How to prioritize cloud spending: 5 strategies for architects

Cloud spending rises every year as organizations adopt innovative digital-first technologies and services to meet new business and social needs. It's easy for companies to overlook their cloud usage, leading to skyrocketing bills and paying for more cloud capacity than they need. Enterprise architects can help organizations optimize their cloud spending by evaluating what's needed and basing their designs on that data.

One option for helping to manage cloud spending is using committed cloud spending programs. Committed cloud spending involves paying for a specific amount of cloud capacity based on what you order. Prioritizing it requires tracking consumption and reducing what you spend. The good news is that architects can help get cloud costs under control and manage them before the bills hit. Read this article for five tips to optimize your cloud budget.

1. Select reserved instances for long-term commitments

If you're ready to employ a specified amount of resources for a particular time, you can capitalize on discounted pricing schemes. One such example is using reserved instances instead of on-demand cloud computing. This billing concept means you get a discount on cloud services in exchange for committing to a certain amount of usage.

Reserved instances allow you to save money on cloud resources in exchange for a commitment to use those capacities for a specified period, such as one to three years. How much you can save varies by the platform and other factors, but reserved instances can cost one-third less than on-demand instances.

Reserved instances and savings plans come in handy for long-running and steady-state workloads, where you can ensure consistent and predictable capacity.

2. Plan for the resources you need

Cloud architecture enables you to spin up and down instances in the cloud swiftly. But there are so many instance types (servers) that architects often choose the incorrect instance size or forget they are using more compute resources than they need. As a result, the servers run idle, causing you to pay for unused capacity.

Capacity planning will help you reduce overall cloud costs. Forecast your consumption to avoid paying for unused capacity. Provide room for unanticipated traffic spikes and load fluctuations without consuming unneeded resources. Monitor unexpected spikes and out-of-band spending that exceeds the forecasted cloud usage, even during seasonal fluctuations.

[ Learn how Red Hat Insights helps you monitor your hybrid cloud environment for identifying security and performance risks, tracking licenses, and managing costs. ]

Your technical team doesn't have to spend time monitoring all situations. Trigger alerts on anomalies when a deviation from a normal trend emerges. This helps your team focus on other tasks while being able to identify and take action on cost anomalies before they damage your budget.

How do you define an anomaly? It may be spending 10 times more than expected on one day, or planning to spend $10,000 a month yet paying $8,000 for a week. Machine learning can become your ally in discovering anomalies. These self-learning tools rely on historical data, predict the normal value range, and flag cases outside that range. They may also compile spending reports and provide tips on cost optimization.

3. Implement rightsizing

How can you optimize costs in terms of overprovisioned service allocations and unused resources? The answer is to practice rightsizing. Rightsizing means adding or reducing cloud resources to match your actual need.

Cloud providers charge businesses according to delivered services, so clients can concentrate on managing virtual resources on demand. As a result, downsizing cloud resources can save you a lot of money on your monthly bill.

How can you implement rightsizing? Track resource usage for a week or another period. Compare it to the received capacity and adjust the allocation size. You can adjust down or up, as you may need to add more resources if performance is poor.

[ Learn how to simplify hybrid cloud operations with Red Hat and AWS. ]

You can enhance your resource consumption with autoscaling solutions. These features assist in prioritizing cost, availability, or performance, as they automatically monitor and adjust application scale to suit demands.

For example, you can specify lower-priority applications. If you don't need to scale them much, you can add performance restrictions to utilize the minimum resources on such applications. Other strategies, including serverless computing, queuing, and caching, can eliminate paying for idle capacity.

In some cases, a cloud provider executes rightsizing on its own without involving the customer. For example, if computing powers are idle at night, they are auto-paused. When the application uses the database, it autoscales to meet those needs. The cloud service charges only for the hours when the workload is utilized.

4. Opt for spot instances

You can save money by leveraging your cloud service's unused capacity, which is less expensive than on-demand capacity. These arrangements are known as spot pricing models.

The price of spot instances changes over days and weeks, so you can't predict the cost at the time of purchase. The amount of money saved varies depending on the type of resource: Low-priority instances are the least expensive, but they may be unavailable or turn off abruptly depending on capacity demand in the region.

[ Learn more about how to modernize your IT with managed cloud services. ]

But such cases are rare. For example, AWS states that the average interruption frequency across all regions and instance types doesn't exceed 10%. Spot instances are best for stateless workloads, batch operations, and other fault-tolerant or time-flexible tasks.

5. Avoid unnecessary data transfers

Fees for data transfers may skyrocket when you move data to and from a public cloud. They may appear when you move data off the system or between regions. How can you limit these data transfer fees?

Begin by examining your cloud provider's transfer fees. Then, find ways to limit the number of data transfers in your cloud architecture. For example, you may need to change your application behavior and architecture to use computing resources in the closest data location. Transfer on-premises apps that often access cloud-hosted data to the cloud.

In contrast to the cloud, specific resources (such as network bandwidth) are considered free in traditional datacenters. So if you move applications from on-premises datacenters, modify your application architecture to limit the amount of data transferred.

Research the costs of various transfer methods, such as using a dedicated network connection service versus a physical transfer device, before making a decision.

Final thoughts

Enterprise-level cloud spending can be hard to control. Organizations face issues predicting cloud purchases, receiving exorbitant bills, and wondering if moving to the cloud was the right decision in the first place.

At the same time, cloud computing provides visibility into IT costs. Employ this advantage to drive more efficient consumption of resources and track where your money goes. Cloud cost optimization lets users receive the maximum capacity for each dollar spent and supports long-term, cost-effective cloud operations.

Architects can help manage cloud environments proactively through detecting and correcting inefficient cloud infrastructure provisioning and developing best practices for cloud financial management. Predict consumption and set budget goals. How much do you spend on each initiative, project, or application? Once you establish tracking, you can reduce your monthly bill by uncovering anomalies, correcting them, and automating decision-making.