Strategies for Reducing Cloud Costs: 5 Things You Can Try

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Axle Networks Blog – Cloud services, with its scalability, flexibility, and efficiency, have become a crucial component of business operations in the current digital era. Still, cloud services can have a big financial impact, so it’s critical for businesses to minimise their cloud costs. You can improve their operational efficiency and financial health by putting costs related to the cloud into lower limits.

But how do you reduce cloud costs while maintaining performance?

Let’s look at some ways to cut your cloud costs while keeping it running smoothly and efficiently.

What Drives Cloud Costs?

Cloud costs are driven by various factors, including resource utilization, storage, data transfer, and service usage. It primarily driven by three main factors:

  1. Compute: This refers to the processing power, memory, and temporary storage you need to run workloads smoothly. Your cloud provider offers a range of compute instance types, each offering a specific configuration of CPU, memory, and network capacity.
  2. Network Connectivity: This refers to the network capacity you use for your applications.
  3. Storage Capacity: The amount of data storage you require also significantly impacts the cost.

In addition to these, other factors such as the specific cloud provider’s pricing model, the geographical location of the servers, and additional services like data transfer, backup, and disaster recovery can also influence the overall cost. It’s also worth noting that the cost of a subscription is a significant factor when choosing a cloud storage service.

For example, as of 2024, Sync.com offers 1TB to unlimited GB of storage for $6 per month. However, the value of a subscription can vary between users, depending on their specific needs and requirements.

5 Strategies for Reducing Cloud Costs

1. Understanding the Concept of Right-Sizing Your Resources on the Cloud

Right-sizing is a crucial strategy in cloud computing that involves optimizing the size of your cloud resources based on your workload requirements.

It improves efficiency and reduces costs by ensuring that the number of resources used corresponds to the demands of your workload. The process involves evaluating your workload and adjusting your resource usage accordingly. Right-sizing your resources can help you save money without sacrificing performance.

With granular visibility, you can identify assets that are over-provisioned or idle. In addition, the rightsizing tool suggests changes to ‘rightsize’ usage and saves money. Such tools also help you optimize the cloud by ensuring that you get the most out of your paid resources.

A rightsizing tool notifies you when costs exceed a predetermined percentage over a given time period. You can also set the tool to terminate unused assets after this time frame to continue optimising your cloud costs.

Using the cloud cost management technique is one way to lower your cloud costs. You can read more about its definition, advantages, and some helpful tools, in our earlier post below.

Read More: Cloud Cost Management: Definitions, Benefits, and Top Tools

2. Choosing the Right Pricing Model

Choosing the right pricing model is critical to reducing your cloud costs. Whether it’s pay-as-you-go, reserved instances, or spot instances, each pricing model provides unique cost-saving opportunities. So, aside from knowing what you need, you also have to have some knowledge of the cloud pricing structure. Five of the most common are:

  1. Pay-as-you-go (PAYG): This model allows users to pay for cloud resources on an hourly or monthly basis, without any upfront commitment. It is ideal for workloads with unpredictable or variable usage patterns.
  2. Reserved Instances (RIs): This model offers significant discounts for a one-year or three-year commitment to a specific instance type in a specific region. It is best suited for steady-state, predictable workloads.
  3. Savings Plans: This model provides lower prices in exchange for a commitment to a consistent amount of usage (measured in $/hour) for a one-year or three-year term. It offers more flexibility in usage compared to RIs.
  4. Spot Instances: This model allows users to bid for spare capacity at lower prices. However, these instances are unreliable because they can be terminated at any time due to capacity demands. They are suitable for batch jobs or jobs that can tolerate disruption
  5. On-demand pricing: This model offers maximum flexibility without any upfront payment or commitment. It is ideal for irregular workloads that cannot be interrupted.

You can choose any of them based on the pricing model that is most cost-effective and meets your needs. However, to determine which option is the most cost-effective, you must assess your workload characteristics, budget constraints, and long-term usage projections.

3. Identifying and Eliminating Waste

Waste in cloud resources can significantly impact costs.

One of the primary sources of waste is idle resources. These are resources that have been provisioned but are not being used or are underutilised. Regularly identifying and eliminating these resources can lead to significant cost savings.

Another common source of waste is over provisioned resources. This refers to having more capacity than is actually needed. It’s important to monitor resource allocation regularly and adjust it to match actual usage. This prevents paying for resources that are not being fully utilised.

Unused storage and unattached volumes are other areas where waste can occur. Regularly reviewing and deleting unnecessary data can help avoid these costs. Similarly, unattached volumes, which are storage volumes that were once attached to a virtual machine but are no longer used, continue to incur costs until they are deleted.

Old snapshots, or backups of your data, can also contribute to waste. If these snapshots are no longer needed, they can be deleted to save costs. Unused IP addresses, particularly public IP addresses that are not associated with a running instance, also incur costs.

4. Use Auto-Scaling System

Auto-scaling is a cloud computing feature that allows users to automatically scale cloud services, like virtual machines (VMs) and server capacities, up or down based on defined situations. This dynamic adjustment of resources helps maintain application availability and allows you to pay only for the resources you need, thereby reducing costs.

To leverage auto-scaling, it’s important to understand how it works. Auto-scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. It provides a single unified interface to configure and manage automatic scaling for all scalable resources in your application.

Implementing auto-scaling involves setting up policies that define when to scale resources. These policies are based on specific metrics, such as CPU utilisation or network traffic. When these metrics hit a certain threshold, the auto-scaling feature kicks in to either add more resources (scale out) or reduce resources (scale in).

AWS Auto Scaling, for example, includes built-in scaling strategies designed to optimise performance, costs, or a balance of both. It also offers predictive scaling, which uses machine learning to automatically schedule the right number of instances based on predicted demand.

In combination with load balancing, auto-scaling ensures an even distribution of workloads across instances, leading to improved performance and cost savings. 

Remember, the goal of auto-scaling is not just about scaling up when demand increases, but also about scaling down when demand decreases. This ensures that you’re not paying for resources that you don’t need.

5. Moving to a Microservices Environment 

This strategy may not be suitable for all business scenarios. However, according to the Middleware blog post, this strategy is one that you should consider.

Making the switch from an on-premises to a cloud environment without making any changes seems like a simple and affordable choice. However, this kind of behaviour could result in cloud waste, meaning that you pay for computational resources that are not used.

Making the switch from legacy applications to microservices-based architecture can save a significant amount of money and time. A portion of the components can be moved to the cloud, given resource constraints. Modest design adjustments can be made to get rid of inefficiencies that could lead to more cloud waste.

Microservices architecture allows for greater flexibility and scalability by breaking down applications into smaller, independent services. This can lead to faster development cycles and easier maintenance of complex systems.

While cost is often the primary concern for businesses, cloud optimisation has been shown to have a greater impact. You can read our previous article to learn more about the relationship between cloud optimisation and business efficiency.

Learn More: 5 Ways to Maximise Business Efficiency through Cloud Optimisation

Conclusion

To summarise, in the current competitive business environment, optimising cloud costs is critical to attaining both financial stability and operational efficiency.

Organisations can attain cost efficiency and minimise cloud expenses by employing tactics like auto-scaling, identifying waste, selecting the appropriate pricing model, and appropriately sizing resources. Companies can improve their overall financial health, drive innovation, and more efficiently allocate resources by proactively managing cloud costs.

Do you want to increase the effectiveness and optimise of your cloud environment?

Axle Networks Cloud Managed Services offers robust cloud management solutions tailored to your specific needs. With our team of experienced professionals, you can rest assured that your cloud-based resources and data will be protected from unauthorised access and potential security threats.

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