Landslide Cloud-Native Infrastructure Benchmarking

Benchmark CPU, memory, storage, and networking performance across Kubernetes clusters to validate infrastructure readiness before CNF deployment.

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  • Technology

    Kubernetes, Cloud-Native Infrastructure, 5G SA, 5G-Advanced

  • Test types

    CPU Benchmarking, Memory Benchmarking, Storage Benchmarking, Networking Benchmarking, A/B Testing, Shadow Testing, Continuous Benchmarking

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Highlights

Landslide Cloud Engine benchmarks the performance, efficiency, and behavior of cloud-native infrastructure and cloud-based resources under real-world conditions using a tiered, microservices-based architecture.

Performance benchmarking

  • Benchmarks CPU, memory, storage, and networking across major private cloud Kubernetes distributions including OpenShift, VMware Tanzu, WNDRVR Cloud Platform, Rancher, and k3s
  • Measures CPU throughput, memory utilization, storage input/output (I/O), and network traffic under configurable workloads
  • Captures detailed Kubernetes-layer metrics on utilization, latency, and allocation efficiency

Workflow and automation

  • Drag-and-drop workflow engine combines unlimited CPU, memory, storage, and networking actions in a single scenario
  • Integrates with continuous integration/continuous delivery (CI/CD) pipelines for ongoing infrastructure benchmarking as part of DevOps workflows
  • Supports user-defined workloads and parameters to emulate diverse operating conditions

Visualization and analysis

  • Real-time dashboards powered by Grafana, Prometheus, and Kafka for rapid, data-driven decisions
  • Comprehensive metrics collection from Kubernetes exporters including cAdvisor, Node Exporter, and kube-state-metrics
  • Time-series database stores results for trend analysis and correlation visualization

Dynamic infrastructure validation

  • Validates that Kubernetes clusters can dynamically allocate, migrate, and recover workloads across multi-vendor environments
  • Supports A/B and shadow testing to compare configuration changes
  • Identifies resource bottlenecks before production deployment