Cloud Cost Optimization for Enterprises: How to Reduce Cloud Costs

Is your cloud bill climbing even after right-sizing, reserved instances, and FinOps tooling? A personalized infrastructure strategy assessment can help you identify opportunities for optimization. Learn more here: https://eqix.it/3S84Pvv Cloud cost optimization for enterprises goes beyond compute. While FinOps can help control traditional sources of cloud spend, egress cost and data movement, geography and connectivity can create significant costs that are harder to track. This video explores practical approaches to reduce cloud costs by optimizing where data lives, how it moves between environments, and how connectivity is designed for different workloads. It also looks at how a more flexible infrastructure strategy can help enterprises reduce data movement fees, maintain cloud optionality, and optimize infrastructure TCO across hybrid environments. Equinix customers using this approach have reduced data movement fees by up to 75%, while Outseer saved up to $500,000 annually by changing how its data moved. FAQs: Q: What is FinOps and how does it relate to cloud cost optimization? A: FinOps brings cost accountability into cloud operations. In this video, the starting point is compute optimization through practices such as right-sizing, reserved instances, shutting off unused resources, mandatory tagging, and team-level budget accountability. From there, cloud cost optimization needs to consider data movement and infrastructure architecture too. Q: How can you reduce cloud costs beyond compute optimization? A: Look at how and where your data moves. Data transfers between regions, availability zones, clouds, and certain services can create significant cloud egress fees. Anchoring data close to the clouds and workloads that consume it can help reduce unnecessary movement. Q: Why is data movement an important part of cloud cost optimization? A: Data movement can become difficult to track because charges may be distributed across many individual workloads and services. For data-intensive applications, including AI workloads, data movement costs can even exceed compute costs. Q: How does FinOps for AI infrastructure spend change the equation? A: AI workloads can involve large data assets, real-time data feeds, inference, encoding, and training pipelines. As a result, managing AI infrastructure costs requires looking at data movement and placement alongside compute and GPU costs. Q: How should enterprises approach infrastructure TCO in a hybrid cloud environment? A: Infrastructure TCO should account for more than compute. Data movement, geography, replication, connectivity, and the cost of moving data between environments can all affect the economics of a hybrid cloud strategy. Q: What are some cloud cost governance best practices? A: Start with mandatory tagging and genuine cost accountability at the team or workload level. Once compute costs are under control, extend that discipline to data placement, movement, and connectivity so teams understand the broader infrastructure costs of their workloads. Chapters: 0:00 — Why cloud bills keep climbing 0:22 — Compute costs and FinOps fundamentals 1:19 — The surprise cost of data movement 3:32 — How to control data movement costs 4:30 — The benefits of anchoring your data 6:41 — Outseer: $500K in annual savings 7:21 — Match connectivity to the workload 8:20 — Optimize geography, not just the bill Explore more strategies for optimizing your hybrid cloud infrastructure: https://youtu.be/FRb8PZcvpKo https://youtu.be/Z3yiyQm13k0 About Equinix: Equinix, Inc. (Nasdaq: EQIX) shortens the path to boundless connectivity anywhere in the world. Its digital infrastructure, data center footprint and interconnected ecosystems empower innovations that enhance our work, life and planet. Equinix connects economies, countries, organizations and communities, delivering seamless digital experiences and cutting-edge AI—quickly, efficiently and everywhere. 6338