Edge Computing

Build and run zero touch managed edge environments with the leading AI capable platform scaling to all your low-latency needs, optimize bandwidth, potential for data privacy or cyber security concerns also with multi tenant, multi-user environments.

Familiar Challenges

  • Service needs low-latency connections

  • High network and data transfer cost

  • Insufficient network capacity at a specific location

  • Data privacy and cybersecurity concerns 

  • Complexities in managing distributed systems, including service orchestration, monitoring, CI/CD pipelines, and cost management.

Our Solution

  • Reduce latency and improve performance by deploying workloads closer to users and devices

  • Implement traffic routing and optimization strategies together with AI powered capabilities

  • Orchestrate and monitor distributed workloads across on-premises, edge, and cloud environments

Our Unique Value

  • Demonstrated experience for edge computing Comprehensive Google Cloud knowledge

  • Accelerated Deployment Frameworks

  • Google Cloud Specialization on Application Development

  • Wide experience and best practices on multiple AI use cases

Edge Computing | Reunalaskenta

Our Edge Computing References

Telia: Pioneering multitenant edge computing with advanced Google Cloud capabilities. Using Google Kubernetes Engine for Enterprise, it ensures resource isolation, scalability, unified management, and enhanced security. Integrated with 5G – or, in the future, 6G – networks, offering exceptional service, enabling developers to build new applications flexibly and cost-efficiently yet securely and use the shared edge computing resources on Google Cloud.

Google Cloud Capabilities

  • Google Kubernetes Engine for Enterprise (Anthos)

  • Cloud Build, Artifact Registry, and Operations Suite

  • Cloud Storage, Cloud SQL

  • PubSub, Cloud Functions

  • Cloud Monitoring

  • Terraform, Deployment Manager

  • BigQuary, Vertex AI

How to Get Started

  • Conduct a workshop to evaluate low-latency, network-intensive and data sovereignty workloads

  • Design an architecture with centralized management

  • Implement pilot edge workloads