore
architecture/for system diagrams and layered breakdowns - See
docs/for deployment workflows and troubleshooting - Review
scripts/for automation used in rack initialization and validation - Check
config/for posture baselines, identity routing, and access policy definitions
The Kuiper EGSE deployment architecture connects Linux and Windows servers with ATE/KTE test environments to support mission-critical satellite validation. Automated workflows standardize rack configuration, enforce secure access controls, and maintain consistent operational baselines across all deployment phases. This ensures predictable test execution, reduced downtime, and high reliability for spacecraft testing operations.
Every satellite must pass rigorous electrical, functional, and communication testing before launch. EGSE systems are the backbone of this process. By standardizing deployments, improving automation, and strengthening access controls, this work:
- Reduces mission risk
- Ensures consistent test execution
- Minimizes operational interruptions
- Accelerates readiness certification
Reliable EGSE deployments directly support spacecraft readiness and contribute to successful aerospace operations.
- Deployed and validated EGSE racks across mixed Linux and Windows environments
- Supported ATE/KTE systems used for spacecraft electrical and functional testing
- Automated rack initialization, network verification, and validation workflows
- Ensured system reliability to maintain continuous satellite test operations
- Maintained secure access controls, MFA/RBAC, and endpoint protection
- Collaborated with cross-functional aerospace engineering teams
- Improved logging, telemetry, and monitoring for rapid troubleshooting
| Category | Technologies | Purpose |
|---|---|---|
| 🖥️ Operating Systems | Linux (Ubuntu, RHEL), Windows Server | Hybrid environment supporting EGSE, ATE, and KTE components |
| ⚙️ Automation | Shell scripting, PowerShell, Python | Rack initialization, validation, onboarding, and configuration automation |
| 🌐 Networking | TCP/IP, VLANs, Routing | Segmented network infrastructure for test and control systems |
| 🔐 Security | SSH, MFA, RBAC, Endpoint Protection | Secure access control and compliance enforcement |
| 📊 Monitoring | Logging systems, telemetry agents | Continuous health visibility and diagnostics |
| 🔌 Hardware | EGSE, ATE, KTE interfaces | Integration with spacecraft electrical and communication test equipment |
A high-level map of the Kuiper EGSE Deployment repository:
Kuiper-EGSE-Deployment/
│
├── architecture/
│ ├── architecture-summary.md # High-level architecture overview (sanitized)
│ ├── architecture-layers.md # Layered breakdown of EGSE/ATE/KTE systems
│ └── architecture-diagram.md # ASCII + PNG architecture diagrams
│
├── docs/
│ ├── deployment-overview.md # Deployment phases, metrics, workflows, authentication
│ ├── troubleshooting-guide.md # Common issues, symptoms, and resolutions
│ ├── runbook.md # Standard operating procedures for pipeline execution
│ └── data-dictionary.md # Definitions for raw, normalized, and processed data fields
│
├── scripts/
│ ├── onboarding-automation.ps1 # Engineer onboarding & access provisioning
│ ├── rack-initialization.py # Rack diagnostics & baseline configuration
│ ├── pipeline-validation.py # Multi-phase validation pipeline
│ └── network-verification.py # Network reachability & segmentation checks
│
├── config/
│ ├── network-baseline.yaml # Standardized network configuration baseline
│ └── rack-profile.json # Rack-specific configuration profile
│
└── README.md # Main project documentation
📐 Architecture:
- architecture-summary.md — High-level overview of EGSE/ATE/KTE architecture
- architecture-layers.md — Layered breakdown of system components
- architecture-diagram.md — ASCII and PNG architecture diagrams
📘 Documentation:
- deployment-overview.md — Deployment phases, metrics, workflows, authentication
- troubleshooting-guide.md — Common issues, symptoms, and resolutions
- runbook.md — Standard operating procedures for pipeline execution and validation
- data-dictionary.md — Definitions for raw, normalized, and processed data fields
<> Scripts:
- onboarding-automation.ps1 — Engineer onboarding & access provisioning
- rack-initialization.py — Rack diagnostics & baseline configuration
- pipeline-validation.py — Multi-phase validation pipeline
- network-verification.py — Network reachability & segmentation checks
⚙ Configuration:
- network-baseline.yaml — Standardized network configuration baseline
- rack-profile.json — Rack-specific configuration profile
Pipeline: Initialization → Configuration → Validation → Handoff
| Step | Action | Tools Used |
|---|---|---|
| 1 | Prepare rack hardware, verify power, confirm baseline OS images | Physical diagnostics, Linux/Windows utilities |
| 2 | Configure network interfaces, VLANs, routing, gateway connectivity | network-baseline.yaml, network-verification.py |
| 3 | Initialize EGSE, ATE, and KTE systems with standardized baselines | rack-initialization.py, PowerShell, Bash |
| 4 | Apply secure access controls (MFA, RBAC, endpoint protection) | OS security tooling, enterprise controls |
| 5 | Run multi-phase validation pipeline to certify readiness | pipeline-validation.py |
| 6 | Enable logging, telemetry, and monitoring integrations | Log aggregation tools, monitoring agents |
| 7 | Validate communication paths across EGSE → ATE → KTE | Automated test scripts, orchestration flows |
| Area | Impact |
|---|---|
| ⚡ Reliability | Standardized initialization and validation improved stability across EGSE/ATE/KTE systems |
| ⏱️ Efficiency | Automated tooling reduced deployment and readiness verification time |
| 🔒 Security | MFA, RBAC, endpoint protection, and encrypted baselines strengthened access control |
| 🤝 Collaboration | Unified workflows improved coordination across hardware, software, and test teams |
| 🎯 Uptime | High availability enabled continuous satellite test operations |
- Standardized EGSE deployments across mixed Linux/Windows environments
- Eliminated configuration drift using Python and PowerShell automation
- Improved ATE/KTE reliability through multi-phase validation workflows
- Strengthened access security with MFA, RBAC, and endpoint protection
- Enabled repeatable validation cycles across multiple racks
- Enhanced monitoring and telemetry for rapid troubleshooting
- Multi-factor authentication (MFA)
- Role-based access control (RBAC)
- Encrypted configuration baselines
- Hardened remote access (SSH, secure endpoints)
- Logging and audit visibility
All content in this repository is fully sanitized. No proprietary spacecraft data, internal documentation, or sensitive operational details are included. Only generalized engineering patterns and deployment workflows are presented.
Suren Jewels
Cloud & Infrastructure Engineer • Security & Automation Specialist
This repository showcases sanitized engineering patterns and automation workflows used in enterprise ServiceNow environments.
- LinkedIn: https://www.linkedin.com/in/suren-jewels/
- GitHub: https://github.com/Suren-Jewels
- Email: SurenJewelsPro@gmail.com