Course Overview of Build Production-Ready Agents on Google Cloud:

This instructor-led course focuses on building and productionizing enterprise-grade AI agents using Google Cloud’s Agentic Stack. Participants will reinforce their understanding of agentic architectures and explore advanced operational concepts including memory management, contextual state handling, multi-agent communication, and human-agent interaction workflows. 

The course covers the use of Agent Development Kit (ADK), session and memory services, Model Context Protocol (MCP), Agent2Agent (A2A) communication, and deployment strategies for scalable AI systems. Learners will also explore designing user-centric AI applications with secure human-agent interaction models. 

Through guided labs and real-world implementation scenarios, participants will gain practical experience building production-ready AI agents capable of interacting with tools, external services, remote agents, and end users on Google Cloud.

After completing Build Production-Ready Agents on Google Cloud, participants will be able to:

  • Reinforce understanding of Google’s Agentic Stack
  • Build production-ready agents using Agent Development Kit (ADK)
  • Manage conversational state using sessions and memory services
  • Utilize example stores for contextual agent learning
  • Integrate external tools using Model Context Protocol (MCP)
  • Build and connect multi-agent systems using Agent2Agent (A2A)
  • Design scalable and collaborative agentic architectures
  • Implement secure human-agent interaction workflows
  • Build user-facing applications powered by AI agents
  • Apply enterprise best practices for production AI systems

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Key Features of Build Production-Ready Agents on Google Cloud

  • Advanced Agentic AI Development

  • Hands-On Learning Experience

  • Google Agentic Stack Deep Dive

  • Context and Memory Management

  • MCP Integration and Tool Usage

  • Multi-Agent Communication

  • Human-Agent Interaction Design

  • Google Cloud AI Ecosystem Exposure

Who should Attend Build Production-Ready Agents on Google Cloud?

  • Generative AI Developers
  • AI Engineers
  • Agentic System Architects
  • Application Developers
  • Conversational AI Developer
  • Machine Learning Engineer
  • Cloud Engineers
  • Solution Architects
  • Professionals building production-grade AI agent systems

Prerequisites of Build Production-Ready Agents on Google Cloud

  • Completion of “Deploy Multi-Agent Systems with Agent Development Kit and Agent Engine” or equivalent knowledge
  • Python programming knowledge
  • Prompt engineering fundamentals
  • Familiarity with Agent Development Kit (ADK)
  • Understanding of Generative AI and conversational AI concepts

    • Why choose CloudThat as your training partner for Build Production-Ready Agents on Google Cloud ?

    • Specialized Google Cloud AI Expertise - CloudThat specializes in cloud and Generative AI technologies, delivering industry-focused Google Cloud AI training programs with practical enterprise implementation experience.
    • Industry-Recognized Trainers - Our trainers are certified Google Cloud professionals with expertise in Vertex AI, AI agents, ADK, conversational AI, and enterprise AI application architectures. 
    • Hands-On Learning Approach - CloudThat emphasizes practical learning through guided labs, real-world AI implementation scenarios, agent orchestration workflows, and multi-agent development exercises. 
    • Customized Learning Paths - Training programs are designed for developers, AI engineers, architects, and cloud professionals with varying levels of AI and agentic system expertise.
    • Interactive and Practical Sessions - Sessions include live demonstrations, architecture discussions, implementation walkthroughs, troubleshooting exercises, and collaborative AI activities. 
    • Career and Certification Support - CloudThat supports learners with AI project guidance, interview preparation, and enterprise Generative AI implementation strategies. 
    • Updated Industry-Relevant Content - Course content is continuously updated to align with the latest advancements in AI agents, ADK, MCP, A2A communication, and enterprise AI systems.
    • Trusted by Enterprises Worldwide - Thousands of professionals and organizations trust CloudThat for advanced cloud, AI, and Generative AI training programs.   

    Learning objectives of Build Production-Ready Agents on Google Cloud

    • Understand Google’s Agentic Stack and production AI workflows
    • Build production-ready agents using Agent Development Kit (ADK)
    • Implement conversational memory and context management
    • Integrate external tools using Model Context Protocol (MCP)
    • Build collaborative multi-agent systems using Agent2Agent (A2A)
    • Design scalable and distributed AI agent architectures
    • Implement secure and effective human-agent interactions
    • Build end-user AI applications on Google Cloud
    • Apply enterprise best practices for production AI systems
    • Develop advanced conversational and agentic AI solutions 

    Course Outline of Build Production-Ready Agents on Google Cloud Download Course Outline

    Lecture Content

    • Agentic Stack Overview
    • Models and the “Brain” of the Agent
    • The Agent Development Kit (ADK)
    • Open Source Libraries and Protocols
    • Deployment Targets for Agentic Systems
    • Enterprise AI Agent Architectures

    Learning Objectives

    • Understand Google’s Agentic Stack architecture
    • Explore ADK and supporting AI frameworks
    • Identify deployment targets for agentic systems
    • Reinforce foundational concepts for production AI agents

    Lab Content

    • NA

    Lecture Content

    • Sessions: Current Conversation Context
    • Memory: Cross-Session Context
    • Example Store: Example Database
    • Context Management Workflows
    • Persistent Conversational AI Strategies

    Learning Objectives

    • Manage conversational state using sessions
    • Implement memory services for AI agents
    • Utilize example stores for contextual learning
    • Build context-aware conversational AI systems

    Lab Content

    • Lab: Building an ADK Agent with Session, Memory, and Example Services

    Lecture Content

    • MCP Fundamentals
    • Using MCP with ADK
    • MCP Tool Integration
    • MCP Server Creation
    • Extending AI Agent Capabilities

    Learning Objectives

    • Understand Model Context Protocol (MCP) concepts
    • Integrate external tools into AI agents using MCP
    • Create MCP-enabled workflows with ADK
    • Extend agent functionality using external systems

    Lab Content

    • Lab: Use Model Context Protocol (MCP) Tools with ADK Agents

    Lecture Content

    • A2A Fundamentals
    • Leveraging A2A in ADK
    • Distributed Agent Communication
    • Multi-Agent Collaboration Patterns
    • Remote Agent Connectivity Workflows

    Learning Objectives

    • Understand Agent2Agent (A2A) communication principles
    • Build collaborative multi-agent systems
    • Connect remote agents using A2A SDK
    • Design scalable distributed agent architectures

    Lab Content

    • Lab: Connect to Remote Agents with ADK and the A2A SDK

    Lecture Content

    • Communicating with Agents
    • Access Control and Security
    • Building Client Experiences
    • Human-Agent Interaction Design Principles
    • User Experience Best Practices for AI Applications

    Learning Objectives

    • Design effective human-agent interaction workflows
    • Implement secure access control mechanisms
    • Build user-facing interfaces for AI agents
    • Create scalable and user-centric AI experiences

    Lab Content

    • Lab: Implementing End-User Interfaces for Agents on Google Cloud

    Certification Details of Build Production-Ready Agents on Google Cloud

      CloudThat Course Completion Certificate

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    Course ID: 28717

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    FAQs for Build Production-Ready Agents on Google Cloud

    This course is designed for Generative AI developers, AI engineers, and professionals building production-ready agentic applications on Google Cloud.

    The course covers Agentic Stack, ADK, MCP, A2A communication, conversational memory, human-agent interaction, and production AI workflows.

    Yes, Python programming knowledge is recommended.

    The course duration is approximately 1 day instructor-led training.

    Yes, the course includes practical labs focused on ADK, MCP, A2A, and human-agent interaction workflows.

    MCP is a protocol that enables AI agents to integrate and interact with external tools and systems.

    A2A enables communication and collaboration between multiple AI agents within distributed agentic systems.

    Yes, the course covers communication patterns, access control, and user interface design for AI agents.

    The course includes Vertex AI, Vertex AI Agent Engine, Gemini Enterprise, and Agent Development Kit (ADK).

    Yes, this is an advanced-level course intended for professionals familiar with AI agents, ADK, and Generative AI concepts.

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