How to Validate Cloud-Native Infrastructure Performance

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Landslide CNF Testing
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Landslide CNF Testing
+ Landslide CNF Testing

Validate Cloud-Native Infrastructure Performance

Network equipment vendors, service providers, and enterprises building Kubernetes-based infrastructure for 5G, secure access service edge (SASE), multi-access edge compute (MEC), and enterprise services must confirm the platform delivers the throughput, connections or transactions per second, and latency that hosted applications and cloud-native network functions (CNFs) require. Engineers need to benchmark capacity, compare compute, network interface card (NIC), Linux distribution, container network interface (CNI), and orchestrator options, right-size resources, and tune auto-scaling policies without degrading end-user quality of experience (QoE).

Cloud-native architectures make this difficult. Heavy east-west traffic between microservices, hardware abstraction, and multivendor stacks increase points of failure, and even a CPU upgrade or new CNI version can change performance unexpectedly. Microservices restart, scale, and move between nodes, so teams must characterize how pod failures, node reboots, latency, and CPU spikes affect CNF key performance indicators before production. With vendors releasing updates continuously, manual testing cannot keep pace; validation must be automated and integrated into continuous integration and continuous deployment (CI/CD) pipelines, and must isolate bottlenecks to a specific layer or vendor in the cloud stack.

Cloud-Native Infrastructure Validation Solution

Keysight Landslide CNF Testing validates Kubernetes cloud-native infrastructure, network functions, and services such as ingress controllers for performance, scale, and resiliency. Realistic, scalable traffic emulation benchmarks cloud-native applications, including next-generation firewall, web application firewall, IPS/IDS, and load balancer CNFs, using real application workloads. Engineers measure maximum throughput and capacity with north-south traffic from outside the cluster, or deploy multiple test agents within containerized microservices to measure performance from inside each workload. Built-in cloud impairments exercise resiliency and self-healing, quantifying the effect of degradations on CNF KPIs and Quality of Service (QoS). Results help select the right NIC drivers, Linux distributions, and CNIs and isolate issues to specific areas and vendors in the cloud stack. API support enables automated, repeatable testing in any CI/CD pipeline at every deployment phase.
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How to Validate Cloud-Native Infrastructure Performance

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