Why testing AI inference deployments is important?

AI inference accounts for the majority of the cost when looking across the lifetime span of building, training, and deploying an AI model in production. For confident roll-out, it is paramount to fully test AI inference infrastructures and stacks before production to expose performance bottlenecks early, scale limits as well as derive better cost estimates. The Keysight AI Inference Builder is purpose-build for this space, and it can reveal bottlenecks across the entire path: from front‑end ALBs / WAFs / AI Security gateways to SmartNICs / DPUs and finally to GPUs, KV‑cache, memory bandwidth, and serving queues, point where the latency, failures, or scalability limits originate, enabling precise tuning, and smarter architecture choices.

How can I benchmark AI inference deployments?

Benchmarking AI inference deployments requires test solutions capable of emulating realistic AI workloads at scale across a variety of environments providing meaningful KPIs. AI inference infrastructures can leverage various public clouds or highly customized private deployments. Therefore, use a test tool that can generate inference traffic from virtual traffic agents as well as using dedicated hardware. While many tools fall short for such challenging requirements, the Keysight AI Inference Builder features lightweight traffic generation agents that can realistically emulate AI inference workloads at scale across virtual and physical deployments while also offering real-time statistics. It can de-risk architecture choices by comparing multiple AI infrastructure components (LLM engines, orchestrators, SmartNICs, ALBs / WAFs, AI security gateways, GPUs / TPUs) using uniform, repeatable benchmarking scenarios, therefore, enabling data driven decisions.

How can I simulate realistic AI workloads for AI inference testing?

Simulating realistic AI workloads for inference testing requires more than just sending simple HTTP prompts. It involves deep research into realistic user persona specific to various industries (for example, financial, legal) as every prompt shape can impact the inference stack across GPU, memory capacity or bandwidth or in a unique manner. The Keysight AI Inference Builder can help optimize network, hardware selection, model serving layers, engines, orchestrators, and GPU / memory usage with a curated library of prompt models and workloads that reflect real-world usage patterns across industries and application types (for example, financial, legal) or technology benchmarks (for example, GPU compute, memory).

Which statistics are important for AI inference validation?

Validating AI Inference deployments involves interpreting statistics across the board from the client perspective, network transport, and very importantly, from the serving stack. In this context, having a single pane of glass view of inference native KPIs from both the client as well as server perspective is instrumental in discovering hidden AI inference stack bottlenecks and inefficiencies. The Keysight AI Inference Builder enables unparallel correlation of client-side metrics with the ingestion of inference engine level telemetry (for example, VLLM statistics), and system-level GPU telemetry (for example, DCGM data) together in one time-synchronized view. These statistics include concurrent users, time-to-first-token, time-to-last-token, prompt/s, token rate, prefill and decode time, cache utilization, scheduler state, GPU power usage, and tensor core usage.

How can I ensure scalable, robust, and resilient AI Inference deployments?

Scalable, robust, and resilient AI Inference deployments require rigorous validation with tools that can easily scale to production-level user concurrency, offers granular control over the generated traffic load, and offers comprehensive automation capabilities for a dynamic mix of representative test scenarios. The Keysight AI Inference Builder accelerates capacity planning and controlling costs by scaling up to millions of simulated users to assess the AI inference infrastructure and software stack under production-scale load with granular control over the generated test load (that is, prompts per second). It enables unparallel resilience and robustness testing of AI inference infrastructures and stacks with fully automated test scenarios for repetitive short duration test or long duration soak tests.

KAI Inference Builder

Validate and Optimize AI Inference Infrastructures

KAI Inference Builder (KAI IB) is an emulation and analytics solution designed to validate, benchmark, and optimize AI inference infrastructures and software stacks emulating realistic AI workloads with high fidelity and at scale, providing deep insights into the performance characteristics, capabilities, and security efficacy of inference systems.

Realistic AI Inference Workload Emulation

Emulate realistic AI LLM inference traffic — matching real user behavior and workloads — to validate inference infrastructures and stacks under conditions that mirror production, not synthetic lab tests.

High Scale Traffic Emulation

Scale to millions of users or prompts per second to quantify true user concurrency linking performance to cost‑per‑token and helping teams plan capacity and ROI accurately.

Private or Public Cloud Deployment Options

Validate private or public cloud-deployed AI inference infrastructures with fully virtual or hardware base inference client emulation.

Single Pane of Glass Statistics View

Have a single pane of glass view with inference native metrics from both the client perspective and statistics ingested from server for faster pinpointing of bottlenecks and streamlined optimizations.

Introducing Keysight AI (KAI) Inference Builder

KAI Inference Builder is an inference-aware emulation and analytics solution designed to validate, benchmark, and optimize AI inference infrastructures under real-world workload conditions. KAI Inference Builder helps teams move beyond synthetic benchmarks and generic load tests by bringing workload-aware, full-stack validation into AI data center deployments.

Most Popular Configurations

KAI Inference Builder Bundle with 2 Agents and up to 100 Prompts per Second

Model

952-1001

The KAI Inference Builder Bundle includes two agents and up to 100 prompts per second (1-year subscription, floating worldwide). The bundle is TAA Compliant.

KAI Inference Builder Bundle with 10 Agents and up to 1000 Prompts per Second

Model

952-1010

The KAI Inference Builder Bundle includes 10 agents and up to 1000 prompts per second (1-year subscription, floating worldwide). The bundle is TAA Compliant.

KAI Inference Builder Bundle with 10 Agents and up to 10,000 Prompts per Second

Model

952-1100

The KAI Inference Builder Bundle includes 10 agents and up to 10,000 prompts per second (1-year subscription, floating worldwide). The bundle is TAA Compliant (952-1100).