Understanding Cloud FinOps Unit Economics

TL/DR

Cloud FinOps unit economics focuses on understanding and optimizing cloud costs at a granular level to align with business outcomes, such as cost per customer, feature, or transaction. Starting from foundational visibility (crawling), organizations progress to advanced practices (walking) and eventually achieve continuous optimization (running). However, challenges like untaggable costs, limited granularity in native tools, and shared service cost allocation require modern FinOps strategies beyond legacy CMPs and native cloud tools.

1. What is Cloud FinOps Unit Economics?

Cloud FinOps unit economics is the practice of analyzing the cost and value of cloud resources at a granular level, such as per customer, per feature, or per transaction. It enables organizations to align cloud spending with business outcomes by providing visibility into the true cost of delivering specific products or services.

For example:

• E-commerce: Understanding the cost of hosting a single product page.
• SaaS: Calculating the cost of serving one user or delivering one transaction.
• Streaming Services: Determining the cost per minute of streamed video.

Key metrics in cloud FinOps unit economics include:

• Cost per unit: Total cloud spend divided by the number of units delivered.
• Margin per unit: Revenue per unit minus cost per unit.
• Efficiency metrics: Cost per customer, cost per deployment, etc.

This approach supports decision-making, optimizing cloud spend, and ensuring profitability at scale.

2. How to Start from Nothing to FinOps Crawling

FinOps crawling is the foundational stage where an organization begins its cloud cost management journey. Steps include:

Step 1: Establish Basic Visibility

• Set up billing exports: Use AWS Cost and Usage Reports (CUR), Azure Cost Management, or GCP Billing Export.
• Choose a visualization tool: Start with basic tools like Excel or Google Sheets or cloud-native tools like AWS Cost Explorer.

Step 2: Categorize Costs

• Tagging: Implement a consistent tagging strategy to classify resources by environment, team, or project.
• Accounts and subscriptions: Use separate accounts for different departments or projects to simplify cost tracking.

Step 3: Create Basic Reports

• Define reports to monitor overall spend and trends.
• Focus on high-cost areas (e.g., compute, storage, and networking).

Step 4: Educate Stakeholders

• Train teams on how cloud costs are generated and their impact on business outcomes.
• Share early insights to demonstrate value.

Challenges of Untaggable Costs

One of the significant hurdles at this stage is managing costs that are not taggable within AWS, Azure, and GCP. Examples include:

• AWS: Costs associated with NAT Gateways, data transfer, and some default services.
• Azure: Marketplace purchases and shared services like Azure Monitor.
• GCP: Inter-region network traffic and some managed services like BigQuery.

These untaggable costs can create gaps in cost allocation and hinder accurate unit economic calculations. Organizations may need to rely on manual estimates or adopt third-party tools to bridge these gaps.

3. How to Move from Crawling to Walking

Once basic visibility is achieved, organizations can progress to FinOps walking by refining practices and involving more stakeholders.

Step 1: Enhance Cost Allocation

• Granular tagging: Expand tagging to include more dimensions like application, feature, or business unit.
• Shared cost allocation: Define and implement rules for allocating shared resources like databases or networking.

Step 2: Build Predictive Models

• Use historical data to create budgets and forecasts.
• Leverage cloud-native tools like AWS Budgets or Azure Cost Management for alerts.

Step 3: Automate Processes

• Automate resource tagging using scripts or tools.
• Automate rightsizing recommendations using policies and native tools (e.g., AWS Trusted Advisor).

Step 4: Involve More Stakeholders

• Establish a FinOps working group with engineering, finance, and product teams.
• Begin linking costs to business KPIs.

Challenges of Granular Cost Visibility

Native tools and legacy CMPs often struggle to provide detailed cost and metric data, such as:

• Query-level costs: Tools like BigQuery and Athena may generate high costs, but native tools lack the ability to break down spend by query.
• Fine-grained metrics: Understanding costs tied to specific microservices, requests, or endpoints can be difficult.

This limitation forces teams to rely on approximate estimates or invest in custom solutions to achieve deeper insights.

4. How to Move from Walking to Running

FinOps running is characterized by a culture of continuous optimization and strategic decision-making.

Step 1: Unit Economics Deep Dive

• Integrate cloud cost data with business data (e.g., revenue, usage metrics).
• Analyze cost drivers for individual features or customers.

Step 2: Advanced Optimization

• Spot and savings plans: Maximize usage of discounts like Spot Instances or Savings Plans.
• Proactive optimization: Predict demand and scale resources dynamically.

Step 3: Real-Time Visibility

• Use tools that provide real-time insights into cost and usage.
• Build dashboards tailored to specific teams or KPIs.

Step 4: Continuous Education and Collaboration

• Establish a culture of accountability for cloud costs.
• Regularly review and iterate on FinOps processes.

Challenges of Shared Service Cost and Usage Ownership

Shared services, such as databases, networking, or storage systems, often serve multiple teams or applications. Challenges include:

• Cost allocation: Determining which team or service is responsible for what percentage of the costs.
• Usage tracking: Identifying and tracking usage metrics for shared resources.
• Native tool limitations: AWS, Azure, and GCP lack robust features for splitting shared service costs proportionally across teams or projects.

Legacy CMPs also struggle in this area, often requiring manual input or custom configurations to approximate shared service cost ownership.

5. Limitations of AWS, Azure, and GCP Native Tools for Visibility into Unit Economics

While cloud-native tools provide foundational cost insights, they have several limitations:

AWS Cost Explorer, Azure Cost Management, GCP Billing Export

• Limited granularity: Hard to tie costs to specific features or customers.
• Inflexible reporting: Customization options are limited.
• Siloed insights: Difficult to integrate with business metrics or cross-cloud costs.
• Lag in data: Data updates may not be real-time, impacting timely decision-making.

Resource Tagging Limitations

• Inconsistent enforcement of tagging policies.
• Lack of retroactive tagging capabilities.

6. Limitations of Legacy CMPs for Visibility into Unit Economics

Legacy Cloud Management Platforms (CMPs) like Cloudability, CloudHealth, and Flexera offer broader capabilities but fall short in several ways:

1. Lack of Real-Time Insights

• Most legacy CMPs operate on batch data processing, leading to delays in actionable insights.

2. Poor Integration with Business Data

• These platforms often fail to natively integrate cloud costs with business metrics like revenue, customer acquisition costs, or feature usage.

3. Limited Customization

• Dashboards and reports may not allow deep customization for specific unit economic analysis.

4. High Cost and Complexity

• Licensing fees and implementation complexity can be barriers for smaller organizations.

5. Limited Multi-Cloud Capabilities

• Cross-cloud visibility and unified insights are often inadequate, especially for organizations leveraging multiple cloud providers.

Challenges of Granular Cost Visibility and Shared Service Costs

Legacy CMPs face additional challenges in:

• Granular cost visibility: Struggling to provide query-level cost insights or detailed metrics for microservices.
• Shared service allocation: Often requiring manual configurations to allocate shared service costs across stakeholders.

Summary

Cloud FinOps unit economics enables businesses to achieve a deeper understanding of cloud costs and their impact on profitability. Starting with foundational practices (crawling), organizations can refine and scale their FinOps practices (walking) to achieve real-time visibility and strategic decision-making (running). Challenges such as untaggable costs, limited granularity in native tools, and shared service cost allocation highlight the need for modern, purpose-built solutions. By addressing these gaps, businesses can unlock the full potential of their cloud investments while ensuring efficiency and profitability.