18 Cloud Cost Optimization Best Practices for 2026

The cloud scales with your needs, which is exactly why the bill is so easy to lose control of. You spin up resources to meet demand, forget to shut them down, and the month-end invoice climbs faster than anyone budgeted for.

Most teams don’t have a spending problem so much as a visibility problem. They can’t see where the money goes until it’s already gone. Cloud cost optimization is how you close that gap.

Cloud cost optimization is the process of addressing this challenge and producing the most cost-effective cloud infrastructure. Implementing a cloud cost management system lets you maximize your ROI from the cloud by providing clear insights on where, how, and why costs are being accrued.

In this article, we’ll elaborate on what cloud cost optimization involves, then share 18 best practices you can adopt to help control and reduce your spend.

1. What is cloud cost optimization?
2. The benefits of cloud cost management
3. Best practices for cloud cost optimization
4. Cloud cost optimization tools

Cloud cost optimization is the practice of cutting cloud spending without giving up performance, reliability, or scalability. You analyze usage patterns, find underutilized resources, and fix what you find by rightsizing instances, buying reserved or spot capacity, and shutting down idle services.

Done well, cloud cost optimization balances operational, compliance, security, and budget requirements, so you pay for the performance you actually need and nothing else.

Working out what’s optimal is the hard part. You compare provider pricing tables, choose between resource types, and pick infrastructure that meets your requirements without generating waste. Without the right tools and processes, that work eats days you don’t have.

Plan for cost problems before they show up. Cloud cost optimization is the set of strategies that keeps you from overpaying as your resources and requirements change, so you know where every dollar of your cloud budget goes.

Cloud cost optimization is the technical work of reducing spend. FinOps is the operating model that makes it stick. It gives engineering, finance, and product teams shared ownership of cloud spending, so cost becomes a number everyone can see and act on rather than a surprise finance chases down after the fact.

The FinOps Foundation frames the work as three repeating phases: inform (give teams visibility into what they spend and why), optimize (rightsize, commit, and remove waste), and operate (build the governance and automation that keep costs down as you scale). 

Most of the 18 practices below map onto one of these phases.

The table below summarizes the benefits that cloud cost management can bring to your organization:

Benefit	Description
Cost visibility	Provides real-time dashboards and reports that break down spending by service, region, or project
Optimized resource utilization	Identifies idle or oversized instances and suggests rightsizing to reduce waste
Cost control	Facilitates setting spending limits and creating alerts to avoid exceeding budgets
Forecasting and planning	Uses historical data to predict future cloud costs and helps in creating accurate budget plans
Automation of cost savings	Automates tasks like shutting down unused resources or scaling services during off-peak hours
Accountability and governance	Assigns costs to specific teams or projects, making it easier to track and justify expenses (read more: Cloud Cost Governance: Best Practices for Controlling Spend)
Scalability without waste	Ensures resources scale up or down based on demand to prevent over-provisioning and unnecessary costs

The best cloud strategy for cost optimization involves rightsizing resources, leveraging reserved or spot instances, and adopting autoscaling to ensure you only pay for what you use while maintaining performance.

The 18 best practices below help you identify, monitor, and reduce cloud costs, optimizing operational efficiency and lowering your monthly bills. Following as many of these cloud cost optimization strategies as possible will give you the best chance of achieving a positive cloud ROI, letting you capitalize on the benefits without incurring eye-watering costs.

All cloud cost optimization efforts begin with gaining insights into what you’re paying for each resource. Until you have this information, you can’t make accurate decisions about whether you’re spending too much.

You can get insights into costs by using dedicated tools to monitor accrued fees in real time. Kubecost is a popular choice for checking costs associated with Kubernetes clusters, for example, while cloud vendors typically offer their own cost-tracking tools. AWS Cost Explorer, Google Cloud Cost Management, and Microsoft Cost Management are some examples.

Paying for redundant resources is one of the most common ways overall cloud costs balloon. Old resources left over from past workloads or administration activities don’t deliver value to your organization but will still contribute to your bill.

You should regularly audit the resources in your cloud accounts to spot and remove unnecessary items. Compute instances without user interactions, empty databases, and detached storage volumes are all good candidates for delivering significant cost savings.

Underutilized resources are another prevalent cause of excess cloud costs. Provisioning large compute resources won’t provide an advantage for apps that can’t utilize the available CPU and memory capacity, but you’ll still have to pay for the unused resources. Storage volumes that are sized much larger than your data create the same problem.

Right-sizing involves matching resource capacity to resource utilization. Cloud mechanisms such as auto-scaling can dynamically right-size on demand based on actual resource utilization. This ensures you don’t end up paying for instances to sit idle.

Using one provider for all your services can increase your costs and create a potential redundancy issue. Consider what’s available from alternative providers. If you want to start using a new type of cloud resource, such as a managed database or storage solution, it could make operational and financial sense to go multicloud and select a service from another cloud provider.

Let’s consider some examples of using multiple cloud providers:

Use case	Primary cloud/service	Secondary cloud/service	Benefit
Disaster recovery and backup	Microsoft Azure: Virtual Machines, Databases	AWS: Amazon S3 for Backup and Disaster Recovery	Improved resilience and redundancy
Hybrid cloud and compliance	On-Premises: Private Infrastructure	Azure: Azure Active Directory, Azure Functions	Meet compliance and security regulations
DevOps and container orchestration	AWS: AWS Lambda (Serverless Compute)	Google Cloud: Google Kubernetes Engine (GKE)	Serverless compute combined with container orchestration

With proper management controls, multi-cloud infrastructure doesn’t have to be complex. Adopting this route means you can choose the most cost-efficient and performant solution for each cloud service you require.

Learn how to optimize your multi-cloud strategy with Infrastructure as Code.

Storage for cloud-native apps comes in different flavors. Object storage, network storage mounts, and block volume disks that mount directly to compute instances are all viable options. Apps often support multiple storage types, so you have flexibility in selecting the right one for your environment. Evaluating different types of storage can lead to significant cost savings.

It’s also important to use an appropriate storage class for each of your data types. For example, infrequently accessed backups should usually be stored in an archival-grade storage tier such as S3 Glacier. This will be substantially cheaper than a more performant tier designed to facilitate regular access.

Designing your apps to use a cloud-native architecture can allow you to reduce costs throughout the app’s life.

Running apps as stateless containers that connect to separate storage solutions lets you try different deployment methods, including PaaS, microservices, and orchestration with tools like Kubernetes. This can be more efficient and easier to maintain than traditional methods that create a new compute instance or VM for each deployment.

Alerts that fire when costs spike allow you to identify spending anomalies as they happen. Tools that understand historical spending can flag anything extraordinary that happens in your infrastructure, ensuring you can take action before the end of the billing cycle.

For this to work, you should clearly define strict budgets and stick to them so team members can quickly tell whether an overspend has occurred.

Cloud compute instances are available in different types to accommodate various performance vs cost efficiency scenarios. Most cloud providers allow you to pick from on-demand, reserved, spot, and dedicated instances. Taking the time to evaluate these choices before you deploy can generate huge long-term savings.

Most organizations default to using on-demand instances for virtual compute. You’re billed for every hour (or second) that your instance is up, so these instances are some of the most expensive available. Spot instances let you access unused capacity when it’s available; the prices vary with demand and can be a much more cost-effective option for less critical workloads.

Alternatively, reserved instances are best for long-term deployments that require consistent performance. Reserving an instance type for an agreed time period, typically measured in years, can offer massive cost savings, up to 72% for AWS or 57% for Google Compute Engine, if you’re willing to make the commitment and pay upfront.

Cloud providers regularly change their pricing, so it’s worth reviewing their offerings periodically to check if you could switch and save. You might be able to reduce your cloud bill by choosing a slightly different service from the same provider or by migrating to a similar solution in a rival cloud.

To simplify cost comparisons, you can use IaC-linked tools like Infracost to evaluate what you’d pay for your infrastructure across different cloud platforms. This removes the repetition of manually scraping information from verbose pricing tables.

Read more: How to Estimate Cloud Costs with Terraform and Infracost.

Unnecessary data retention can gradually increase your cloud costs, especially when you use an inappropriate storage type. You can prevent this by periodically auditing your data catalog and deleting anything that doesn’t need to be kept. Old backups, log files, and crash dumps are some of the data types to look at.

You can prevent excess storage consumption by configuring appropriate data retention timelines, and then using automated processes to prune your storage as records become outdated. For example, you can use lifecycle policies to automatically delete files in your object storage buckets once they reach a certain age.

Cloud cost budgets should also account for any proprietary software subscriptions or licenses that your deployments depend on. These could be deployed manually or via the service marketplaces that are integrated into cloud provider control panels.

Pruning the number of licensed software subscriptions you use could be a viable way to reduce your total bill, especially where good free or open-source (FOSS) alternatives are available. You can then reallocate your budget to other infrastructure areas.

High cloud costs sometimes arise because developers don’t appreciate how expensive cloud resources can be. Developers need autonomy within frictionless workflows, so many organizations prioritize extending cloud access to them so they can launch new apps and test environments. However, a lack of guardrails can allow developers to create excessive resources and then forget to delete them later.

Educating engineers on how they can contribute to cost-cutting will help prevent bill shock. Establish a cost culture within your organization to encourage people to reduce waste without compromising their output.

Shadow IT describes the unauthorized use of apps, devices, and compute infrastructure that occurs without an administrator’s knowledge. Shadow IT can evolve into shadow cloud when team members are given access to cloud computing environments.

Preventing a shadow cloud can stop charges for mysterious, unknown activities from appearing on your bill. To do this, you should systemize your process and ensure that all developer interactions with cloud resources are managed through a consistent platform. This will ensure you have constant oversight of what’s running in your cloud environments, allowing costs to be accurately accounted for.

Self-service test, staging, and QA environments can shorten the software development lifecycle (SDLC) by allowing developers to preview changes in production-like environments. However, these ostensibly transient environments can be forgotten after the work is completed, causing unexpected costs to accrue.

These situations can usually be resolved by integrating tooling into your development pipeline that automatically shuts down development environments after the relevant code has been merged into your project’s main branch. This prevents waste and removes the need for admins to manually clean up old instances.

Network and bandwidth costs are among the hardest to control because they’re usually directly proportional to how your system is being used. One way to control bandwidth costs is to avoid data flows outside your cloud platform to the maximum extent possible. Network traffic between resources in your cloud is often cheaper than external traffic — providers charge an egress fee each time data leaves their boundaries.

Transfers between regions can also incur extra charges. For high-traffic applications, try distributing your deployment across multiple geographic regions so users always hit the data center closest to them. Sometimes, the answer can be to move more resources into the cloud: If you have an on-premises app that interacts with a lot of cloud data, moving the system entirely into the cloud could reduce your egress fees.

Read more: Cloud vs On-Premise: Cost Comparison

The cost of cloud support is often overlooked. Premium support plans with dedicated contacts and troubleshooting steps add reassurance, but they can also significantly increase your monthly bill.

If you rarely use support, you could consider switching to an alternative plan, requesting a long-term arrangement to reduce your costs, or dropping premium support altogether. Arguably, a competitive SLA is more important than direct support access — when cloud providers fail, it’s often in a catastrophic outage that frontline staff will be unable to help you with directly.

Costs are one of the key ways cloud providers compete for customers. Most leading platforms publish resources to help you cut costs, such as these recommendations from Google, as well as offering dedicated savings plans that tangibly reduce your bill.

Savings plans typically require you to make a multi-year commitment to purchase resources from the provider. In return, you’ll receive heavily discounted rates on selected services, during the lifetime of the term. For example, AWS Savings Plans can reduce your Compute, EC2, and SageMaker bill by up to 72%. Azure’s equivalent provides discounts of up to 65%.

Forecasting future cloud spending helps organizations prevent budget overruns and optimize cloud resource utilization. Accurate predictions are achieved by analyzing historical usage patterns and applying tailored forecasting methods to specific workloads and business needs.

Key approaches to cloud spending forecasting include:

1. Analyzing historical data: Review detailed cloud usage logs (e.g., compute instances, storage usage, and data transfer) to identify trends, such as spikes during product launches or seasonal demands.
2. Workload-specific forecasting: Break down forecasts by workload types (e.g., machine learning pipelines, database queries, or container orchestration clusters) to pinpoint areas likely to scale and drive cost increases.
3. Using predictive analytics tools: Cloud-native services like AWS Cost Explorer, Azure Cost Management, or third-party tools (e.g., CloudHealth) use AI-driven models to predict future costs based on current usage, resource configurations, and growth plans.
4. Scenario planning: Develop forecasts for multiple growth scenarios, such as “steady-state,” “rapid expansion,” or “cost-optimized refactoring,” to prepare for fluctuating business demands.
5. Real-time adjustments: Integrate continuous monitoring and alerts to detect cost anomalies, enabling you to refine forecasts dynamically and avoid unexpected spikes in spending.

Cloud cost management tools provide features like cost visibility, automation, and actionable insights to optimize your cloud investments. Below is a comparison of some leading cloud cost optimization tools:

Tool	Key features	Supported platforms	Pricing model
CloudZero	Aligns cloud costs with business metrics,  per-unit cost insights (e.g., cost per customer)	Primarily supports AWS, Azure, GCP, Oracle	Custom pricing based on usage and requirements
IBM Cloudability (formerly Apptio Cloudability)	Provides comprehensive dashboards, anomaly detection, cost allocation, and supports FinOps practices	AWS, Azure, GCP	Subscription-based pricing
nOps	Real-time cost analysis, compliance tracking, change management, and automation of cloud operations	AWS	Subscription-based pricing
Flexera One	Cost reporting, security, automation, and governance across multicloud environments (now includes the former CloudCheckr and Spot capabilities)	AWS, Azure, GCP	Subscription-based pricing
Densify	Utilizes machine learning for resource optimization, supports hybrid environments, and offers automated cloud resource management	AWS, Azure, GCP	Subscription-based pricing

These tools provide robust features tailored for different cloud environments, making it easier to streamline costs and boost efficiency in your cloud operations. To select the right tool, consider your cloud provider, organizational needs, and budget constraints.

A platform like Spacelift can help your organization manage cloud infrastructure more efficiently.

Spacelift is the infrastructure orchestration platform built for the AI-accelerated software era. It manages the full lifecycle for both traditional infrastructure as code and AI-provisioned infrastructure, supporting tools like OpenTofu, Terraform, Ansible, Pulumi, Kubernetes, and CloudFormation.

Security is one of Spacelift’s top priorities, with features such as policy as code, encryption, single sign-on (SSO), MFA, and private worker pools built into the product. Spacelift is SOC 2 Type II audited and provides compliance and security artifacts, including GDPR resources and its DPA, through the Spacelift Trust Center.

It is also the first IaC orchestration platform to receive FedRAMP authorization, delivering flexible, policy-driven automation to federal agencies and contractors seeking secure, compliant infrastructure workflows.

The power of Spacelift lies in its fully automated approach. Once you’ve created a Spacelift stack for your project, changes to the infrastructure as code files in your repository are automatically applied to your infrastructure.

For non-critical workloads like tests, POCs, and demos, Spacelift Intelligence adds an AI-powered layer that enables natural language provisioning, diagnostics, and operational insight, so developers can request infrastructure without writing configuration code while platform teams retain full governance and visibility.

Spacelift’s pull request integrations keep everyone informed of what will change by displaying which resources are going to be affected by new merges. Spacelift also allows you to enforce policies and automated compliance checks that prevent dangerous oversights from occurring.

Spacelift includes drift detection capabilities that periodically check your infrastructure for discrepancies compared to your repository’s state. It can then launch reconciliation jobs to restore the correct state, ensuring your infrastructure operates predictably and reliably.

With Spacelift you get:

• Multi-IaC workflow
• Stack dependencies: You can create dependencies between stacks and pass outputs from one to another to build an environment promotion pipeline more easily.
• Unlimited policies and integrations: Spacelift allows you to implement any type of guardrails and integrate with any tool you want. You can control the number of approvals you need for a run, which resources can be created, which parameters those resources can have, what happens when a pull request is open, and where to send your notifications data.
• High flexibility: You can customize what happens before and after runner phases, bring your own image, and even modify the default workflow commands.
• Self-service infrastructure via Blueprints and Templates: You can define infrastructure templates that are easily deployed. These templates can have policies/integrations/contexts/drift detection embedded inside them for reliable deployment.
• Drift detection & remediation: Ensure the reliability of your infrastructure by detecting and remediating drift.
• Spacelift Intelligence: AI capabilities are embedded in the platform, such as Infra Assistant and Intent, which operate within the same policies and approval flows as everything else, so that teams can adopt AI-driven workflows with the guardrails already in place.

If you want to learn more about Spacelift, create a free account today or book a demo with one of our engineers.

Cloud cost optimization strategy is an essential part of cloud operations management. When using the cloud at scale, you’re likely to accumulate redundant, outsized, and misconfigured resources that add to your cloud bill without providing any value to your organization.

Following the 18 cloud cost optimization best practices discussed above will allow you to anticipate costs, understand what’s causing them, and make informed changes to increase your cloud ROI. Remember that cost management starts with securing full visibility of where costs are originating before you begin to make any changes.

Does your organization have extra compliance concerns? Here you can learn more about self-hosting Spacelift, to ensure your organization’s compliance, control ingress, egress, internal traffic, and certificates, and have the flexibility to run it within GovCloud.