Cloud computing offers a great amount of flexibility, but with great scalability comes great potential for bill shock. As workloads multiply and teams spin up new resources, the cloud bill begins to resemble a mystery. To avoid this, you need cloud cost analysis as part of your workflow.
In this guide, we’ll walk you through the essential steps, best practices, and top tools for cloud cost analysis. Let’s begin.
What is cloud cost analysis?
Cloud cost analysis is how you figure out exactly where your cloud budget is going and whether you’re getting the most bang for your buck.
The process breaks down what you’re paying for, from storage to compute power, and seeing if those resources are actually being used efficiently.
In other words, in cloud cost analysis, you’re tracking your cloud expenses down to the resource level.
That includes monitoring usage, dissecting billing reports, and spotting trends like sudden spikes in expenses or services that are costing way more than they should.
Why is cloud cost analysis important?
Cloud cost analysis is important because ignoring it is the fastest way to light your budget on fire. One of its biggest benefits is catching waste before it drains your budget.
Unused instances, overprovisioned resources, and forgotten test environments can all add up fast. But a solid cloud cost model helps you spot and eliminate them.
Beyond just saving money, this analysis gives you full transparency into who’s spending what. By mapping costs to specific teams or projects, you can hold people accountable and make smarter budgeting decisions.
Most importantly, cloud cost analysis keeps your spending aligned with business goals. Knowing where every dollar goes ensures your cloud investments actually drive growth. And since cloud pricing is always changing, regular check-ins mean you stay ahead of surprises instead of scrambling when the bill arrives.
Cloud cost analysis vs. cloud cost optimization
A lot of teams blur the lines between cloud cost analysis and cloud cost optimization. But in practice, they play separate, though codependent, roles.
Cloud cost analysis is the observation deck where you monitor:
- Your cloud consumption cost
- Trace the usage patterns
- And highlight the services or workloads that are silently draining your budget
There’s no actual intervention yet, just insights.
Cloud cost optimization, on the other hand, is the action plan. It takes those insights from the analysis phase and uses them to:
- reduce waste
- Implement more efficient provisioning
- And align resource allocation with real needs
This might mean rightsizing instances, adjusting storage tiers, or adopting different cloud costing models altogether.
In essence, cloud cost analysis tells you what’s wrong (or at least, what’s inefficient), and optimization focuses on how to fix it.
Understanding the components of a cloud cost analysis
A reliable cloud cost assessment framework takes a granular look at every element that drives cost and matches each one to specific consumption behaviors. While the details vary by provider, the core categories remain fairly consistent.
Infrastructure cost
The largest contributor to cloud spend Infrastructure costs stem from compute services, like:
- Virtual machines
- Containers
- Orchestration platforms
- And serverless functions
These are billed based on real-time usage metrics such as vCPU hours, memory allocation, and IOPS. These costs fluctuate depending on provisioning strategies.
Data transfer cost
Transferring data across services, regions, or hybrid environments comes at a price. Cloud providers charge based on the volume of data, where it’s going, and what type of service is doing the transferring.
Moving data between availability zones, pulling it out of the cloud, or syncing with external systems can all generate charges that aren’t immediately obvious.
Licensing cost
Licensing costs cover software products and third-party tools running in your cloud environment. Depending on the licensing model, you might be billed by the hour, by user count, or by resource utilization.
Storage cost
Storage is deceptively cheap until it’s not. Object storage, block storage, and archival each has a different pricing model based on:
- Size
- Redundancy
- Access patterns
- And geographic region
Additional services cost
Additional service costs come from managed services, advanced features, and basically anything outside basic compute and storage.
Now, what does it include, you might ask? It includes:
- Serverless functions
- Backup services
- Database-as-a-service
- Machine learning pipelines
- And any analytics workloads
You’ll also see charges related to security and compliance features, such as data encryption, firewall policies, and regulatory audits.
What is the cost model of the cloud?
The cloud follows a usage-based pricing approach. You only pay for what you consume, whether that’s compute power, storage, bandwidth, or higher-level managed services.
This model eliminates upfront capital expenditure but introduces the need for vigilant monitoring, since costs can scale up just as fast as your workloads.
But what are the cloud cost models? They include:
- On-demand pricing: No commitments. Pay per hour or second, ideal for short-term or unpredictable workloads.
- Commitment-based discounts (e.g., Reserved Instances, Savings Plans, etc.): Commit to a specific usage level over a 1- or 3-year term for significant discounts.
- Spot instances: Purchase unused capacity at a deep discount, great for flexible, interruptible tasks like batch jobs.
- Tiered pricing and region-based variability: Prices differ depending on data center region, storage tier (standard, infrequent access, archive), and data transfer volumes.
Best practices for cloud cost analysis
These best practices will help you turn your cloud cost analysis from a reactive task into a proactive advantage.
- Decode the cloud bill maze: Your cloud bill is a mesh of SKUs, usage metrics, and fine-print footnotes. Learning to interpret its structure, like usage duration, resource IDs, and charge rates, gives you the visibility you need to trim waste without accidentally snipping critical services.
- Focus on value, not just cost: Align costs with business impact. Ask which workloads matter most to customers and whether you’re delivering them at an efficient unit cost.
- Tag like a pro: Tagging resources by project, department, or environment achieves transparency. It allows for cleaner reporting, tighter accountability, and smarter showback/chargeback.
- Set lights on / lights off policies: Why pay for cloud instances to nap overnight? Schedule them to power down when not in use. Weekends, non-business hours, and development environments are prime targets for automated shutdowns.
- Keep data transfers in check: Data egress charges can sneak up on you. Minimize cross-region transfers, lean on CDNs, and keep services as geographically close as possible to users.
- Use spot instances wisely: Use spot instances for fault-tolerant jobs like data crunching or background processing. When used right, they can slash compute costs dramatically.
How to calculate cloud costs?
Here’s how to calculate cloud computing costs.
- Audit the old setup: Capture every cost in your current infrastructure, from hardware and licenses to staffing and support overhead.
- Map out your cloud blueprint: Estimate your cloud needs, pick the right pricing model, and use provider calculators to forecast expected spend.
- Account for the hidden costs: Don’t forget the extras: team training, security measures, compliance, and data migration expenses.
- Break down the bill, then break it down more: Take a close look into your cloud bill to spot inefficiencies, idle resources, and missed savings opportunities like discounts or rightsizing.
- Do the cloud vs. on-premises math: Compare total cost of ownership for cloud and on-premises setups—short-term vs. long-term value, scalability, and agility.
Performing a cost-benefit analysis
When cloud adoption is on the table or under review, you need more than assumptions. A cloud computing cost-benefit analysis provides a structured framework to determine whether the benefits of moving to or continuing in the cloud justify the associated costs.
Here’s how to approach it:
Step 1
Begin by clearly stating what you’re analyzing (a single workload migration, a full infrastructure shift, or a hybrid implementation) and outline what outcomes you’re aiming for.
Step 2
Identify costs and benefits:
- Direct costs: Include expenses such as cloud compute, storage, licensing, managed services, and third-party tools.
- Indirect costs: Don’t ignore costs for staff training, potential downtime during migration, compliance efforts, and added security requirements.
- Tangible benefits: These are measurable gains like reduced capital expenditure, lower operational overhead, improved uptime, and elasticity in scaling.
- Intangible benefits: These include faster deployment cycles, improved disaster recovery posture, and operational agility.
Step 3
Estimate the financial impact of both costs and benefits over a defined period, typically three to five years, to allow for ROI calculations.
Step 4
Use standard financial metrics like Net Present Value (NPV), Return on Investment (ROI), and Benefit-Cost Ratio (BCR) to assess whether the investment makes sense.
Step 5
If the benefits, both hard and soft, outweigh the projected cloud expenses, the move may be justified. If not, consider hybrid models or optimization before full transition.
How to analyze cloud costs: A step-by-step guide
Now that you have understood what drives cloud expenses, the next step would be to develop an approach to analyze them. Here are some of the steps you can follow to analyze cloud costs at your workplace.
Step 1: Collect clean, complete cloud data
Everything starts with data. To kick off a meaningful cloud cost analysis, collect detailed usage and billing data from your cloud provider’s dashboard.
Most platforms like AWS, Azure, and Google Cloud offer native tools that export this information down to the resource level.
You’ll be looking for things like instance types, service identifiers, consumption metrics, region usage, and associated costs.
Step 2: Segment, visualize, and investigate
Once the data is in place, analysis begins.
- Organize your data into logical segments: by department, project, business unit, or environment (dev, staging, prod).
- Look at how usage fluctuates over time.
- Compare forecasted costs to actuals.
- Identify which services are trending upward and which ones spike unexpectedly.
Visualization tools like dashboards, graphs, and heat maps can help make sense of this data. They help identify anomalies and patterns you’d miss in a CSV file.
Step 3: Spot wasteful cloud behavior
With your analysis in full swing, spotting inefficiencies becomes easier. Maybe you have instances running 24/7 that only need to be active during business hours. Or perhaps someone spun up a test environment six months ago and never shut it down. And maybe storage buckets are holding log files that no one ever reads.
Whatever the case, this is where cloud cost analysis starts paying off.
Step 4: Optimize for efficiency and value
What to do about the identified waste now? You optimize.
Some optimization strategies include:
- Reallocating resources
- Rightsizing workloads
- Automating processes to improve efficiency
- Switching to reserved or spot instances
- Implementing auto-scaling policies
- Transitioning from high-performance storage to a more cost-effective tier
Cloud costing models also come into play here. You may find that your current approach (say, entirely on-demand) doesn’t align with your usage profile. Adjusting your cloud cost model to better match real demand can yield major cloud cost savings over time.
Step 5: Communicate findings that drive change
Reporting should be clear, structured, and tailored to the audience.
For example:
- The IT team might want technical details
- The finance department will care more about budget impact
- Executives will want high-level trends and recommendations
Effective communication of cloud computing cost analysis outcomes helps secure buy-in for proposed changes. It also reinforces accountability across teams and promotes ongoing cost awareness, something that’s essential for maintaining long-term efficiency.
Getting started: Tools for cloud cost analysis
The leading cloud providers offer billing consoles and cost management tools out-of-the-box. These are often referred to as native tools. Native tools are the most common way to get started with cloud cost analysis.
Below is a breakdown of tools that take the guesswork out of tracking and visualizing cloud costs.
| Tool | Description | Key benefit |
|---|---|---|
| AWS Cost Explorer | Native AWS tool for visualizing and managing cloud costs. | Provides a detailed view into AWS spending, making it easier to forecast, budget, and cut unnecessary costs. |
| Google Cloud cost management | A suite of tools for tracking and optimizing spend on Google Cloud. | Helps teams gain visibility into spending, set proactive budgets, and capitalize on discounts tailored to actual usage patterns. |
| Microsoft Cost Management | A native cloud cost management tool for Azure users. | Allows Azure users to track and manage costs efficiently, with built-in optimization insights. |
| Ternary | A leading multi-cloud cost optimization platform built with FinOps in mind. | Dramatically reduces manual effort and increases accuracy in cloud cost analysis. Ternary empowers finance and technical teams to stay aligned on budget and margin goals. |
If you are just getting started on your cloud journey and are operating primarily in a single cloud, native tools can meet your needs. Companies that require greater customization and flexibility, have moderate to advanced cost use cases, and/or want to manage spend across their multi-cloud and containerized environments should explore third-party platforms.
Analyze cloud costs with Ternary
Now that you’ve explored everything about cloud cost analysis, it’s time to take action.
Ternary takes everything you’ve just learned and makes it actually usable. With billions of dollars in managed cloud spend and recommendations that are tailored to your business goals, Ternary regularly helps teams save an average of 30%. And because our platform tracks your spend across timeframes and teams, it helps you scale smarter.
Our cloud infrastructure costs were 17% of non-GAAP revenue. We reduced that down to 8% of non-GAAP revenue with Ternary
Jamie Tischart, CTO, BetterCloud
Ready to rein in your cloud bill before it becomes a financial black hole?
