🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
GCPSPARKSOPSAIAGENTS

Operationalizing AI Agents on Google Cloud Training

This course equips technical professionals and cloud architects with the specialized skills needed to deploy, manage, and optimize autonomous AI agents at scale within an enterprise environment. It covers the core taxonomy and operational lifecycle of agentic AI, multi-agent design patterns, enterprise governance and security frameworks, and advanced full-stack evaluation metrics. Participants will learn how to leverage Google Cloud services, such as the Gemini Enterprise Agent Platform, Google Kubernetes Engine (GKE) Autopilot, and Spanner Graph, to construct secure, scalable, and cost-effective autonomous multi-agent systems that drive business value while mitigating operational, identity, and economic risks.

Google Cloud
✓ Official training Google CloudLevel Advanced⏱️ 0.5 day (3h)

What you will learn

  • Analyze an organization's operational landscape and determine its current position on the 5-level AI autonomy maturity model.
  • Design scalable multi-agent architectures using design patterns.
  • Apply the 12 non-negotiable governance capabilities for autonomous systems to mitigate autonomous risk.
  • Evaluate agent performance using multi-step trajectory metrics and formulate a FinOps optimization strategy.

Prerequisites

  • Familiarity with Google Cloud core services, AI foundational concepts, and standard model application programming interfaces (APIs).

Target audience

  • Solutions architects, lead AI engineers, and technology leaders with technical knowledge of cloud infrastructure who plan to build, scale, and govern autonomous multi-agent fleets within an enterprise setting.

Training Program

5 modules to master the fundamentals

Objectives
  • Explain the components and core definitions of AI agents
  • Evaluate organizational readiness using the AI autonomy maturity model
  • Select the appropriate Google Cloud platform for agent deployment based on architecture requirements.
Topics covered
  • →The agentic imperative
  • →AI agent taxonomy
  • →Agentic scaling challenges
  • →Identifying agentic use cases
  • →Introducing GCP products for operationalizing agents
Activities

1x reflection

Objectives
  • Design multi-agent architectures using industry design patterns
  • Prevent infinite loops during reasoning execution
  • Integrate models with external tools via standard protocols
  • Build robust long-term memory structures for enterprise data grounding
Topics covered
  • →Multi-agent design patterns
  • →Interoperability standards
  • →Grounding and memory
  • →Agentic AI operational cycle
Activities

1x discussion

Objectives
  • Implement policy-as-code and tool governance across agent fleets
  • Select platform-level security barriers to prevent data exfiltration or malicious injection
  • Construct clear escalation matrices defining boundaries for autonomous actions vs. human verification
Topics covered
  • →Agentic AI governance gap
  • →Agentic AI governance strategy
  • →Security architecture on GCP
  • →The human-agent control mandate
  • →AI CoE and AI review committees
Activities

1x discussion

Objectives
  • Formulate an evaluation strategy to measure reasoning coherence and tool use success
  • Execute production-scale agent monitoring using pre-defined trajectory metrics
  • Establish cost-control optimization guardrails to maximize token efficiency and business value delivery
Topics covered
  • →Agent evaluation
  • →FinOps for Agentic AI
  • →Practical implementation roadmap
  • →5 phases of the production-ready operational cycle
  • →Industry example: Marketing
Objectives
  • Reinforce topics learned during the Spark
Topics covered
  • →Course recap
  • →Q&A session
  • →MCQ quiz
Activities

1x quiz (4 MCQs)

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Upcoming sessions

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We regularly organize new sessions. Contact us to find out about upcoming dates or to schedule a session at a date of your choice.

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Quality Process

SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach

Teaching Methods Used
  • Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
  • Group Discussion — Open exchange among peers and the instructor on a specific topic.
  • Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
Evaluation and Monitoring System

The achievement of training objectives is evaluated at multiple levels to ensure quality:

  • Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
  • Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
  • Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.

Frequently Asked Questions

Solutions architects, lead AI engineers and technology leaders with technical knowledge of cloud infrastructure who plan to build, scale and govern autonomous multi-agent fleets in an enterprise setting.
Familiarity with Google Cloud core services, AI foundational concepts, and standard model application programming interfaces (APIs).
You will determine an organization's position on the 5-level AI autonomy maturity model, design scalable multi-agent architectures using design patterns, apply the 12 non-negotiable governance capabilities for autonomous systems, and evaluate agent performance with multi-step trajectory metrics to formulate a FinOps optimization strategy.
Yes. A module is dedicated to governance, security and runtimes: the agentic AI governance gap, the governance strategy and the security architecture on Google Cloud.
The course lasts 3 hours and is delivered in an instructor-led format by SFEIR Institute. It includes a reflection, group discussions and a final quiz.
Yes. This is an official Google Cloud Sparks course delivered by SFEIR Institute, a certified Google Cloud Training Partner.

395€ excl. VAT

per learner

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