Experts predict that by 2025, businesses will spend over 50% of their annual technology budgets on cloud services.
AWS’s pay-as-you-go pricing model, while flexible, can lead to unexpected costs from unused or unnecessary resources. These cost overruns are a serious issue that can significantly impact a business’s bottom line. But mitigating these expenses requires more resources and bandwidth than most engineering and finance teams can dedicate to the issue.
Luckily, a number of tools, techniques, and strategies exist to help you reduce cloud costs with minimal intervention from your internal teams. In this guide, we’ll take a look at some of the best ways to reduce your cloud computing expenses with little effort.
1. Use cost management tools
Cloud financial management tools help organizations monitor, control, and optimize their cloud expenses. As more businesses migrate to cloud platforms, managing costs becomes critical for ensuring the most efficient use of resources and staying within budget.
ProsperOps helps businesses optimize AWS costs without requiring extensive manual intervention. By avoiding the pitfalls of overcommitment and offering a flexible commitment layer, we help businesses get the lowest rates on their AWS investments while also having the freedom to adapt to changing needs.
We take an automated continuous optimization approach to managing AWS Reserved Instances (RIs) and Savings Plans (SPs). We handle the intricacies of managing RIs and Savings Plans, allowing businesses to focus on what they do best.
Here’s how ProsperOps helps businesses approach AWS cost reduction:
- Making objective discount optimizations in real time to provide significant savings without any customer action required
- Providing autonomous renewals of Savings Plans (which otherwise have to be purchased or queued by a team member)
- Freeing customers up to focus on compute engineering optimizations while removing rate optimization work from their plate
- Automating prepayment amortization
- Reallocating savings with the Intelligent Showback feature.
To find out more about how we can optimize AWS costs and provide your finance and accounting teams with the intelligence needed to close your books, schedule a demo with ProsperOps today!
2. Right-size your instances
Rightsizing instances is a crucial aspect of AWS cost management. It involves adjusting your instance configurations to match the actual workload requirements, ensuring you’re not overpaying for unused capacity while maintaining performance.
How it works
Rightsizing ensures you’re using the most appropriate resources for your applications, neither over-provisioning nor under-provisioning. Over-provisioning leads to unnecessary costs as you pay for unused capacity, while under-provisioning can result in poor performance.
By analyzing your workload’s CPU, memory, and network usage patterns, you can identify instances that are either too large or too small for their tasks.
Adjusting to the right instance type ensures you only pay for what you really need, optimizing both performance and cost. Regularly reviewing and adjusting based on changing workloads ensures continuous efficiency.
3. Take advantage of Reserved Instances (RIs)
RIs are a billing concept provided by AWS that allows users to reserve compute capacity for a specified term in exchange for a big discount compared to standard on-demand AWS pricing.
How it works
RIs offer a reduced hourly rate (up to 75% off) compared to on-demand instance pricing. In exchange, you commit to using (and paying for) the instance for a one- or three-year term.
Since you commit to a specific term and rate with RIs, you have a predictable cost structure for that time. If your needs change, you can sell your unused RIs on the AWS Reserved Instance Marketplace.
While you commit to a specific instance type when purchasing a standard RI, AWS also offers Convertible RIs. These allow you to exchange one RI for another of equal or lesser value, giving you the flexibility to change instance families, sizes, operating systems, or tenancies.
4. Use Spot Instances for flexible applications
Spot Instances are a type of compute capacity offered by AWS that let you use its spare resources at significantly discounted rates compared to standard pricing.
How it works
You get to use spare Amazon EC2 computing capacity at a fraction of the regular price, but with the caveat that they can be terminated with little notice if that capacity is needed elsewhere.
This makes them ideal for workloads that can tolerate interruptions, such as stateless web servers, fault-tolerant applications, batch processing, or HPC clusters.
Clever use of Spot Instances can significantly reduce your AWS bills. You just bid on the spare capacity—and when your bid exceeds the standard pricing—you get the compute power. However, if the standard price goes above your bid or if you need the capacity elsewhere, AWS terminates your instance.
5. Leverage auto-scaling to match demand
AWS Auto Scaling is like having a thermostat for your cloud resources. Just as a thermostat adjusts the heating or cooling in a room based on the desired temperature, auto-scaling adjusts the number of resources based on demand.
How it works
When your application experiences increased traffic, auto-scaling automatically adds more instances to handle the load, ensuring smooth performance. Conversely, during periods of low traffic, it scales down by removing unnecessary instances. This dynamic adjustment, referred to as horizontal scaling, means you’re only using and paying for what you need at any given time.
By using auto-scaling, you avoid over-provisioning and paying for idle resources during off-peak times. At the same time, auto-scaling safeguards you against under-provisioning, which could lead to poor user experiences during traffic spikes. In essence, auto-scaling helps you achieve an optimal balance between performance and cost, ensuring you pay only for the resources you genuinely need based on real-time demand.
6. Optimize data transfers and storage
Optimizing data transfers and storage in AWS is pivotal for businesses aiming to manage their cloud expenses effectively.
How it works
Amazon S3 lifecycle policies let businesses automate the transition of data between different storage classes or even configure the bucket to delete objects after a specific duration. This ensures organizations aren’t incurring unnecessary costs for data that’s either obsolete or can be stored more cost-efficiently.
Complementing this is Intelligent Tiering, a feature designed to automatically shift data between two access tiers based on access patterns. This adjustment caters to datasets with fluctuating or unknown data access patterns, ensuring optimal storage costs.
When it comes to block storage, businesses can look toward gp3 volumes instead of defaulting to the pricier io1/io2 EBS volumes. Gp3 volumes offer a harmonious blend of cost and performance, catering to a wide array of workloads without breaking the bank.
For those exceptional scenarios demanding higher IOPS or throughput, RAID striping across multiple gp3 volumes can sidestep the need for the more expensive io1/io2 volumes.
Finally, a simple yet effective data transfer strategy that can help reduce AWS costs is consolidating non-critical or developmental workloads within a single Availability Zone (AZ). This approach curtails the costs associated with inter-AZ data transfers, ensuring data movement within the cloud doesn’t unnecessarily inflate expenses.
While the exact approach may differ from business to business, using a combination of these strategies to optimize your data transfer and storage systems can help you greatly reduce your cloud computing expenses.
7. Clean up unused or unattached resources
Over time, as projects evolve and needs change, AWS resources can accumulate after they are no longer in active use. These unused or unattached resources, while seemingly harmless, can lead to increased costs and a cluttered environment.
For instance, EC2 instances that were once crucial to a project might now be idle. Similarly, EBS storage volumes that were detached from various instances might still exist, incurring charges without serving a business purpose.
The same goes for data snapshots, custom machine images (AMIs), and even reserved IPs that are no longer associated with any active instance.
AWS’s cloud storage component, S3, can also become a repository of outdated or redundant data over time. Redundant or obsolete databases might also be running in the background, leading to unnecessary expenses and reduced value.
AWS resource management revolves around the continuous monitoring and periodic cleanup of these various resources. By ensuring they only retain necessary resources, businesses can optimize costs, streamline operations, and maintain a more efficient and effective cloud environment.
8. Avoid paid operating systems like Windows and RHEL
Using paid operating systems like Windows and RHEL can significantly increase the overall cost of running workloads in AWS. Windows and RHEL come with licensing costs that add to the hourly rate of the EC2 instance. Over time, these costs can accumulate, especially for businesses running multiple instances or for prolonged periods.
In contrast, Amazon Linux is free, eliminating any additional licensing fees. AWS also regularly updates it to address security vulnerabilities. Being a lightweight and optimized OS, Amazon Linux often delivers better performance compared to heavier operating systems. This can lead to faster application response times and better resource utilization.
While paid operating systems like Windows and RHEL have their merits in specific use cases, Amazon Linux offers a cost-effective, optimized, and seamless solution for businesses looking to reduce AWS costs. By eliminating licensing fees and providing a platform tailored for AWS, Amazon Linux ensures businesses can run their workloads efficiently without sacrificing value.
9. Implement anomaly detection
As cloud infrastructures grow and become more complex, the associated costs can become intricate and challenging to track manually. Human errors (like forgetting to terminate an EMR cluster after a batch job or accidentally copying TBs of EBS snapshots across regions) can lead to unexpected costs.
In a high-spend environment where monthly expenses can run into the millions, even significant cost spikes can get lost in the noise. Anomaly detection can identify unusual spikes in costs, such as those caused by a runaway lambda function or an inadvertently large data transfer. By catching these spikes early, businesses can take corrective actions before they escalate.
Anomaly detection systems, such as AWS Cost Anomaly Detection and AWS CUDOS, use machine learning to compare current costs against historical baselines. This means the system learns from past spending patterns and can detect subtle deviations that you might overlook in manual reviews.
Find out how ProsperOps can help you reduce your AWS costs today!
We designed ProsperOps to optimize and automate cloud spend management, specifically for Amazon Web Services (AWS). ProsperOps combines automation and performance-based pricing to offer a comprehensive solution for AWS cost management.
ProsperOps continuously optimizes your AWS Reserved Instance (RI) and Savings Plans portfolio, adjusting your reservations as needed to make sure you get the best possible savings.
ProsperOps also requires minimal effort, and once you’ve set it up, it takes over most of the day-to-day management and optimization tasks on AWS, allowing you to focus on other important aspects of your business.
Want to learn more? Sign up for a demo today!