Case Study: TeamSystem achieves lower cloud costs and improved latency with Akamas

Delivering high-quality SaaS services at lower cloud cost and carbon footprint

TeamSystem, a leading provider of business software applications and SaaS services for SME clients, labor professionals, and accountants, was facing rising cloud costs as its Kubernetes-based microservices scaled across Azure and AWS. The company needed to reduce spending without harming service quality, agility, or the frequent updates required to stay aligned with changing legislation.

Using Akamas’ AI-powered autonomous optimization platform, TeamSystem optimized JVM, Kubernetes, and autoscaling parameters for critical microservices on Azure Kubernetes Service. Akamas found a better configuration in just 20 hours, cutting costs by 49% at peak load and 66% at off-peak load while maintaining throughput and slightly improving average response time by about 5%, also lowering latency by reducing autoscaling triggers.

TeamSystem

Luca Montecchiani

Lead Software Architect, Product Owner