Electrolux Group
Scaling thousands of operations with Kotlin Ktor microservices on AWS — fast, available, resilient.
About Electrolux Group
Electrolux is a global appliance company founded in 1919 in Stockholm. They sell in over 120 markets under brands like Electrolux, AEG, and Frigidaire, with around 50,000 employees worldwide.
The Project
Challenge
The existing platform ran on Kotlin and Java Spring Boot — slow startup times, heavy memory usage, and too much boilerplate. Every optimization cycle was expensive. Electrolux needed to handle thousands of concurrent operations across global markets with sub-second response times, but the stack wasn't built for that kind of throughput. Performance had to improve across the board: cold starts, serialization, connection pooling, everything.
Solution
We replaced Spring Boot with Kotlin Ktor — lightweight, coroutine-native, and built for concurrency. Kafka decouples the services and handles event delivery. Kubernetes on EKS auto-scales the fleet, and Terraform keeps infrastructure reproducible. Circuit breakers and bulkheads keep things running when parts fail.
Technology Stack
Ktor microservices on AWS, Kafka for events, Kubernetes for orchestration. Click through to see how each piece fits.
Kotlin Ktor
AWS
Kafka
Docker
Kubernetes
PostgreSQL
Terraform
Kotlin Ktor
We picked Ktor because it's lean. No annotation magic, no heavyweight container — just coroutines and explicit routing. Each service handles thousands of connections with minimal threads. Startup is fast, memory is low, and the code stays readable.
Results & Impact
Thousands of concurrent operations with sub-second P99 response times
99.99% uptime with multi-AZ, circuit breakers, and self-healing pods
Millions of Kafka events processed daily with exactly-once delivery
40% lower compute costs through auto-scaling during off-peak hours
Zero-downtime deployments via rolling updates
10x more concurrent connections per instance compared to the old Spring Boot stack
Ready to scale your operations?
Need a backend that actually scales? Let's talk.