Energy Transmission Project

A realistic utility-style platform that shows how an energy company could deploy and monitor a .NET 8 transmission application using:

• Red Hat OpenShift and AWS EKS for Kubernetes
• Jenkins for CI/CD automation
• Docker for containerization
• Prometheus and Grafana for observability
• Oracle Autonomous Database (ADB) for grid and transmission data storage

Repo Structure

---
config:
  layout: dagre
---
flowchart LR
 subgraph Cluster["OpenShift / K8s Cluster<br>(Ubuntu Server, On-Prem)"]
        Pod["📦 Pod<br>(.NET Energy App)"]
        Prometheus["📈 Prometheus"]
        Grafana["📊 Grafana Dashboards"]
        OracleDB["OracleDB"]
  end
    Dev["👨‍💻 Developer"] -- Push Code --> Jenkins["🧰 Jenkins"]
    Dev -- Webhook --> GitHub["🐙 GitHub"]
    GitHub --> Docker["Docker"]
    Jenkins -- Build Docker --> Docker
    Jenkins -- Manual Deploy --> Cluster
    Docker -- Docker Image --> App["App"]
    App -- Oracle SQL --> OracleDB
    App -- Deploy Pod --> Cluster
    Pod --> Prometheus
    Prometheus --> Grafana
    Grafana --> OracleDB

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This project is built as a full end-to-end demonstration suitable for interviews, portfolio presentations, and real-world cloud engineering discussions.

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⚡ Quick Links

• OpenShift Live App: https://energy-transmission-web-redleopard-dev.apps.rm2.thpm.p1.openshiftapps.com
• Jenkins Pipeline: jenkins/Jenkinsfile
• Kubernetes Manifests: k8s/
• Monitoring: monitoring/
• Ansible Automation: ansible/
• Docs: docs/

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🌐 Project Summary

This project mirrors a real utility company workflow:

• Start on OpenShift for initial hosting (as many energy companies use Red Hat OpenShift).
• Expand into AWS EKS to complete CI/CD, observability, and scalability.
• Implement a full Jenkins pipeline to automate building and deploying the .NET app.
• Build ECR repositories and container images with Docker.
• Deploy everything via Kubernetes manifests under a single namespace.
• Add Prometheus + Grafana for system-wide monitoring.
• Integrate an Oracle Autonomous Database to simulate transmission/event storage and future AI analytics.

The result is a realistic end-to-end cloud engineering demo.

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🚀 Running the App Locally

1. Run .NET Application

cd app/EnergyTransmission.Web dotnet restore dotnet run

2. Build Docker Image

cd docker docker build -t energy-transmission-web:latest -f Dockerfile ..

3. Run Container

docker run -p 8080:80 energy-transmission-web:latest

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☸️ Deploying to Kubernetes

1. Create Namespace

kubectl create namespace energy-transmission

2. Apply Manifests

kubectl apply -f k8s/

3. Verify

kubectl get pods -n energy-transmission kubectl get svc -n energy-transmission

4. Expose App

• OpenShift: use Routes
• EKS: use LoadBalancer or Ingress

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🧪 Jenkins Pipeline Overview

The Jenkins pipeline includes:

1. Checkout source
2. Restore & build .NET
3. Docker build & push to ECR
4. Kubernetes deploy (EKS or OpenShift)

File located at:

jenkins/Jenkinsfile

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📈 Monitoring with Prometheus & Grafana

Prometheus scrapes:

• Node health
• Pod restarts
• Resource usage
• Application metrics

Grafana visualizes everything in central dashboards.

Configuration inside:

monitoring/

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🗄 Oracle AI Database Integration

This provides the long-term data layer for:

• Transmission events
• Line status data
• Outage history
• Future predictive analytics

No sensitive credentials are stored in the repo.

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📸 Visual Evidence

✔ OpenShift

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✔ EKS Cluster

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✔ ECR Repository

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✔ Jenkins Pipeline

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✔ Grafana

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✔ Oracle Database

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📦 Roadmap

• Add alert rules & dashboards
• Add more Oracle queries & analytics
• Automate full deployment via Ansible
• Optional multi-cluster (OpenShift + EKS) demo

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🔗 Built With Pride

Created by Edward Thornton
Energy Transmission Project — Cloud Engineering • Kubernetes • DevOps • Observability