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Energy Industry Microservices Platform Development
  1. case
  2. Energy Industry Microservices Platform Development

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Energy Industry Microservices Platform Development

reenbit
Energy & natural resources
Business services

Digital Transformation Challenges in Energy Sector

Existing product admin systems required enhancement while scaling microservices architecture for new energy management solutions. Complex industry regulations, multi-tenant platform requirements, and sophisticated UI/UX demands for energy-related product distribution posed significant technical challenges.

About the Client

German-based energy industry digitalization leader specializing in energy product distribution, software solutions for energy purchase cycles, and B2B services for national/private organizations

Strategic Development Goals

  • Build scalable microservices architecture for energy process optimization
  • Develop multi-tenant energy product marketplace platform
  • Implement regulatory-compliant pricing/discount systems
  • Establish robust DevOps pipelines for continuous delivery

Core System Requirements

  • Energy usage tracking and prediction dashboard
  • Dynamic pricing calculation engine
  • Multi-tenant admin portal with customization capabilities
  • Comprehensive discount rule management system
  • Tenant-specific configuration interfaces

Technology Stack

.NET Core
Kubernetes
Azure DevOps
Azure ARM
Azure Key Vault
Angular
SQL
Azure Storage

System Integrations

  • Energy market data APIs
  • Customer identity management systems
  • Billing/payment gateways
  • Third-party energy consumption sensors

Operational Requirements

  • High-availability architecture (99.99% uptime)
  • Multi-tenancy security isolation
  • Real-time energy usage analytics performance
  • GDPR-compliant data handling
  • Auto-scaling for seasonal energy demand fluctuations

Business Impact Projections

Enables rapid expansion of energy management services portfolio, supports €50M+ in annual energy transactions through scalable platform architecture, reduces time-to-market for new energy products by 40%, and establishes foundation for AI-driven energy optimization capabilities.

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