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A suite for GPUaaS and AI cloud providers who want to turn raw GPU capacity into predictable experience for inference and training workloads—while keeping the option to monetize experience-based tiers. A product suite that helps AI cloud and GPUaaS providers to better manage their network resources to facilitate customer and AI workload growth in an optimal way.

 

What’s in the Observability and Optimization Suite

360-degree Network Observability

  • Real time and historical insight into bandwidth, latency, and traffic performance
  • Highly contextual insights across apps, content, clients, locations, network segments and more
  • AI-powered insights for rapid problem identification and troubleshooting
  • Monitor SLAs & QoE per tenant
  • Monitor bandwidth and quota usage per tenant
  • Identify and troubleshoot problems in real-time.

Network Workload Optimization

  • Manage very high-volume ingress and egress traffic effectively
  • Manage spiky heavy training flows
  • Shape low priority system and software update traffic
  • Prioritize low-latency inference and agentic communication
  • Isolate inter–data center replication from client traffic to protect performance
  • Dynamically activate traffic management for heavy usage clients

Service Personalization

  • Define service tiers across various client based on SLA requirements
  • Define policy templates that encompass the bandwidth and resource allocation per device or content specifically to their workloads
  • Rapidly apply policies for new users, applications, etc.
  • Monitor and manage quotas and policy use per client and tier

Network Security

  • Complements firewalls, device and system security
  • Identify network threats that slip past firewalls before they breach systems
  • Detect anomalies & network-based attacks such as DDoS, flow masquerading, scans & floods
  • Rich metadata with flow audit to SIEM platform
  • Block unauthorized apps, traffic or geos (dynamic and static)

Motions Foresight Enables

Observe

Connect tenant experience and workload performance to network behavior.

  • Tenant-, workload-, server- and region-level network QoE scoring and detailed performance metrics.
  • Correlation between network issues and performance with specific network fabrics or paths.
  • Insights into tenant and workload application mix across network segments and regions.
Optimize

Optimize your network traffic across various tenants and workloads.

  • Allocate bandwidth across different tenants and workloads
  • Control both ingress and egress traffic effectively
  • Manage bandwidth between real-time jobs and heavy training ones
  • Prioritize low-latency inference and agentic communication
  • Dynamically activate traffic management for heavy usage clients
Personalization and Monetization

Offer differentiated SLAs and usage services and monetize each.

  • Latency- or reliability-based tiers for inference.
  • Premium training windows or fabrics with measured benefits.
  • Experience-backed commitments to strategic tenants.

Who uses the AI and GPU Observability Suite

Cloud and SRE Teams
Diagnose performance regressions with tenant and job context, not just node metrics
Capacity and Fabric Planning
Plan GPU and network expansion based on where workloads actually feel pain
Product and Commercial
Design, price and defend SLAs and tiers grounded in real experience data