Client Story: From Monolith to Microservices in 3 Months for an Automotive Marketplace Company

Overview

As automotive marketplaces strive to deliver personalized, scalable, and real-time digital experiences, old monolithic systems have become barriers to progress. One such company worked with Atsky to modernize its platform, moving from a single-tier monolith to a containerized, microservices-based architecture on AWS. The result? 30% faster feature releases, better system resilience, and a smoother path to partner integrations, all within 90 days.  

The Client

A North American automotive wholesale marketplace enables real-time auctions between used car dealers and buyers. With ambitious growth goals and an expanding partner network, including credit unions and OEM data providers, their existing system couldn't keep up.  

• Business Model: B2B/B2C vehicle auction & financing platform  

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• Users: 10,000+ active dealers and agents  

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• Monthly Volume: 30,000+ car listings  

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• Original Stack: Monolithic Django + Postgres hosted on EC2 

The Challenge

The client’s monolithic platform created several bottlenecks:  

• Slow Feature Releases: Monthly releases due to fear of regressions  

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• Scalability Issues: One service failure could impact the entire application  

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• Partner Inflexibility: Integrations with financing APIs were fragile and slow 

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• Developer Frustration: Tight coupling made onboarding and testing painful  

Their goal was to replatform in under 3 months without affecting active users or revenue.  

Our Approach

Phase 1: Application Decomposition  

We ran a domain-driven analysis to break the monolith into independently deployable services. Key bounded contexts included: 

• Auction Engine  

• Dealer Onboarding & Identity  

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• Vehicle Listings & Pricing  

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• Financing & Credit Flow  

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• Notification & Analytics  

Each service was designed around clear API contracts with async communication via event buses.  

Phase 2: Infrastructure Modernization  

• Migrated from EC2 to Amazon EKS (Elastic Kubernetes Service)  

• Split Postgres DB into service-specific schemas with read replicas   

• Introduced Kafka and EventBridge for service separation  

• Centralized auth using AWS Cognito  

Phase 3: CI/CD Automation & Observability  

• Set up GitHub Actions and ArgoCD for service-level deployments  

• Canary deployments and feature flag rollouts via LaunchDarkly  

• Observability stack with Prometheus, Grafana, and Loki 

• Full-stack tracing using OpenTelemetry and AWS X-Ray 

The Results

RTO / RPO

• Recovery Time Objective (RTO): ~10 minutes

  • Once microservices were implemented on Amazon EKS, the platform began to benefit from:

  • Kubernetes self-healing (automatic pod restarts) Service-level health checks Blue/Green or Canary deployments via ArgoCD

  • With separate service boundaries, a service can fail independently without affecting the entire system.

  • In the event of a complete EKS node failure or regional service impairment, critical functionality is resumed within ~10 minutes due to multi-AZ failover alongside auto-scaling.

• Recovery Point Objective (RPO): ~0 to 5 minutes

  • Through layer decoupling and data replication using RDS read replicas, the system captures:

  • Near real-time backups Utilization of WAL (write-ahead logging) or point-in-time recovery Streaming data via Kafka/EventBridge ensures data in-flight is either persisted or retried

  • For non-transactional services (notifications, analytics), a combination of retries and idempotent design helps mitigate data loss.

  • Before modernisation, monolith deployment complexity would likely have led to RTO exceeding 1-2 hours. RPO suffered due to no event replay or partial backup mechanism.

Business Impact

• Launched a new Buy Now financing option powered by OfferLogix APIs  

• Rolled out real-time dealer bidding and live auction pricing  

• Reduced mean time to recovery (MTTR) for bugs by 60%  

• Created dedicated squads with end-to-end ownership of microservices 

• Built a platform culture ready for scale, partners, and experimentation  

“This wasn’t just a tech upgrade. We moved from one big bottleneck to a nimble, scalable platform, and we’re now shipping weekly without fear.” — CTO, Automotive Marketplace Company  

Tech Stack Highlights

• Backend: Node.js, Python (FastAPI), Kafka 

• Container Orchestration: Amazon EKS, Helm  

• Database: PostgreSQL with read replicas  

• Auth: AWS Cognito, OAuth 2.0  

• CI/CD: GitHub Actions, ArgoCD, LaunchDarkly 

• Monitoring: Prometheus, Grafana, Loki, OpenTelemetry

• Security: IAM policies, Secrets Manager, OPA for policy as code 

Why It Matters

The shift to microservices isn’t just about fancy terms; it’s about speed, resilience, and flexibility. For this client, modernization wasn’t only technical; it unlocked new business capabilities: 

• Faster time-to-market  

• Platform stability under growth stress  

• Ability to monetize new partner APIs 

Ready to Leave the Monolith Behind?

Whether you're a mobility startup or a legacy OEM, Atsky’s cloud-native modernization playbook can help speed up your transformation.