From no-code to scalable backend: the digital transformation of Cardino
About the project
Cardino is an innovative B2B platform designed for car dealers, enabling the purchase and sale of electric and plug-in hybrid vehicles. The company provides new vehicle listings daily, featuring various brands and models, including nearly new and used cars sourced from across Europe. Cardino stands out with a standardized vehicle verification process, which includes service history, technical condition, and battery reports.
IT System Migration
System Performance Improvement
Market Expansion
Back-end Development
Standardization of Technical Processes
Ingestion Pipeline Development
Digital Transformation
From challenge
Key Challenges
- Performance and scalability issues – as sales volume grew from 40 to 400 vehicles per month.
- Dependence on external operators and their reliability – resulting in downtimes of up to 24 hours.
- Limited control over data and business logic – restricting flexibility and customization.
Lack of a Unified Data Format - Vehicle data was provided in various formats (JSON, PDF, multiple languages), requiring standardization and integration to ensure seamless processing.
Need for Automation - Manual auction listing was time-consuming and prone to errors. Automating the process aimed to increase efficiency and reduce operational costs.
Key functional requirements
Support for vehicle data in various structures and languages (PDF, JSON).
Data processing and standardization to meet platform requirements.
Integration with multiple car suppliers.
Automation of the auction creation process – minimizing manual work when adding new listings.
Error reduction – ensuring high data quality on the platform.
Sales process monitoring – maintaining operational stability.
Through the solution
Through the solution
Migration to Kotlin and Spring Boot
- Eliminating no-code tools and replacing them with a scalable backend.
Development of an ingestion pipeline
- Modular architecture enabling easy integration with new vehicle suppliers.
Microservices Implementation
- Integration with FINN via REST API.
- Integration with Trading Solutions through Octoparse API.
Automated data processing
- Standardizing and analyzing data from various sources to unify formats.
Monitoring and scalability
- Using Kubernetes and Argo CD for deployment management and resource optimization.
To the success
Technological outcomes
Deployment of an automated pipeline
Data from supplier APIs is fetched and published on the Cardino platform without user intervention.
Elimination of no-code
Transitioning to full-code development enabled better control over business logic and process optimization.
Increased performance
The system is now fully scalable and can dynamically adapt to a growing number of vehicles.
Business Benefits
Reduced operational costs
Process automation has decreased the need for manual offer management.
Increased sales
Cardino can now handle more transactions per month, boosting revenue.
Minimized human errors
Data standardization and automation have reduced the number of errors in auctions.
Project team
Mirek
Backend developer
Project Management Methodology
The project was executed using the Kanban methodology, allowing for continuous task prioritization without the need for sprint planning.
- Lack of a testing environment – Code was deployed directly to production, posing risks to system stability.
- No dedicated testers – Testing processes were limited to internal code reviews by the development team.
Tech stack
Kotlin
SpringBoot
JOOQ
ArgoCD
Make
Kubernetes
AWS
RDS
PostgreSQL
Datadog
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Conclusions & recommendations
Key Lessons Learned
FlowBoost.pro workshops – Enabled a quick understanding of the client’s environment and documentation of essential information (domains, rules, challenges).
Best Practices
Automation and monitoring – ArgoCD and Kubernetes ensure greater system stability and better control over deployments.
The critical role of testers – The lack of a testing environment introduced additional deployment risks.
Modular ingestion pipeline – Facilitates easy scaling and adaptation to new data providers.
Miro as a planning tool – Visualizing processes in Miro helped organize work and synchronize the technical team with the business side.
Documentation in Miro – Enhances transparency and communication within the team.
