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title: Build an AI-Powered GPU Fleet Optimizer with Gradient ADK
description: A step-by-step guide to building an AI-powered GPU fleet optimizer using DigitalOcean&#x27;s Gradient ADK, LangGraph, and NVIDIA DCGM metrics. The agent scrapes...
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# Build an AI-Powered GPU Fleet Optimizer with Gradient ADK

**[DigitalOcean Community](https://daily.dev/sources/do_community)** · 14 min read · 0 upvotes · 0 comments

## Summary

A step-by-step guide to building an AI-powered GPU fleet optimizer using DigitalOcean's Gradient ADK, LangGraph, and NVIDIA DCGM metrics. The agent scrapes real-time GPU telemetry (temperature, power draw, VRAM usage, engine utilization) across all GPU Droplets concurrently, compares values against configurable thresholds, and flags idle resources via natural language queries. The tutorial covers cloning the blueprint repo, customizing idle thresholds and agent personality in config.py, extending the agent with new tools like a power_off_droplet action, testing locally, and deploying as a serverless endpoint. A comparison table weighs the AI agent approach against traditional Grafana/Prometheus dashboards, recommending the agent for small-to-mid teams and a hybrid approach for larger fleets.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.digitalocean.com/community/tutorials/gpu-fleet-optimizer>

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#digitalocean](https://daily.dev/tags/digitalocean), [#langgraph](https://daily.dev/tags/langgraph)

[View this post on daily.dev](https://daily.dev/posts/build-an-ai-powered-gpu-fleet-optimizer-with-gradient-adk-5rpzpuxj5)

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