3 hours EN / DE Max 50

Agent Observability on Google Cloud

This course provides an applied, intermediate guide to operationalizing AI agents, focusing specifically on achieving production confidence and cost predictability for Gemini-powered workflows on Google Cloud. Participants will learn the methodology and actionable skills necessary to transform non-deterministic agent logic into transparent, auditable, and scalable systems.The course covers core operational disciplines, including mapping the agent's complex thought process (ReAct loops) to Cloud Trace Spans for debugging, implementing Logs-Based Security Metrics for compliance, and setting up actionable alerts and custom dashboards in Cloud Monitoring to proactively control cost overruns and quality drift. The course uses presentations, Visual Walkthroughs, and strategic discussions to ensure effective learning that is directly applicable to the Vertex AI ecosystem

€295,00 excl. VAT

Individual scheduling

The courses are held as dedicated group sessions. Once you've booked, we'll coordinate a date that works for your team and send invitations to all participants.

Prerequisites

Mandatory Foundational Knowledge

  • Familiarity with foundational Machine Learning (ML) concepts, specifically the distinction between models and agents.
  • Experience with Google Cloud services and basic navigation of the Google Cloud console.
  • Familiarity with software development principles and lifecycles (DevOps/MLOps).

Highly Beneficial (Recommended)

  • Experience with the Google Cloud CLI and Vertex AI services.
  • Basic understanding of Git/version control for deploying code.
  • Familiarity with structuring logs (e.g., JSON) and setting up basic monitoring alerts.

What you'll learn

  • Trace non-deterministic agent logic using Cloud Trace Spans and the ReAct loop.
  • Implement cost and quality controls through custom Cloud Monitoring dashboards.
  • Establish a continuous quality loop utilizing Golden Test Cases.
  • Implement governance and auditability using Logs-Based Security Metrics.
  • Align technical observability metrics with Business KPIs such as Cost and ROI.

Course modules
The Agent Observability Mandate. Tracing the Agent Engine Workflow. Establishing the Immutable Audit Trail.
Implementing Real-Time Metrics. Designing Actionable Alerting Policies. Evaluation for Continuous Improvement through Golden Test Cases.
Proactive Observability for Audit and Security (PII compliance). Scaling Agent Development and Deployment trade-offs. Scaling the Observable Enterprise and aligning technical metrics with Business KPIs.
Review of Core Concepts via scenario-based questions.
Agent Observability on Google Cloud