FinOps in Practice — How to Manage Cloud Costs in 2026

The average Czech company spends 30–40% more in the cloud than necessary. FinOps is not just about cutting costs — it’s a cultural change that connects engineering, finance, and business. Here’s how in 2026.

What Is FinOps and Why You Need It¶

FinOps (Cloud Financial Operations) is an operational framework that brings financial accountability to cloud operations. It connects three worlds: engineering teams understand technology, finance understands budgets, business understands value. FinOps is the bridge between them.

In 2026, FinOps is more relevant than ever. With the advent of AI workloads — model training, inference, GPU instances — cloud costs are exploding. Companies without FinOps practices often discover the problem only on the invoice.

Three Pillars of the FinOps Framework¶

The FinOps Foundation defines three cyclically repeating phases:

• Inform (Visibility): Who spends how much on what? Tagging strategy, cost allocation, dashboards. Without visibility, you can’t optimize.
• Optimize: Rightsizing, reserved instances, spot/preemptible instances, storage tiering, idle resource cleanup.
• Operate (Governance): Budgets, alerting, policy enforcement, showback/chargeback models. Continuous improvement.

Quick Wins — Savings in 30 Days¶

Most companies have low-hanging fruit that delivers 15–25% savings with zero performance impact:

• Shutting down idle resources: Dev/test environments running 24/7, unused load balancers, orphaned disks. Automatic scan via Azure Advisor or AWS Trusted Advisor.
• Rightsizing: Instances sized “just in case” at double the needed capacity. CPU/RAM utilization analysis over the last 30 days reveals overprovisioned instances.
• Storage tiering: Data in hot storage that nobody has accessed in months. Automatic lifecycle management moves data to cool/archive tiers.
• Reserved Instances / Savings Plans: For stable workloads, they deliver 30–60% savings over on-demand prices. Requires a 1–3 year commitment.

AI Workloads — A New FinOps Challenge¶

GPU instances for AI are orders of magnitude more expensive than regular compute. A single A100 instance on Azure costs over $3/hr, H100 even more. Without controls, it escalates fast.

Specific strategies for AI workloads:

• Spot instances for training: With checkpointing, you can train on spot instances at a 60–90% discount. Requires a fault-tolerant training framework.
• Inference optimization: Batching, model quantization (INT8/INT4), model distillation — reduces required compute by 50–80%.
• Auto-scaling inference: Scale-to-zero for low-traffic inference endpoints. Serverless inference (Azure ML, SageMaker) is pay-per-request.
• Model caching: Semantic caching of responses — if a similar query has already been answered, the cached response is returned without calling the model.

Tagging — The Foundation of Cost Allocation¶

Without consistent tagging, you can’t assign costs to teams, projects, or products. Recommended minimum tag set:

• cost-center: Cost center (finance)
• team: Responsible team
• environment: dev / staging / production
• project: Project or product
• managed-by: terraform / manual / helm

Enforcement: Azure Policy / AWS SCP blocks resource creation without required tags. No exceptions. Compliance checks in the CI/CD pipeline ensure IaC code also contains tags.

Tools and Automation¶

In 2026, we have a rich FinOps tool ecosystem:

• Native tools: Azure Cost Management, AWS Cost Explorer, GCP Billing — a good start, free.
• Multi-cloud platforms: Kubecost (Kubernetes-native), OpenCost (open-source), Vantage, CloudHealth — for companies with multi-cloud strategy.
• Automation: Terraform + Infracost (cost estimation in PR review), Spot.io (automatic spot management), Karpenter (Kubernetes node autoscaling).

The key is to integrate cost feedback into the developer workflow. When a developer sees the cost impact of their PR before merge, they naturally optimize.

Cultural Change — The Hardest Part¶

Technical optimizations are easy. The real challenge is cultural change:

• Decentralized responsibility: Each team “owns” their cloud costs. Showback reports instead of central IT billing.
• Engineering KPIs: Add cost-per-transaction or unit economics to team dashboards alongside latency and error rate.
• Gamification: Monthly FinOps challenge — which team achieves the biggest optimization? Celebrate successes publicly.
• FinOps champion: One person on each team who monitors trends and proposes optimizations. Doesn’t have to be a full-time role.

Measuring Success¶

How do you know FinOps is working? Track these metrics:

• Unit cost: Cost per transaction / user / API call — decreases with efficiency gains
• Coverage: Percentage of workloads covered by reservations / savings plans
• Waste ratio: Percentage of idle or unoptimized resources
• Forecast accuracy: How accurately you predict monthly spend
• Tag compliance: Percentage of resources with complete tags

FinOps Is a Marathon, Not a Sprint¶

Cloud costs never stop growing — they grow with the business. The goal of FinOps isn’t absolute minimization but maximizing value for every crown spent. Start with visibility, continue with quick wins, build a culture of accountability.

Our tip: Do a FinOps assessment — a 2-week analysis of current cloud spending with specific recommendations. It typically reveals 20–35% potential savings.