Electrolux Group project

Electrolux Group

Scaling thousands of operations with Kotlin Ktor microservices on AWS — fast, available, resilient.

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Electrolux Group

High-Throughput Backend & Cloud Infrastructure

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.

Founded

1919

Headquarters

Stockholm

Project Overview

Built a high-throughput backend on Kotlin Ktor and AWS, with Kafka handling the event flow between services. The focus was performance at every level.

The 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.

The Solution

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.

Electrolux Group platform

Technology Stack

High-throughput backend on Kotlin Ktor with AWS infrastructure, Kafka for event-driven communication, and Terraform for infrastructure as code.

Kotlin Ktor

AWS

Kafka

Docker

Kubernetes

PostgreSQL

Terraform

Kotlin Ktor

Ktor was picked 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 Platform?

Build high-performance backends with modern frameworks, cloud-native infrastructure, and event-driven architecture designed for throughput.

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