Conquer Cloud Costs: Your Power Guide to FinOps Terminology

Land Your Dream FinOps Job: Your Friendly Guide to Cloud Cost Mastery

Master Azure Costs with the FinOps Toolkit: Optimize, Analyze, and Save

Understanding AWS Bedrock: Basics, Pricing, and Cost Optimization
AWS structures its AI/ML offerings into three layers: infrastructure, generative AI platforms, and applications. At the foundation is the infrastructure tier, featuring hardware and Amazon SageMaker for building and deploying ML models. The middle layer, Amazon Bedrock, offers access to leading large language models (LLMs) and other foundational models, enabling businesses to scale generative AI applications efficiently. The top layer includes user-friendly applications that leverage generative AI without requiring specialized knowledge or coding.

Essential FinOps Tools: Streamlining Cloud Cost Management in the Age of AI

FinOps Foundations: Best Practices for Product Teams

Taming Cloud Costs with GCP Preemptible VMs: A Practical Guide

Mastering BigQuery Performance: The Ultimate Guide to Slot Optimization and Cost Management

Align FinOps with SaaS management within your organization

Top 14 FinOps KPIs and How to Maximize Them

Gartner Insights: Uniting SAM and FinOps to target cloud costs

Decoding FinOps Framework 2024 Updates: Implications for ITAM Professionals

Cloud computing trends: Flexera 2024 State of the Cloud Report

How FinOps and ITAM teams can work together in real-life scenarios

Proven Strategies for Cloud Cost Optimization

Uncovering hidden cloud costs: Tips for maximizing your cloud investments

How to pass your FinOps certification exam

Exploring the Differentiated Offerings of Managed Service Providers (MSPs) Using Snow Cloud Cost

Making data-driven decisions for your IT sustainability strategy

The endless cloud cost optimization loop: The phases of FinOps

Snow saves 25% of total compute Azure bill with BYOL data insights

Forrester Wave™: Flexera named as a leader in CCMO

FinOps for AI: 8 steps to managing AI costs and resources

FinOps vs. Traditional Finance: What’s the Difference?

How FinOps Drives Cost Optimization in Cloud Services

Flexera recognized as a Leader in 2024 Gartner Magic Quadrant for Cloud Financial Management Tools

The Future of FinOps: Trends to Watch

Building a Cross-Functional FinOps Team

Unlocking Business Agility: The Transformative Power of FinOps

FinOps: It’s not just for cloud anymore

Best Practices for Creating FinOps Culture

The Role of Automation in FinOps

The Importance of FinOps in Cloud Financial Management

10 Key Insights into FinOps: A Comprehensive Guide to Cloud Cost Optimization

Flexera One FinOps: Cloud Cost Optimization year in review

Conquer Cloud Costs: Your Power Guide to FinOps Terminology

Land Your Dream FinOps Job: Your Friendly Guide to Cloud Cost Mastery
Master Azure Costs with the FinOps Toolkit: Optimize, Analyze, and Save
Understanding AWS Bedrock: Basics, Pricing, and Cost Optimization
AWS structures its AI/ML offerings into three layers: infrastructure, generative AI platforms, and applications. At the foundation is the infrastructure tier, featuring hardware and Amazon SageMaker for building and deploying ML models. The middle layer, Amazon Bedrock, offers access to leading large language models (LLMs) and other foundational models, enabling businesses to scale generative AI applications efficiently. The top layer includes user-friendly applications that leverage generative AI without requiring specialized knowledge or coding.

Essential FinOps Tools: Streamlining Cloud Cost Management in the Age of AI
FinOps Foundations: Best Practices for Product Teams
Taming Cloud Costs with GCP Preemptible VMs: A Practical Guide

Mastering BigQuery Performance: The Ultimate Guide to Slot Optimization and Cost Management
Flexera One FinOps: Cloud Cost Optimization year in review

EKS Pricing Components, Examples, and 7 Ways to Cut Your Costs

Conquer Cloud Costs: Your Power Guide to FinOps Terminology

Land Your Dream FinOps Job: Your Friendly Guide to Cloud Cost Mastery
