Traditionally, enterprises turn to short-term fixes to control cloud costs, using tools to identify inefficiencies in existing workloads. But this is only part of the solution. True cloud cost optimization requires long-term and smart architectural decisions.
There are three main strategies to reduce costs, though they only address short-term expenditures:
Right-sizing. Cost management tools evaluate whether a given configuration is the most economical approach for a particular workload. For example, it could help identify a different Amazon EC2 instance that would deliver the same performance for a certain workload that is currently running at a lower cost.
Autoscaling. Autoscaling, usually implemented using a framework provided by a cloud vendor, automatically increases or decreases the allocation of resources to a running workload in response to shifts in demand.
Reserved instances. Reserved instances, such as Amazon EC2 Reserved Instances and Azure Reserved VM Instances, cost less than on-demand VMs. However, they must be booked ahead of time, so they fit best with predictable, static workloads.
With these techniques, enterprises can react in real time, or close to real time. Right-sizing and autoscaling enable users to optimize configurations when those workloads are already running on a particular cloud platform. And while reserved instances can be set up ahead of time, it's typically not very far in advance -- days, at most.
Six long-term optimization strategies
To keep cloud budgets in check, businesses must embrace long-term cloud cost optimization strategies. However, unlike most short-term options, these approaches can't be implemented by a single tool. Instead, they require a more complex and nuanced analysis of business needs and the cloud-based options available to meet them. Through this analysis, enterprises can make decisions that lead to lower cloud computing costs over the long haul.
While cloud cost optimization strategies will vary by organization, here are a six common approaches that can benefit many businesses.
1. Choose the right provider
Finding a provider that trims your costs is easier said than done, given all of the variables involved in cloud computing bills. Cost calculators, such as AWS Total Cost of Ownership Calculator and Microsoft Azure Pricing Calculator, can provide a relatively precise estimation of the cost of a given workload.
Keep in mind that you may find lower prices from a cloud vendor that specializes in a particular kind of cloud service, compared with general-purpose cloud providers. For example, a provider that focuses primarily on cloud storage, like Wasabi or Backblaze, might prove more cost-efficient for storage workloads than AWS, Microsoft Azure or Google Cloud.
2. Choose the right type of service
No matter which cloud provider -- or providers -- you use, it might offer multiple types of cloud services that could be used to achieve the same goal. For example, a typical application could be hosted using standard VMs on a service like Amazon EC2, or it could be containerized and hosted on Amazon Elastic Container Service or Elastic Kubernetes Service. It could potentially be hosted in a serverless computing environment, too.
The cost, performance and management complexity of each of these approaches varies. Cost optimization, then, requires finding the type of service that delivers the best balance between cost and other needs.
3. Choose a cost-efficient redundancy strategy
Today, there are multiple approaches to achieve redundancy in the cloud. One way is to choose a hosting option that distributes workloads across multiple data centers within the same cloud region. This strategy is typically the least expensive, although it also provides the lowest level of redundancy. Similarly, users can mirror a workload across two or more cloud regions, but that typically doubles the cloud computing bill for the workload.
Another option is to take a multi-cloud approach by hosting workloads in two distinct clouds at once. This can also double your bill and additional challenges that come with a multi-cloud architecture. But it delivers the greatest level of redundancy.
Not all workloads require the same level of redundancy, and some require no redundancy at all. The goal is to choose a strategy that meets enterprise needs, but does not provide additional, unnecessary features that cost more.
4. Fix cost-inefficient architecture
The ways in which cloud resources or services interact can have significant ramifications for long-term cloud costs. Consider data egress -- in most cases, cloud providers charge a fee every time data leaves their cloud. A cloud architecture that requires data to exit a cloud frequently can lead to substantial expenses that could be avoided with a different setup.
Egress-related cost bloat can be particularly challenging in multi-cloud architectures, where data frequently passes cloud boundaries. Enterprises should evaluate their workloads to minimize unnecessary data movement.
5. Choose cost-efficient tooling
Most providers' management, monitoring and security tools are free to use for workloads running on their clouds. However, businesses can also implement third-party services to replace or supplement the functionality of native cloud tools. In many cases, the added capabilities of third-party tools are worth the cost. However, it's easy for businesses spend money unnecessarily if they adopt more of these tools than needed, or if they opt for a third-party offering in cases where a vendor's native tool would work just as well.
If you run all of your workloads on a single cloud today, but to adopt a multi-cloud strategy in the future, third-party tools that work with both of the clouds you to use might be worth it, even if it costs more. But businesses with no plans to migrate away from a particular cloud can save more money by sticking with a cloud vendor's native offerings.
6. Don't overlook on-premises infrastructure
Despite the cloud hype, don't overlook on-premises options when the most cost-efficient strategy.
The cloud is powerful, but it's not always the cheaper choice for some workloads. Sometimes, on-premises infrastructure delivers a better tradeoff between cost and performance. This is especially true in the case of workloads that involve high volumes of data egress or ones that require specialized hardware configurations, such as a bare-metal server, that cost extra in the cloud. Don't be afraid to repatriate workloads already running in the cloud if on-premises hosting proves to be more inexpensive.