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A Platform as a Service (PaaS) Case Study for a Large Automotive Supplier

White Label PaaS - Critical Infrastructure You Control

The development of an in-house PaaS (Platform as a Service) can be just the right solution for large companies that seek full control and strive to minimize (or eliminate) their reliance on third-party vendors. The main challenge was to create a flexible and functional PaaS that would also allow the client to extend the time of the electric cars’ batteries life. In this case study, we share the details of this project, explain how we solved the client’s issue with the help of White Label architecture and reached the needed result!

Our client is a large automotive supplier. We are not permitted to give the name as a result of our NDA but are permitted to offer the description that the client in question is a startup model backed by a transnational corporation - a major manufacturer of auto electronics and spare parts in the EU.

Project Overview
  • Built a stable in-house PaaS for the customer using White Label architecture
  • Enhanced functionality and security
  • Seamless algorithm integration for calculating battery health, correct charging cycles, recommendations and assessment of the charging schedule and driving models
  • Ensured multi-tenancy

The Challenge

The K&C team was tasked to build an in-house PaaS (Platform as a service) for the customer. The key goal of the PaaS we were working on is to help the client extend the time of the electric cars’ batteries life and for rating the performed charged cycles and driving habits. The idea was to use car batteries in a way that preserves their health and charging capacity at a maximum possible level. Also we needed to provide a technical solution that were ought to provide for both multi-tenancy and seamless integration with potential tenants' portals and sites that exist already.

Our Solution

The K&C team suggested building a PaaS platform and seamlessly integrate it in the existing White label platform using the Python libraries and frameworks to turn the algorithm script into the Python microservices integrated with the Spring Cloud service discovery. Within the platform, the battery charging is controlled with the help of a cloud-based app that operates using an advanced algorithm. The application monitors the performance of car drivers and ranks them based on different criteria. Based on the data collected, the app provides car drivers with comprehensive recommendations regarding their driving habits, speed regime, etc. The offered idea allowed us to develop a flexible architectural solution that lets serving multiple tenants within one infrastructure.

First we listened

Any project starts with a clear, shared vision which becomes the basis for implementation. Our client told us their needs and priorities and we proposed an approach.

Architecture based on Microservices

A white label concept was adopted. That allowed for technological solutions to be customized for different companies without any brand connection. We used a microservice architecture to achieve lightness of loads and flexibility.

Quality Assurance

Systematic manual testing in combination with automated testing using Selenium / Cucumber ensure high quality.

Technology Stack

Microsoft Azure Cloud, Microservices based on Spring Cloud Framework, Integration Python algorithm

Need Help Building A PaaS?

The K&C team easily handles PaaS challenges facing our customers. We can build a stable and convenient platform as a service for you that will offer smart solutions to your unique issues. In case your business is in a complex organization with hybrid infrastructure, we can implement a proven, highly scalable, highly available White Label application, so don’t hesitate and contact us!

The Result

Our team has successfully built the platform requested by the customer and customized Platform as a Service (PaaS) for the client’s algorithms. 

Technology stack:

Microsoft Azure Cloud, Microservices based on Spring Cloud Framework, Integration Python algorithm, Spring Boot, Java, Spring Cloud, Rabbit MQ, Redis, Open ID Connect, OAuth2, Keycloak.

Frameworks: gunicorn; flask; connexion; psycopg2-binary; py-eureka-client.

  • Security. We ensured that the tenants’ data never crossed, so the unique user couldn’t access other users’ info. Also that each tenant would have a possibility to stop using the WL infrastructure and be sure that his personal data will be removed from the system.
  • Flexibility. We built the platform with light and adaptable mechanism, which ensured that it could be smoothly integrated into any user’s website and customized according to the user’s specific needs and preferences.
  • Scalability. Expected data transmits up to 500 000 requests per day from the car sensors.

Word of mouth

It was an exciting experience to create such a complex platform with ambitious goals in close cooperation with the customer. By understanding the client's vision, goals and constraints we use our best practices and experience to deliver whatever it takes.
Krusche & Company GmbH
Jakob-Klar-Str. 4
80796 München
+49 89 41617569-00

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