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Nutanix AI

Nutanix AI

End-to-end observability for your Nutanix AI Agentic and LLM workloads.

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How Dynatrace integrates with Nutanix AI to provide automatic, real‑time observabilityCreate powerful dashboards to provide a comprehensive overview to AI model and services for reliability, performance, and cost management.Get visibility into latency, reliability, and cost measurements for your Agentic and LLM application.End-to-end tracing for Agentic and LLM workloadsSide‑by‑side comparison of AI models and agents, with performance, cost, and quality metrics to support A/B testing.
  • Product information

Overview

Nutanix AI is a comprehensive solution for all your AI apps and agents across on‑premises, hybrid, and multicloud environments. Nutanix AI provides a consistent foundation for running models, AI services, and inference workloads of your choice to help you maintain control, privacy, and security over your models, data, and token costs with the same ease of running other business critical workloads

Dynatrace delivers automatic, real‑time observability across your full Nutanix AI stack, from Kubernetes clusters and Nutanix infrastructure to AI services, models, and prompt flows - using metrics, traces, logs, and topology without additional proprietary instrumentation.

By combining Dynatrace end‑to‑end observability with Nutanix AI, you gain unified visibility into model behavior, service health, infrastructure utilization, and token‑level cost, all correlated in a single platform to help you operate AI workloads confidently in production.

Use cases

Monitor service health and performance

  • Detect bottlenecks using real‑time metrics for inference requests, latency, throughput, and error rates across Nutanix AI services and Kubernetes workloads.
  • Correlate model performance with underlying Kubernetes nodes, underlying infra resources, and Nutanix infrastructure to identify root causes faster.
  • Track SLOs for AI services and APIs using Dynatrace dashboards and alerting.

Monitor model behavior, quality, and cost

  • Validate model response time, token usage, and throughput using OpenTelemetry and vLLM metrics ingested into Dynatrace.
  • Detect abnormal cost patterns, usage spikes, and inefficient prompts before they impact budgets.
  • Compare models, versions, and endpoints to prevent quality regressions during rollout.

Get started

To get started with Dynatrace observability for Nutanix AI, follow the step‑by‑step setup guides in the GitHub repository. The repository covers infrastructure, Kubernetes, and AI observability scenarios, including dashboards and OpenTelemetry‑based integrations.

View setup guides on GitHub

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