17 Cloud Cost Optimization Best Practices for 2024

Cloud architectures provide significant enhancements for operational efficiency and performance. Moving to the cloud can also deliver cost savings as you’re able to continually scale resources to satisfy changes in requirements.

Nonetheless, many organizations struggle to control cloud costs. The flexibility of the cloud means it’s easy to end up with a higher bill than expected at the end of the month.

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 17 best practices you can adopt to help control and reduce your spend.

Cloud cost optimization is an umbrella term that describes the overall method of maximizing cloud resource efficiency in order to reduce your bill. Effective cloud cost optimization strategies balance operational, compliance, security, and budgetary requirements to achieve the best cloud performance at the lowest possible spend.

Working out what’s optimal can be a daunting task. Comparing cloud provider pricing tables, choosing between different types of resources, and selecting infrastructure that satisfies your operational requirements without causing waste is time-consuming if you don’t use proper tools and processes.

Planning ahead so you can anticipate cost-related issues equips you to solve this problem. Cloud cost optimization encapsulates the different strategies you can use to avoid paying too much as you iterate on your cloud resources and evolve your operational requirements. It lets you accurately assess the most suitable way to spend your cloud budget.

Why is cost optimization important in the cloud?

Practicing cloud cost optimization is essential as you increase your cloud adoption. Unused and incorrectly sized resources will waste your budget and lead to overspends that can quickly multiply as time passes.

Engaging in cost optimization will also uncover insights that allow you to accurately attribute costs to different apps, projects, teams, and customers. This information lets you track where costs are being accrued across all levels of your organization. Taking a proactive approach to cost management means you can spot trends and anomalies before they affect your bill, making it possible to prevent unexpected spending.

The 17 best practices below allow you to identify, monitor, and reduce cloud costs so you can optimize operational efficiency while lowering your monthly bills. Following as many of these best practices as possible will give you the highest possible chance of seeing a positive cloud ROI that lets you capitalize on the benefits, without facing eye-watering costs.

All cloud cost optimization efforts begin with gaining visibility 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 obtain visibility 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 solutions—AWS CloudWatch, GCE Cost Management, and Microsoft Cost Management are some examples.

One of the most common ways that cloud costs balloon is when you’re paying for redundant resources. Old resources that are leftover 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 so you can spot and remove unnecessary items. Compute instances without any user interactions, empty databases, and detached storage volumes are all good candidates that can deliver 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 be paying more for the privilege. Storage volumes that are sized much larger than your data result in the same problem.

Right-sizing is the process by which resource capacity is matched to resource utilization. You can use cloud mechanisms such as auto-scaling to 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, in addition to creating a potential redundancy issue. Don’t blind yourself to 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, then it could make operational and financial sense to go multi-cloud and select a service from another cloud provider.

With proper management controls, multi-cloud infrastructure doesn’t have to be complex. Going 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 that you can choose between. 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. As an example, infrequently accessed backups should usually be stored in an archival-grade storage tier such as S3 Glacier. This will be substantially lower cost than a more performant tier that’s designed to facilitate regular access.

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

Running apps as stateless containers that connect to separate storage solutions allows you to try different deployment methods, including PaaS, microservices, and orchestration through tools like Kubernetes. This can be more efficient and easier to maintain when compared with 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 and adhere to strict budgets 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 grant huge long-term savings.

Most organizations default to using on-demand instances, the most popular form of virtual compute where you’re billed for every hour (or second) that your instance is up. Yet these instances are also 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 75% for AWS or 57% for GCE—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 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 cause gradual increases in cloud costs, especially when an inappropriate storage type is being used. 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; extending cloud access to them, so they can launch new apps and test environments is, therefore, a priority for many organizations. 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 tighten the software development lifecycle (SDLC) by letting developers 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 some of the hardest to control because they’re usually directly proportional to how your system is being used. One way to keep a lid on 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 will charge an egress fee each time data leaves their boundaries.

Transfers between regions can also incur extra charges. For high-traffic applications, you can 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.

The cost of cloud support is a factor that’s often overlooked. Premium support plans with dedicated contacts and troubleshooting steps add reassurance, but they can also be significant contributors to your monthly bill.

If you rarely call upon 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 won’t be able to directly help you with.

It’s no secret that cloud providers want you to use their services, and they understand that costs are one of the key ways they can compete. 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. AWS Savings Plans can reduce your Compute, EC2, and SageMaker bill by up to 72%, for example, while Azure’s equivalent provides discounts of up to 65%.

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

Following the 17 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 obtaining precise visibility into where costs are coming from, before you begin to make any changes.

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