Secure Ai Agent Discovery With Agent Name Service (ans)

[Emperor2011]

Secure Ai Agent Discovery With Agent Name Service (ans)
Published 7/2025
Created by Domas Masiulis
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 26 Lectures ( 4h 32m ) | Size: 1.5 GB
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Build a robust and secure name service for your AI agents. Learn to manage, discover, and protect multi-agent systems.
What you'll learn
Understand the core principles and architecture of an Agent Name Service (ANS) for multi-agent systems.
Implement a basic, secure ANS with registration and discovery APIs from scratch.
Apply key security concepts like agent authentication and authorization to protect your agent communications.
Analyze advanced ANS topics including decentralized models, health checking, and scalability strategies for production environments.
Requirements
Basic understanding of AI concepts and agents. Familiarity with programming concepts and APIs (examples may use Python or general API design principles). No prior experience with agent name services is required.
Description
Welcome to the definitive guide on creating a secure and efficient Agent Name Service (ANS) for your AI agent ecosystems! As AI systems become more complex, involving dozens or even hundreds of specialized agents, the challenge of enabling them to find and communicate with each other securely becomes critical. This course is your solution.In this comprehensive course, we will demystify the concept of an Agent Name Service, a crucial piece of infrastructure for any serious multi-agent system. You will move from foundational theory to hands-on implementation, equipping you with the skills to build, deploy, and manage a robust ANS from the ground up.We'll start by exploring the fundamentals of AI agents and the rise of multi-agent systems. You will quickly understand why traditional service discovery methods fall short and why a specialized ANS is necessary for managing the dynamic and complex interactions in modern AI applications. We will cover the core principles, key components, and the essential processes of agent registration, deregistration, and discovery.Security is a paramount concern in any distributed system, and AI agents are no exception. A significant portion of this course is dedicated to ensuring your ANS is secure. You will learn about agent identity, robust authentication mechanisms, authorization protocols to enforce access control, and how to establish secure communication channels to prevent eavesdropping and tampering. We will make sure your agents are talking only to whom they are supposed to be talking to.Then, we'll roll up our sleeves and get practical. Guided by step-by-step instructions, you will design and implement a basic ANS. This includes designing the data schema, setting up the necessary infrastructure, and building the core API endpoints for registration and discovery. You'll gain invaluable hands-on experience that you can apply directly to your own projects.Once you've mastered the basics, we'll dive into advanced topics that will prepare you for real-world production environments. We'll compare and contrast decentralized versus centralized ANS architectures, discuss strategies for agent health checking and liveness probes, explore common service discovery patterns, and address the critical challenge of scaling your ANS to handle a large number of agents and high query loads.To tie it all together, we'll examine practical applications and real-world case studies. You'll see how an ANS can be a game-changer in automated supply chains, smart home device coordination, and complex financial services systems. By the end of this course, you will not just understand the theory; you will have the practical skills and confidence to design and implement a secure, scalable, and efficient Agent Name Service for any multi-agent system you can imagine. Join now to start building the backbone of tomorrow's AI applications!
Who this course is for
This course is designed for AI developers, software engineers, and system architects who are working with or interested in building multi-agent systems. It is also valuable for students and researchers exploring advanced AI topics. If you want to learn how to manage, discover, and securely communicate between multiple AI agents, this course is for you.


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