Company Profile

Ray.Life is a leading Networking and IoT solutions provider, specializing in Captive Portal and SD-WAN services. With its own hardware infrastructure and a SaaS platform supporting thousands of connected devices, Ray.Life enables enterprises to manage and optimize their network connectivity with real-time data insights and control.

Background

Ray.Life, a Networking and IoT company offering Captive Portal and SD-WAN services, manages thousands of connected devices through its SaaS platform. However, their existing AWS and on-premise setup suffered from high costs, limited scalability, and minimal observability.

To overcome these challenges, Ray.Life partnered with Cloud Solitaire to modernize its on-premise infrastructure—aiming to build a scalable, automated, and resilient platform that enhances performance, reliability, and operational efficiency while reducing costs.

Business Challange

Ray.Life’s existing infrastructure faced several critical limitations that affected performance, scalability, and cost-efficiency:

• High Cloud Costs: The AWS ECS setup led to escalating infrastructure expenses, making scaling unsustainable.

• On-Premise Constraints: Deployments were limited to single-machine Docker environments with no redundancy or high availability.

• Limited Monitoring: Minimal observability delayed issue detection and increased downtime risks.

• Operational Complexity: On-premise deployments lacked automation, making scaling and recovery cumbersome.

Ray.Life needed a scalable, reliable, and automated on-premise infrastructure to efficiently serve large enterprise customers while optimizing costs.

Solution Offered

To address these challenges, we collaborated closely with Ray.Life’s engineering team to design and implement a modern infrastructure blueprint built on Kubernetes and GitOps principles.

• Implemented Prometheus and Grafana for real-time monitoring and alerts.

• Configured load balancers and performance optimizations for seamless operations.

Storage & Backup

• Integrated Longhorn for distributed storage across multiple servers, enabling high availability and fault tolerance.

• Configured automated cloud backups to protect critical customer and application data.

Automation & Playbooks

• Built Ansible playbooks for repeatable, reliable provisioning and scaling.

• Automated workflows for storage, monitoring, and failover — reducing manual intervention and human error.

• Deployed Kubernetes for container orchestration and environment standardization.

• Introduced GitOps using FluxCD for automated resource management.

Kubernetes Foundation

Monitoring & Reliability

Benefits

Technology Used

• Rapid Deployment: New customer environments now deploy in under one day.

• Enhanced Scalability: Kubernetes enables reliable scaling across environments.

• High Availability: Distributed storage and automated backups ensure continuous uptime.

• Operational Efficiency: GitOps and automation reduced manual tasks and errors.

• Cost Optimization: Infrastructure modernization significantly lowered long-term

• operational costs.

• Kubernetes – Cluster orchestration

• FluxCD – GitOps automation

• Longhorn – Distributed storage and backup

• Prometheus & Grafana – Monitoring and alerting

• Ansible – Infrastructure automation

• Load Balancers & Linux Optimizations – Performance and reliability enhancements

Conclusion

By embracing modern infrastructure practices and DevOps automation, Ray.Life successfully transitioned from costly, rigid systems to a scalable, high-availability platform.

This case study demonstrates how Kubernetes, GitOps, and cloud-native tooling can revolutionize even the most challenging on-premise environments — turning infrastructure into a true competitive advantage.

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