Top 5 Multi-Cloud FinOps Challenges and How to Solve Them

You already know what FinOps is, a practice that brings finance and engineering together to make cloud spending smarter, more accountable, and more efficient.

But just like a stomach ache, cloud cost pain can come from many causes. Sometimes it’s from overeating (over-provisioning resources), sometimes skipping meals (under-utilizing commitments), and sometimes just bad digestion (poor tagging or visibility). And just like you can’t fix all types of stomach pain with one pill, you can’t solve all FinOps challenges with one tool or process.

Every organization feels the “pain” differently, depending on its cloud setup, team structure, and maturity. In this post, let’s break down the five biggest Multi-Cloud FinOps challenges and how to treat each one with the right solution.

1. Fragmented Cost Data and Reporting

The Challenge: Each cloud provider exports billing data in its own format. AWS uses the Cost & Usage Report, Azure has Cost Management exports, and GCP relies on BigQuery billing exports. These datasets vary in structure, granularity, and terminology, making it difficult to get a unified view of total spend.

Solution: Use a centralized cost data platform that aggregates, normalizes, and enriches billing data across providers. Apply a consistent schema to standardize attributes like usage type, environment, and project. Tools such as BigQuery, ClickHouse, or FinOps platforms like Opslyft, ProsperOps, or CloudHealth can automate this normalization.

When to Solve: When you’re operating across multiple clouds and leadership teams (finance, engineering, product) are struggling to get a single, accurate source of truth for spend.

Impact if Ignored: Without unified reporting, budgets go off track, forecasts become unreliable, and cost visibility breaks down, resulting in double counting, missed optimizations, and financial blind spots.

2. Inconsistent Pricing and Discount Models

The Challenge: Each cloud has its own discount structures, AWS with Reserved Instances and Savings Plans, Azure with Reservations and hybrid benefits, and GCP with Committed Use Discounts. None of them is interchangeable, and managing them separately leads to inefficiencies.

Solution: Implement automated commitment management across all providers. Platforms like ProsperOps or Opslyft dynamically adjust commitments in real time based on actual usage to maximize your Effective Savings Rate (ESR) and prevent overcommitment.

When to Solve: When your usage fluctuates across providers or you’re managing large annual commitments and need to ensure optimal coverage without manual tracking.

Impact if Ignored: You risk overcommitting in one platform and underutilizing in another, wasting savings opportunities, locking into bad deals, and driving up total cloud costs despite having “discounts” in place

3. Disjointed Tagging and Cost Allocation

The Challenge: AWS uses tags, Azure adds cost categories, and GCP uses labels — all with different formats and limitations. This inconsistency makes it difficult to allocate costs accurately to teams, projects, or products.

Solution: Create a unified tagging and labeling framework across clouds. Define a standard schema (like env, team, product, cost_center) and enforce it automatically using Infrastructure as Code tools (Terraform, Pulumi) and policy engines (OPA, Cloud Custodian).

When to Solve: When costs can’t be accurately attributed to business units or when finance teams rely on manual spreadsheets to track ownership and accountability.

Impact if Ignored: You’ll lose traceability. Costs become opaque, accountability disappears, and wasted resources hide under untagged or mis-tagged assets.

4. Lack of Centralized Ownership and Collaboration

The Challenge: In many companies, cloud responsibilities are divided: engineering runs workloads, finance manages budgets, and no one owns the shared outcome. This siloed approach keeps FinOps reactive instead of strategic.

Solution: Adopt a hybrid FinOps operating model, central governance for strategy, decentralized execution for speed. Let a central FinOps team set policies, tools, and KPIs, while individual platform teams drive day-to-day optimizations.

When to Solve: When multiple departments use different clouds or when your cost reviews feel more like post-mortems than proactive planning.

Impact if Ignored: Silos deepen, accountability fades, and FinOps maturity stalls. You’ll continue firefighting budget overruns instead of preventing them.

5. Limited Automation Across Clouds

The Challenge: Automation scripts for idle resource cleanup, scaling, or tagging enforcement are often built separately for each cloud. As environments scale, maintaining them becomes unmanageable.

Solution: Use cross-cloud automation platforms that enforce policies and optimize usage continuously, for example, Opslyft, ProsperOps, or CloudZero. These systems rightsize resources, manage commitments, and schedule workloads automatically, freeing teams to focus on innovation.

When to Solve: When your FinOps team spends more time reconciling data or writing scripts than actually optimizing costs.

Impact if Ignored: You’ll accumulate invisible waste, idle resources, over-provisioned storage, and missed discounts, quietly draining your budget every month.

Conclusion

Multi-Cloud FinOps isn’t about doing FinOps everywhere; it’s about doing it smarter, consistently, and automatically across every cloud. When you standardize data, automate decisions, and align teams around shared accountability, cost management evolves from a reactive process to a continuous, intelligent system.

In the end, success in multi-cloud FinOps isn’t about chasing discounts; it’s about creating a culture where every dollar in the cloud is spent with purpose.