Case Study

Rambunct Accelerates go2stream’s Fleet Platform with AWS EKS, Control Tower & Automation

Background

go2stream partnered with Rambunct to transform its fleet management platform using Amazon EKS, AWS Control Tower, and CloudFormation—delivering real-time route optimization, driver tracking, and ePOD automation through a scalable, secure, and multi-tenant Kubernetes-based solution.

The Challenge

go2stream sought a high-availability, multi-tenant platform to support real-time fleet operations across logistics companies—facing constraints in scalability, governance, and infrastructure automation.
  • Required dynamic scaling to support thousands of concurrent GPS and route tracking events.
  • Complex microservices ecosystem demanded orchestration for seamless service interaction.
  • Needed secure, isolated environments for multiple clients with unified governance.
  • Manual infrastructure provisioning hindered consistency and rapid client onboarding.

Our Solution

Rambunct implemented a Kubernetes-based microservices architecture using Amazon EKS, Control Tower, Helm, and CloudFormation to enable scalable fleet operations with centralized governance.
  • Deployed Amazon EKS clusters with autoscaling and GPU-optimized node groups for route optimization and tracking.
  • Used Helm charts and GitOps for consistent application delivery across client environments.
  • Applied AWS Control Tower for centralized security, logging, and policy enforcement.
  • Built CloudFormation stacks for automated, parameterized infrastructure deployment and disaster recovery.

The Result

The implementation enabled go2stream to deliver a resilient, intelligent fleet management platform with measurable performance and operational improvements.
  • 85% improvement in route planning speed via optimized container orchestration and ML integration.
  • 99.9% uptime across customer environments, supporting real-time logistics operations.
  • 70% reduction in deployment time through fully automated EKS cluster and app provisioning.
  • 60% increase in tracking responsiveness thanks to Kubernetes autoscaling and optimized compute.
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