Letting Data Speak, AI Act!
Case Study
Data EngineeringImplementation of Cloud-Agnostic Smart Meter Billing Solution
Overview
A leading Indian smart meter provider partnered with JashDS to transform their AWS-locked system into a cloud-agnostic solution built on Kubernetes, achieving an 80% reduction in processing time for managing millions of consumer accounts. The new system revolutionized smart meter management through the implementation of FastAPI and TimescaleDB, enabling efficient charge calculations, automated connection management, and comprehensive usage tracking for 6 million consumers.
About the Client
A leading smart meter provider serving multiple Indian state governments, responsible for implementing smart meter systems at scale for millions of consumers.
The Challenge
The implementation of the smart meter system required integration across multiple independent systems, including smart meters, the headend system, the billing system, middleware APIs, mobile application, an administrative portal, and a pre-paid system. The administrative portal and pre-paid system were critical components, responsible for managing rate configurations, calculating charges, and handling connect-disconnect requests based on consumer balances.
The client’s in-house implementation of these core components was closely tied to AWS, leading to vendor lock-in and increased costs. System performance was also a major constraint—processing data for just a few thousand consumers took over 90 minutes. This inefficiency made it impractical to scale to the target of 6 million consumers, putting service level agreements at risk.
Key Results
- Reduced processing time by 80%, enabling charge calculations for millions of consumers within 2 hours and ensuring compliance with critical SLA requirements.
- Deployed a cloud-agnostic solution, utilizing a Kubernetes-based architecture, to scale and handle data for up to 6 million consumers.
- Managed disconnection requests based on charge calculations and consumer account balances, as well as reconnection requests after a consumer’s recharge.
- Provided 100% configurability for rates, rebates, and other charge calculation factors via an intuitive web interface for administrators.
- Achieved complete visibility into consumer usage patterns with detailed historical tracking and reporting capabilities.
Our Solution
The JashDS team developed a comprehensive cloud-agnostic solution with the following key features:
- Developed and deployed a Kubernetes-based system on GKE to replace the tightly coupled AWS setup, enabling multi-cloud flexibility.
- Created a new administrative portal for configuring rates and rebates used for charge calculations.
- Built a robust pre-paid system to manage connect-disconnect requests based on configured rates and consumers' account balances.
- Integrated a historical tracking system for detailed consumer usage and billing history.
- Developed an automated connection management system to handle disconnection and reconnection requests based on charge calculations and balance updates.
- Implemented a configuration-driven charge calculation system, allowing utility providers to easily modify rates and rebates.
Technologies Used
Related Case Studies
← Back to All Case Studies
Data Engineering
WhatsApp-Based EV Cab Booking Platform
An EV cab booking company required a fully automated backend integrated with WhatsApp Business API to streamline booking workflows and enable real-time trip management. Our team built a scalable Python and PostgreSQL-based solution with FastAPI that increased booking efficiency by 80% and ensured seamless trip updates and notifications through automated message parsing and asynchronous processing.
Read More
Data Engineering
Azure to AWS SaaS Platform Migration
An EdTech SaaS company migrated its entire Azure-hosted student risk monitoring platform to AWS in 9 weeks — lifting and shifting 17 VMs, 12 PostgreSQL databases, and multiple application services with zero disruption to school district operations. The solution leveraged Terraform, AWS Control Tower, and a fully automated CI/CD pipeline to deliver a scalable, cost-optimized cloud foundation built for rapid expansion.
Read More
Data Engineering
Real-Time AI Chatbot Platform’s Lambda to ECS Migration
An AI chatbot startup faced critical Lambda performance issues including 100% memory utilization causing crashes, 7-8 second cold starts,Scalability issues where in multiple concurrent users using this application concurrently faced issues to use the application which includes laginess taking too much time to get the response, application crashing and completely non-functional WebSocket group chat due to protocol incompatibility between Socket.IO frontend and API Gateway WebSocket backend. Through a 4-week POC engagement, we successfully containerized Lambda functions to ECS Fargate, conducted systematic JMeter load testing up to 1,000 concurrent users, and delivered complete Terraform Infrastructure-as-Code, achieving 94% response time reduction (to sub-1-second), 100% cold start elimination, 0% error rate, and validated linear horizontal scalability while providing all technical documentation and architecture recommendations for production migration decision-making.
Read MoreHave a similar challenge?
Connect with us