Technical Foundations of FinOps on Google Cloud Training

This two-day intermediate course dives into the technical underpinnings of FinOps, equipping participants with the expertise to optimise cloud spending and drive business value. Through hands-on exercises, labs, and case studies, learners will explore proven strategies, tools, and frameworks to master cloud financial management with Google Cloud.

Target audience

This course is designed for cloud architects, engineers, and technical professionals responsible for cloud cost management and financial governance.

Knowledge of Google Cloud infrastructure as covered in the 'Google Cloud Fundamentals: Core Infrastructure' course.

By the end of this course, participants will be able to:

• Understand the core principles of FinOps and its role in bridging technology and finance in the cloud.
• Identify cost inefficiencies and optimise resource utilisation for significant savings.
• Leverage monitoring tools and data-driven insights to forecast costs and make informed decisions.
• Implement cost allocation models to attribute cloud expenses accurately.
• Utilise Infrastructure as Code (IaC) for automating cost management processes.
• Gain visibility into cloud spending through industry-leading tools and platforms.
• Apply FinOps strategies to real-world scenarios using hands-on exercises and case studies.
• Foster a culture of cost awareness and accountability within an organisation.

Module one: Foundations of FinOps on Google Cloud

• Financial governance challenges.
• The Google Cloud FinOps framework.
• Cloud FinOps operating model.
• The three phases and five pillars of the Google FinOps journey.

Module two: Exploring and understanding billing data

• Google Cloud Billing accounts and dashboard.
• Billing export to BigQuery.
• Visualising costs using Looker Studio.
• Labs: Exploring the Billing Dashboard and Visualising Costs.

Module three: Resource labelling and tagging

• Labels and tags for cloud resources.
• Accessing and analysing label and tag data in billing.
• Labs: Tagging Resources and Examining Labels in BigQuery.

Module four: Budgets and alerting

• Creating budgets and setting alerts.
• Automating budget creation using tools like gcloud, Python, and Terraform.
• Demo: Automating budget creation with Terraform.

Module five: BigQuery cost management and optimisation

• Compute and storage cost concerns.
• Allocating and managing BigQuery costs effectively.
• Lab: Analysing BigQuery Costs Across Projects and Organisations.

Module six: Compute and GKE cost management

• Identifying and reducing compute waste.
• Managing costs for Compute Engine and Kubernetes.
• Labs: Reviewing Compute Billing and Kubernetes Costs.

Module seven: Cloud storage and database cost management

• Optimising costs for Cloud Storage.
• Managing SQL and NoSQL database costs, including Spanner, Bigtable, and Firestore.
• Lab: Managing Cloud Storage and Database Costs.

Module eight: Machine learning and Vertex AI cost management

• Monitoring costs for machine learning models and generative AI usage.
• Lab: Reviewing Vertex AI Costs in Billing Data.

Module nine: Automating billing activities

• Automating resource management and responding to budget alerts programmatically.
• Leveraging the Cloud Asset Inventory service and Google FinOps Hub.
• Labs: Automating Tagging and Programming Budget Alert Actions.

Module ten: Building a FinOps practice

• Establishing a FinOps team and roadmap.
• Defining goals, milestones, and success metrics.
• Continuous improvement and evolution of FinOps.
• Lab: FinOps Challenge Lab.