Crypto Flexs
  • DIRECTORY
  • CRYPTO
    • ETHEREUM
    • BITCOIN
    • ALTCOIN
  • BLOCKCHAIN
  • EXCHANGE
  • ADOPTION
  • TRADING
  • HACKING
  • SLOT
Crypto Flexs
  • DIRECTORY
  • CRYPTO
    • ETHEREUM
    • BITCOIN
    • ALTCOIN
  • BLOCKCHAIN
  • EXCHANGE
  • ADOPTION
  • TRADING
  • HACKING
  • SLOT
Crypto Flexs
Home»ADOPTION NEWS»Improving Data Center Performance Using AI Agents and OODA Loops
ADOPTION NEWS

Improving Data Center Performance Using AI Agents and OODA Loops

By Crypto FlexsSeptember 17, 20243 Mins Read
Facebook Twitter Pinterest LinkedIn Tumblr Email
Improving Data Center Performance Using AI Agents and OODA Loops
Share
Facebook Twitter LinkedIn Pinterest Email

Alvin Lang
17 Sep 2024 17:05

NVIDIA introduces an observable AI agent framework that uses the OODA loop strategy to optimize management of complex GPU clusters in the data center.





Managing large, complex GPU clusters in a data center is a massive undertaking, requiring careful oversight of cooling, power, networking, and more. According to the NVIDIA Technical Blog, NVIDIA has developed an observable AI agent framework that leverages the OODA loop strategy to address this complexity.

AI-based observation framework

The NVIDIA DGX Cloud team, which manages the global GPU fleet across major cloud service providers and NVIDIA’s own data centers, has implemented this innovative framework that allows operators to interact with their data centers to ask questions about GPU cluster stability and other operational metrics.

For example, an operator can query the system for the top five most frequently replaced components that are at risk for supply chain risk, or assign a technician to fix a problem in the most vulnerable cluster. This feature is part of a project called LLo11yPop (LLM + Observability), which uses the OODA loop (Observe, Orient, Decide, Act) to improve data center management.

Accelerated Data Center Monitoring

With each new generation of GPUs comes the need for comprehensive observability. Standard metrics like utilization, errors, and throughput are just the bar. To fully understand the operating environment, additional factors like temperature, humidity, power stability, and latency must be taken into account.

NVIDIA’s system leverages existing observability tools and integrates them with the NIM microservice, allowing operators to talk to Elasticsearch in human language, providing accurate and actionable insights into issues like fan failures across the fleet.

Model Architecture

The framework consists of different agent types.

  • Orchestrator Agent: Pass your questions to the right analyst and choose the best course of action.
  • Analyst Agent: Translates broad questions into specific queries that search agents answer.
  • Action Agent: Coordinate response, including notifying Site Reliability Engineers (SREs).
  • Search Agent: Execute a query against a data source or service endpoint.
  • Task Execution Agent: Perform specific tasks through the workflow engine.

This multi-agent approach mimics an organizational hierarchy, with directors coordinating tasks, managers leveraging domain knowledge to assign work, and workers optimizing for specific tasks.

Moving to a multi-LLM composite model

To manage the diverse telemetry required for effective cluster management, NVIDIA uses a Mixed Agent (MoA) approach, which involves using multiple large-scale language models (LLMs) to process different types of data, from GPU metrics to orchestration layers like Slurm and Kubernetes.

By linking small, focused models, the system can fine-tune specific tasks, such as generating SQL queries for Elasticsearch, thereby optimizing performance and accuracy.

Autonomous agent with OODA loop

The next step is to close the loop with autonomous supervisory agents operating within the OODA loop. These agents observe data, take direction, decide on actions, and execute them. Initially, human supervision ensures the reliability of these actions, forming a reinforcement learning loop that improves the system over time.

Lessons learned

Key insights gained while developing this framework include the importance of rapid engineering rather than initial model training, selecting the right model for a particular task, and maintaining human supervision until the system is proven to be reliable and secure.

Building AI Agent Applications

NVIDIA offers a variety of tools and technologies for those interested in building their own AI agents and applications. Resources are available at ai.nvidia.com, and detailed guides can be found on the NVIDIA Developer Blog.

Image source: Shutterstock


Share. Facebook Twitter Pinterest LinkedIn Tumblr Email

Related Posts

NVIDIA improves everything by acceleration of RTX AI PC.

June 2, 2025

BNB AI Hackathon promotes innovative projects to higher classes

June 2, 2025

Stellar (XLM) Soroban Audit Bank Smart Contract Security Improvement

June 2, 2025
Add A Comment

Comments are closed.

Recent Posts

Bitcoin vs Altcoins-Check for the new ALT season.

June 2, 2025

NVIDIA improves everything by acceleration of RTX AI PC.

June 2, 2025

SPX, DXY, BTC, ETH, XRP, BNB, SOL, Doge, ADA, Hype

June 2, 2025

Electrum testnet wallets do not display the trading record for the address.

June 2, 2025

BNB AI Hackathon promotes innovative projects to higher classes

June 2, 2025

It is so easy to be a millionaire! Winner Mining helps to become rich in 2025

June 2, 2025

Can Ether Lee’s signal with a major candlestick pattern?

June 2, 2025

Stellar (XLM) Soroban Audit Bank Smart Contract Security Improvement

June 2, 2025

Flux.1 KONTEXT: Edit Image Editing as a Multimodal Model

June 2, 2025

Genzio podcast | Vault12 encryption inheritance and asset management | Toronto

June 2, 2025

TRON (TRX) sets a new record for monthly transmission in May.

June 2, 2025

Crypto Flexs is a Professional Cryptocurrency News Platform. Here we will provide you only interesting content, which you will like very much. We’re dedicated to providing you the best of Cryptocurrency. We hope you enjoy our Cryptocurrency News as much as we enjoy offering them to you.

Contact Us : Partner(@)Cryptoflexs.com

Top Insights

Bitcoin vs Altcoins-Check for the new ALT season.

June 2, 2025

NVIDIA improves everything by acceleration of RTX AI PC.

June 2, 2025

SPX, DXY, BTC, ETH, XRP, BNB, SOL, Doge, ADA, Hype

June 2, 2025
Most Popular

From a historic banking family to BTC — Rothschild-linked company invests in Bitcoin ETFs GBTC and IBIT.

May 15, 2024

UPDATE: Mt. Gox Moves Billions of Dollars in Bitcoin Ahead of Expected Payout

July 16, 2024

Pepe price is down 24%, but its rival PEPE ICO is close to $35 million.

December 24, 2024
  • Home
  • About Us
  • Contact Us
  • Disclaimer
  • Privacy Policy
  • Terms and Conditions
© 2025 Crypto Flexs

Type above and press Enter to search. Press Esc to cancel.