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ScaleOps

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Autonomous real-time optimization for Kubernetes and AI infrastructure resources

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About ScaleOps

ScaleOps provides an advanced platform for automated, real-time optimization of Kubernetes and AI infrastructure resources. Designed for enterprise cloud environments, it dynamically rightsizes CPU, memory, GPU, and replicas based on live workload behavior and cluster conditions. The platform enhances resource utilization, reduces cloud costs by up to 80%, and improves performance reliability without manual intervention. ScaleOps is ideal for organizations running complex, dynamic Kubernetes clusters and AI workloads that require continuous tuning to maintain efficiency and uptime.

The solution offers comprehensive observability and troubleshooting capabilities, enabling IT and cloud engineering teams to gain real-time visibility into cluster costs, workload behavior, and performance metrics. By automating resource management tasks such as pod placement, spot instance optimization, and node consolidation, ScaleOps frees engineering teams from repetitive manual tuning, allowing them to focus on innovation. Its AI-driven approach ensures that resources are allocated precisely according to demand, supporting both cloud and AI infrastructure management at scale.

Key Capabilities

  • Automated real-time CPU and memory pod rightsizing
  • Dynamic replica scaling based on workload demand
  • Smart pod placement to maximize node utilization
  • Automated GPU workload rightsizing and optimization
  • Cost monitoring and cluster workload troubleshooting

Integrations

KubernetesKarpenterSpot Instances

This profile was compiled by CIOPages from public sources with AI assistance, and may be incomplete or out of date. It is informational only and not an endorsement. Represent this vendor? or .

Quick Facts

www.scaleops.com
CategoryObservability & Monitoring
PricingSubscription
DeploymentSaaS
Target SizeEnterprise