Your cloud bill keeps rising, but managing costs doesn’t have to mean hiring a dedicated FinOps team. Here’s how you can take control of cloud expenses with simple, actionable strategies:
To get a handle on cloud costs, you need to start by understanding where your money is going. Without clear visibility, managing and controlling expenses becomes a guessing game. Cloud bills often resemble itemised receipts rather than straightforward financial reports, making it challenging to answer questions like, "What did our staging environment cost last month?" or "Which team is driving up storage expenses?"
The solution? Build cost visibility, starting with effective resource tagging.
Resource tagging is the cornerstone of cost management in the cloud. Tags are simple key-value pairs that act as digital labels for cloud resources, helping you categorise and track your infrastructure.
Making tags mandatory for every resource is critical. Start with these key categories:
prod, staging, dev, or test to differentiate production environments from development and testing. This can highlight unexpected costs in non-production environments.marketing, engineering, or product allow you to allocate costs to specific teams. This ensures monthly reports reach the right people and promotes accountability.Here’s a practical example: A multinational corporation implemented mandatory tags like CostCenter, Project, and Environment. This revealed that test environments in the marketing department were often left running long after campaigns ended. By automating the shutdown of test environments after 30 days, they cut costs significantly. Monthly cost reports sent to department heads further boosted accountability and awareness.
For consistency, embed tags directly into your infrastructure-as-code tools like Terraform, CloudFormation, or ARM templates. This ensures no resource is missed.
"AWS advise 'tag too much' over 'tag not enough', which is a sensible approach."
Regular audits are also essential. Most cloud platforms provide tools to detect resources missing required tags, and automated policies can block untagged resources from being deployed in the first place.
With tagging in place, the next step is to focus on tracking the metrics that matter most.
Once your tagging strategy is up and running, shift your attention to the metrics that can help you manage costs effectively. Start by monitoring these core indicators:
Review these metrics weekly to catch problems early without overwhelming your team with unnecessary alerts. Most cloud platforms offer APIs to pull this data into dashboards or spreadsheets for regular analysis.
The goal is to give engineers a clear view of how their decisions impact costs. When they see the financial effects of their actions, they naturally become more mindful about spending - without feeling restricted. By focusing on trends rather than isolated numbers, you can differentiate between justified increases (like launching a new feature) and unexplained cost surges that need further investigation.
As your cloud infrastructure expands, keeping track of costs manually becomes a Herculean task. Automated tools step in to provide constant oversight and early warnings, ensuring you stay on top of your spending. The key is to select tools that align with your team's needs and expertise. These tools not only enhance visibility but also help automate the process of keeping expenses under control.
Major cloud providers offer built-in cost management tools that serve as a great starting point, especially for teams without dedicated FinOps resources. These tools provide immediate insights into your spending and are tightly integrated with their respective platforms.
AWS Cost Explorer acts as a central dashboard for visualising your spending habits. It allows you to filter costs by service, region, or custom tags, making it easier to understand where your money is going. With forecasting features based on historical data, you can even estimate your next month's bill with a fair degree of accuracy.
AWS Budgets helps you set spending limits and sends alerts when you're nearing them. For instance, you could set a budget for a specific environment and receive notifications as you approach your threshold, giving you time to address potential overspending.
Azure Cost Management + Billing offers similar tools for Microsoft's cloud platform. It provides cost analysis, budgeting options, and tailored recommendations. Its integration with Azure's resource management tools makes it straightforward to monitor spending across multiple subscriptions and resource groups.
Google Cloud's Cost Management tools deliver detailed billing reports and budget alerts. They also suggest cost-saving actions like rightsizing instances or removing unused resources, helping you keep unnecessary expenses in check.
When setting up cost alerts, it's common to configure notifications at 80% and 100% of your budget, though these thresholds can be adjusted based on your spending habits. Another benefit of native tools is consolidated billing. For example, AWS Organizations offers consolidated billing across multiple accounts at no additional cost, simplifying the process of tracking expenses across development, staging, and production environments.
While these native tools are great for foundational cost management, you may need third-party solutions for more advanced features.
Third-party tools go beyond the basics, offering advanced automation and broader coverage. These solutions are especially useful for companies managing multi-cloud environments or requiring deeper insights into their spending. They build on your tagging and metric tracking strategies, ensuring you maintain a clear view of your costs.
The choice between native and third-party tools often depends on the complexity of your setup and the scope of your needs:
| Category | Native Cloud Tools | Third-Party Tools |
|---|---|---|
| Integration | Fully integrated with cloud services; no external setup required | Requires connecting cloud accounts; setup can be more complex |
| Coverage | Focused on a single cloud provider | Supports multi-cloud, Kubernetes, and SaaS platforms |
| Cost | Typically free | Subscription-based, with pricing tied to features and cloud spend |
| Features | Basic cost visibility, budgeting, and optimisation | Advanced automation and workflow integration |
| Best For | Teams using one cloud provider needing basic cost control | Teams needing multi-cloud support, advanced insights, or deeper optimisation |
CloudHealth (part of VMware) is a standout for companies using multiple cloud providers like AWS, Azure, and Google Cloud. It excels in environments with complex tagging needs, automatically categorising costs by business unit, project, or customer.
nOps focuses specifically on AWS environments, offering features like automated pausing of non-production resources during off-hours, resizing underutilised instances, and managing Reserved Instance purchases. These capabilities can lead to noticeable savings.
For many businesses, the subscription cost of third-party tools is offset by the efficiencies they bring, particularly in multi-cloud setups or complex infrastructures. You might consider third-party tools if you face challenges such as:
Ultimately, the best tool for your team depends on factors like size, technical expertise, and specific operational hurdles. Keep in mind that the real value of any cost monitoring tool lies in how effectively you act on the insights it provides.
After setting up cost visibility and monitoring tools, the next logical step is to optimise how your resources operate. By using the insights gained from tracking costs, you can take practical steps to eliminate waste and save money. This involves two main strategies: aligning resources with actual needs and shutting down idle ones. These methods can bring noticeable savings without the need for a dedicated FinOps team.
It's worth noting that more than 60% of companies overspend on cloud services due to over-provisioned resources. Even more striking, businesses could reduce their AWS costs by 36% just by properly sizing their resources. For small and medium-sized businesses (SMBs) and growing companies, these savings could be reinvested in areas that drive growth and innovation.
Right-sizing is all about matching your cloud resources to your actual workload requirements, ensuring you balance performance and cost. The first step is understanding what you're using versus what you're paying for.
To identify underutilised resources, focus on four key metrics: CPU usage, memory usage, disk I/O, and network I/O. For example, if an instance shows consistently low CPU and memory usage, especially during peak hours, it’s likely oversized and can be adjusted.
Tools like AWS CloudWatch, AWS Trusted Advisor, or Azure Advisor can help pinpoint underused instances. Azure Advisor, for instance, can suggest resizing virtual machines or changing storage tiers for cost efficiency.
Make it a habit to review usage data weekly. For example, if an instance runs at low CPU usage during business hours, it might be a candidate for downsizing.
Storage offers another area for savings. AWS S3 Intelligent-Tiering can automatically shift data across storage tiers based on usage patterns, helping to save costs without sacrificing performance. Similarly, Azure Blob Storage provides hot, cool, and archive tiers for different access needs.
Here are a few practical steps for compute resources:
Optimising when resources run is another key part of cutting costs.
Non-production environments, such as development, testing, and staging, often run 24/7 - even though they’re typically used only during working hours. This makes them a prime target for cost savings.
For teams in the UK, for example, you could schedule environments to operate during standard working hours, say 08:00 to 18:00 on weekdays, and shut them down overnight and on weekends.
Take the example of a fintech company running multiple test environments on Azure. By automating shutdowns during off-hours, they could cut environment costs by 30–50%, potentially saving tens of thousands of pounds annually. This allows full functionality during work hours while significantly reducing idle costs.
To implement scheduling, start by mapping out when your environments are actually used. Track usage over two weeks to identify peak and idle periods, as most development teams stick to standard business hours.
AWS provides tools like Step Functions, Lambda, and EventBridge to automate start/stop operations for EC2 instances, RDS databases, and Auto Scaling groups. Azure Automation offers similar functionality through runbooks that can schedule virtual machine operations.
Consider creating tailored schedules for different teams or projects. For example, your development team might only need resources from 09:00 to 17:00, while a QA team may require extended hours during release periods. Smart tagging can help you manage these varied schedules efficiently.
Start small. Test this approach with a single non-critical environment, monitor the results for a week, and then expand to other environments. Regular monitoring is essential as usage patterns change over time.
Modern tools make this process straightforward. Using Terraform, you can integrate scheduling logic directly into your infrastructure-as-code setup, ensuring new environments automatically follow cost-saving patterns. This also helps avoid the common issue of forgotten, idle resources.
Additionally, reducing the active hours of non-production resources can lower your security risks by limiting potential entry points for attacks. By scheduling these environments effectively, you can maintain production capabilities while significantly cutting unnecessary costs.
Once you've streamlined your resource usage and scheduling, the next logical step is to take advantage of commitment-based discounts. These discounts allow you to secure lower rates by committing to specific usage levels over one or three years. For small and medium-sized businesses (SMBs) without dedicated FinOps teams, understanding how and when to use these discounts can lead to meaningful cost reductions. They also offer engineering teams a way to achieve long-term savings while scaling operations.
The two main options to explore are Reserved Instances and Savings Plans. Choosing the right one depends on your workload patterns and how certain you are about your future needs.
Reserved Instances (RIs) are ideal for workloads that are predictable and run consistently on the same infrastructure. By committing to specific instance types in particular regions for one or three years, you can unlock significant discounts.
Before committing to RIs, analyse at least three months of past usage data. Look for workloads that consistently use the same instance types during the same hours - examples include production databases, web servers with steady traffic, and always-on monitoring systems.
RIs come in two main types:
To minimise risk, start small by committing to 50–70% of your baseline usage. Avoid locking in commitments for peak capacity, which could lead to overpayment. A rolling purchase strategy can also help. For instance, instead of committing £1,200 annually upfront, spread it out as £100 per month over 12 months. This way, one-twelfth of your commitment expires each month, giving you regular opportunities to adjust based on actual usage.
Keep a close eye on your RI utilisation using cost management tools. If utilisation drops below 80%, consider modifying or exchanging RIs to avoid paying for unused capacity. For workloads requiring more flexibility, Savings Plans might be a better fit.
Savings Plans offer the flexibility needed for dynamic and evolving workloads. Instead of committing to specific instances, you commit to spending a certain amount per hour on compute services.
There are two types of Savings Plans:
| Feature | Compute Savings Plans | EC2 Instance Savings Plans | Reserved Instances |
|---|---|---|---|
| Maximum Savings | Up to 66% | Up to 72% | Up to 72% |
| Flexibility | Highest – any instance, region, service | Medium – specific region/family | Lowest – specific instance type |
| Services Covered | EC2, Fargate, Lambda | EC2 only | EC2 only |
| Best For | Dynamic, multi-service workloads | Stable workloads with some flexibility needs | Highly predictable, unchanging workloads |
For many SMBs, starting with Compute Savings Plans is a practical choice due to their adaptability. Begin with a modest commitment - say £50–100 per month - and adjust as your usage patterns become clearer.
When deciding on your commitment level, review your consistent baseline spending over the past six months. Commit to 60–70% of this baseline rather than your peak usage. For example, if your monthly compute costs consistently exceed £200, consider a monthly commitment of £120–140.
AWS often recommends Savings Plans over RIs because of their flexibility. However, combining both can yield the best results: use EC2 Instance Savings Plans for predictable workloads and layer Compute Savings Plans for more dynamic services.
To avoid overcommitting, track key metrics such as your Effective Savings Rate (the actual savings you're achieving) and Commitment Lock-in Risk (the percentage of your total spend that's committed). Limit commitments to no more than 70% of your baseline spend to maintain flexibility for growth and unexpected changes.
For maximum benefit, purchase Savings Plans from a dedicated account or your root management account if it doesn’t have running infrastructure. This ensures the discounts apply across your entire organisation rather than being restricted to specific accounts or projects.
Commitment-based discounts are a powerful way to achieve the next level of cost efficiency. However, they require ongoing attention. Set monthly reminders to review utilisation rates and adjust future purchases based on your evolving needs. This proactive approach ensures you maximise savings without straining your budget.
Incorporating cost awareness directly into development workflows can help prevent expensive mistakes before they make it to production. Instead of being blindsided by unexpected monthly bill increases post-deployment, engineering teams can integrate cost visibility into their processes. This approach allows costly changes to be identified during code reviews and stops resource-heavy deployments from reaching production.
The good news? Adding cost visibility doesn’t mean overhauling your entire workflow. By focusing on two key areas - Infrastructure-as-Code (IaC) reviews and CI/CD pipeline controls - you can cut down on surprise cloud expenses without slowing down development.
IaC tools like Terraform make it easier to provision resources but can also lead to costly mistakes. A single misstep - such as choosing the wrong instance type or storage option - can significantly inflate your monthly bill. Cost estimation tools can catch these issues early in the development process, long before deployment.
Infracost is one such tool, designed to analyse your IaC configurations and provide detailed cost breakdowns before resources are created. It supports over 1,100 Terraform resources across AWS, Azure, and Google Cloud.
"Infracost sits in your engineering workflow and tells you and your engineers how much code changes will increase cloud costs before changes are deployed." – Infracost
Infracost works seamlessly with existing development workflows, integrating directly into GitHub and GitLab pull requests. When infrastructure changes are proposed, Infracost automatically adds cost estimates as comments on the pull request. This gives teams the information they need to make informed decisions during code reviews.
For more precise cost estimates, you can define resource usage in a configuration file (e.g., usage.yml). By integrating through GitHub Actions or pre-commit hooks, Infracost provides real-time cost feedback. For example, it can estimate costs for usage-based resources like AWS Lambda or S3. If a Lambda function is expected to handle 5 million monthly requests with a 300ms execution time, Infracost estimates a monthly cost of around £26.
Spacelift takes this a step further by combining Infracost with policy enforcement. Using Open Policy Agent (OPA), you can create rules that block deployments exceeding specific cost thresholds. For instance, a policy might halt any resource that surpasses your budget, prompting engineers to justify or redesign expensive configurations before deployment.
Once IaC reviews are in place, the next step is to embed cost controls directly into your CI/CD pipelines.
Integrating cost controls into CI/CD pipelines is another effective way to prevent expensive deployments. Positioned between code changes and production, CI/CD pipelines are an ideal checkpoint for enforcing cost policies. By embedding these controls into your deployment process, you can automatically block costly changes and ensure efficient resource usage.
Cloud Custodian is a powerful tool for policy-based resource management that fits neatly into CI/CD workflows. It allows you to define policies that, for example, terminate unused resources, resize over-provisioned instances, or prevent the deployment of overly expensive configurations.
CI/CD platforms also offer opportunities to optimise costs. Using serverless computing for CI/CD tasks eliminates idle resource costs by charging only when builds are running. Similarly, leveraging spot instances for non-critical tasks like testing or staging deployments can save up to 90% compared to on-demand pricing.
For example, in May 2025, nOps showcased how its Compute Copilot achieved 90% cost savings by managing spot instances in Auto Scaling Groups. It used machine learning to update recommendations and lifecycle hooks to drain job queues efficiently.
Pipeline optimisation is another way to cut costs. Techniques like test parallelisation, incremental builds, and caching dependencies or Docker images can reduce execution time, saving not only money but also boosting developer productivity.
Real-time cost reporting within your CI/CD pipeline can link cost changes to specific deployments, enabling quick corrective actions when spikes occur. Tagging strategies also play a critical role here. By consistently tagging pipelines, projects, and environments, you can simplify cost tracking and chargebacks, encouraging teams to stay mindful of expenses.
By embedding cost controls into your workflow, you create a continuous feedback loop that promotes smarter spending. The aim isn’t to slow down deployments but to weave cost considerations seamlessly into the process. Teams that adopt these practices often experience fewer surprise bills and more predictable cloud spending - all while maintaining their development speed.
It’s worth noting that security oversights can also lead to unexpected cloud costs, making robust access controls in CI/CD pipelines equally important.
When engineers understand the cost implications of their decisions during development, they tend to make choices that benefit both performance and the bottom line. This kind of cost awareness fosters more efficient infrastructure planning and better financial outcomes.
You don’t need a dedicated FinOps team to manage cloud costs effectively. With the right strategies, small and medium-sized businesses (SMBs), SaaS startups, and EdTech platforms can make meaningful savings by adopting practical, scalable measures.
The first step is visibility. Surprisingly, only 3 out of 10 organisations have a clear understanding of how their cloud budget is being spent. This lack of clarity is a major reason why nearly half of businesses struggle to control their cloud expenses. Tools like centralised dashboards and proper resource tagging can provide the insights needed to make informed decisions. Once you have this visibility, you can take further steps to streamline costs.
Automation is a game-changer for small teams. By automating tasks like scheduling non-production environments or cleaning up unused resources, you can eliminate unnecessary spending without constant manual effort. This is crucial when you consider that up to 30% of cloud expenses are wasted on resources that aren’t even being used. Automation helps ensure that your cloud usage is efficient, saving both time and money.
Beyond visibility and automation, cost-aware engineering is a long-term solution for controlling expenses. When development teams factor in costs during the planning and deployment phases, they naturally make infrastructure choices that balance performance with budget considerations. This proactive approach can significantly reduce waste while maintaining operational efficiency.
For predictable workloads, commitment-based discounts can lead to substantial savings. These are particularly effective for SaaS and EdTech platforms, where baseline usage can often be anticipated. This approach allows organisations to lock in discounts while still keeping the flexibility to scale as needed.
"You shouldn't need a full-time FinOps team to keep costs under control. We help you cut through complexity with clear visibility, smart automation, and simple controls. No excess and no vendor lock-in." - Critical Cloud
The path to lean cloud cost management is all about taking small, actionable steps. Start with basic visibility using native cloud tools, automate routine processes like environment scheduling, and gradually embed cost-awareness into your engineering practices. Each step builds on the last, creating a sustainable approach to managing cloud expenses.
Small businesses can improve their understanding of cloud costs by using resource tagging effectively. Here’s how to make it work:
Start by creating a clear tagging policy. Include essential tags like project names, cost centres, and environments (e.g., production or development). This keeps everything organised and consistent across your resources. Then, automate the tagging process to minimise manual errors. Automation tools can handle tagging as resources are created, saving time and ensuring compliance with your policy.
Make it a habit to audit your tags regularly. This helps you spot any gaps or inconsistencies, ensuring your cost tracking is accurate. Also, use tags to assign ownership - link resources to specific teams or projects to improve accountability. Finally, invest in team training. Help your team understand why tagging matters and show them how to do it correctly.
Following these steps will help you keep cloud costs visible and under control, even if you don’t have a dedicated FinOps team.
When it comes to managing cloud costs, native tools like AWS Cost Explorer or Azure Cost Management are often the go-to choice for organisations sticking to a single cloud provider. These tools are straightforward to set up and work seamlessly within their respective platforms, making them a convenient option for smaller setups or businesses with simpler needs. However, they might fall short when it comes to handling multi-cloud environments or offering in-depth cost breakdowns.
On the flip side, third-party solutions bring a lot more to the table. They typically offer advanced analytics, better forecasting capabilities, and tools for optimising costs. These features make them a strong contender for organisations with more complex cloud setups or those that require detailed insights and governance across multiple cloud platforms.
Choosing the right option comes down to a few key factors: the complexity of your cloud usage, your budget, and how detailed your cost management needs to be. For straightforward requirements, native tools might do the job just fine. But if you're dealing with a more intricate setup, a third-party tool could provide the deeper insights and control you need.
To keep cloud costs under control and steer clear of surprise expenses, there are a few practical steps teams can take. First, leverage automated cost monitoring tools like AWS Cost Explorer or CloudHealth. These tools provide real-time insights into your spending, making it easier to spot underused resources and fine-tune allocations. The goal? Pay only for what you actually use.
Equally important is fostering a mindset of cost accountability within your team. Assign clear ownership for cloud resources and use resource tagging to track usage and expenses more precisely. This approach links costs directly to business activities, offering a clearer picture of how engineering decisions impact the budget.
By weaving these strategies into everyday workflows, teams can stay efficient, keep costs in check, and support business growth without unnecessary spending.