Cost Optimization Techniques for AWS: Easy Wins Without Engineering Overhead
The current global economic atmosphere has caused businesses to become significantly cautious about their spending, especially the investments surrounding cloud and AWS.
This caution has resulted in a strategized and conscious practice of AWS cost optimization, where strategies, techniques, best practices, and tools help reduce cloud costs and aid in maximizing the business value of utilizing its power. However, optimizing cloud costs isn’t just about reducing costs; it’s also about aligning costs with business goals.
When it comes to spending, an increase in expenditures is never a problem if it is accompanied by a parallel increase in revenue. If the increased expenditures are not supported by profits, it’s a cue to reassess strategy and analyze the areas of improvement. The first step and one of the most important goals, is to ensure that costs correlate with productive and profitable activities.
If you are currently reassessing your strategies surrounding cloud spending, to encourage more profits, this blog will suggest the right modifications and focus on improving price-to-performance while handling engineering overheads, significant time investment, and large planning cycles. Let’s dig in!
Understanding AWS Cost Structures
A curious number of businesses remain unaware of AWS cost structures and what root causes explain magnified expenses. Hence, before leaping on how to win it all without engineering overheads, let’s cover the basics!
AWS Pricing Models
In order to fully understand AWS cost optimization techniques first understanding the different pricing models it offers is a mandatory protocol. There are three most prominent AWS pricing models every business must know.
1. On-Demand Instances
In this model, you pay for computing capacity per hour or second based on your chosen instances. No upfront payments are needed. You can increase or decrease your computing capacity to meet your application’s demands and only pay for the instance you use.
- Users who prefer low-cost and flexible EC2 Instances without upfront payments or long-term commitments.
- Enterprises looking to increase or decrease computing capacity per the application’s demands.
2. Spot Instances
Amazon EC2 Spot Instances offer unused EC2 capacity in the AWS cloud at up to a 90% discount compared to On-Demand prices. The Spot price fluctuates periodically based on supply and demand, supporting per-hour and per-second billing plans.
- Applications with flexible start and end times or urgent computing needs for large-scale dynamic workloads.
3. Reserved Instances
This model allows enterprises to capacity reservations in specific Availability Zones, making it great for applications with predictable workloads. Customers can reduce their overall computing costs by committing to using EC2 over a 1- or 3-year term. Plus, the flexible pricing model offers low prices on EC2.
- Organizations with a higher computing capacity looking for cost-effective options as a whole.
Check out the AWS cost calculator to create estimations per your business for specified details. You can choose any plan resources needed for your organization.
AWS Cost Components
Now the probing question is, how can AWS help customers lower costs with the best cost optimization techniques? The answer to it is linked with understanding AWS cost components first!
When using AWS, three main factors affect cost: computing, storage, and outbound data transfer. These factors can vary depending on the business’s specific AWS product and pricing model. Typically, there are no charges for inbound data transfer between other AWS services within the same Region. However, there may be exceptions, so verifying data transfer rates before getting started is important.
Remember! The more data you transfer, the lower the cost per GB. As for compute resources, you are charged by the hour or second from the time you launch a resource until you stop or terminate it. If you have made a reservation, the cost is agreed upon beforehand.
For data storage and transfer, you typically pay per GB. AWS prices do not include applicable taxes and duties, such as value-added and sales tax.
Tapping the Unknown AWS Environment
For the majority of businesses, the AWS environment is unknown. For this reason, they commit serious mistakes, spend more and receive weaker results.
To effectively manage your AWS costs and usage, it’s essential to have a general understanding of your environment’s efficiency.
- One helpful tool to achieve this is AWS Cost Explorer, which provides an easy-to-use interface that allows you to visualize and manage your costs over time. By creating custom reports with Cost Explorer, organizations can identify areas for cost optimization.
- Another helpful feature within Cost Explorer is the ‘Rightsizing recommendations,’ which helps to identify cost-saving opportunities by downsizing or terminating underutilized instances in Amazon EC2. This feature provides a single view across member accounts, making identifying potential savings on your overall AWS spending easier.
- Lastly, AWS Trusted Advisor is another excellent AWS cost optimization tool for finding such opportunities. It can perform various checks, highlighting underutilized Amazon EBS Volumes and idle Amazon RDS DB instances. To effectively reduce waste within your AWS footprint, reviewing these tools at least quarterly is recommended.
AWS Cost Optimization Checklist
So far, we have covered AWS’s pricing models and cost components. Once businesses understand these, navigating through the cost optimization phase becomes easier. As per Amazon Web Services, there are 3 tried-and-tested ways enterprises can optimize their cost without engineering overheads.
By implementing these changes, experts predict businesses can witness 10% to 20% cost optimization overnight!
Modernizing Amazon EBS (Elastic Block Store) Volumes
Are you interested in optimizing your Amazon EBS volumes to save up to 20% on expenses? Consider upgrading from GP2 to GP3 volumes. By doing so, you enjoy cost savings and the flexibility to provision IOPS separately from your volume storage. This means you can further optimize your Amazon EBS volumes, especially for GP2 workloads requiring large volume sizes to meet IOPS requirements. And the best part? Upgrading to GP3 volumes won’t cause downtime since you can use Amazon EBS Elastic Volumes.
With Elastic Volumes, you can adjust your volume size, performance, and type without detaching the volume or restarting the instance. Plus, all the latest-generation instances support Amazon EBS Elastic Volumes. You can be confident that your volume performance will stay below your original source volume. So, consider upgrading to GP3 volumes today and enjoy the benefits of cost savings and flexibility.
Assumptions with Amazon EBS
What will the outcomes be with 150 individual 1 TB GP2 Volumes making 3,000 IPS?
Result for Better Cost Optimization
The assumptions and analysis display the potential regular and yearly savings at par by transitioning from GP2 volumes to GP3 volumes monthly.
Swapping Out Underlying Compute Mechanisms
Once you have upgraded your Amazon EBS volumes, it’s time to optimize Amazon RDS and Amazon Aurora setups for maximum performance. The beauty of AWS-managed services is that enterprises can rely on AWS to handle their cloud resources, in part or in full. This means that AWS will take care of the software’s maintenance, performance, and operability, allowing them to focus on what matters.
If you use Amazon Aurora PostgreSQL Compatible Edition or Amazon Aurora MySQL Compatible Edition, you can leverage AWS Graviton2-based database instances. This is brilliant because Graviton2 instances offer up to a 20% performance improvement and up to 35% price-performance improvement for Aurora, depending on the size of your database. For RDS open-source databases, Graviton2 instances provide up to a 35% performance improvement and a 52% price-performance improvement.
So, what will be the implementation ground while carefully handling the AWS cost optimization pillars? Upgrading an Aurora database instance to Graviton2 is a straightforward process. If your database version is supported, simply modify your instance type, and your application will continue to work seamlessly without requiring changes to your code. On the other hand, for Amazon RDS, you can navigate to the Amazon RDS console, select your database, and click on the modify option. Then, select the Graviton2-based instance that best meets your computational requirements. During the modification process, there will be a brief service interruption. The modification will be applied by default during your next scheduled maintenance window.
By upgrading Amazon EBS volumes, organizations can optimize their Amazon RDS and Amazon Aurora setups. And AWS-managed services with the powerful Graviton2 instances can handle the cloud infrastructure more efficiently, reliably, and cost-effectively than ever before.
Assumptions with Underlying Computing
What will the outcomes be with 25 Amazon Aurora db.r5.2x instances alongside 25 Amazon RDS for MySQL db.r5.2xlarge instance?
Result for Better Cost Optimization
The assumptions and analysis display the potential monthly and yearly cost reductions when using Graviton-based computing for backing up your Aurora and RDS databases.
Migrating Linux-based Workloads to EC2
Discover an effective cost optimization technique for your Linux-based workloads with Graviton2-based Amazon EC2 instances. If you don’t require the x86-based chip architecture, you can save a lot by switching to 64-bit Arm processors. Don’t worry about the effort needed to port an application; it’s worth it!
Organizations can easily find better-priced performance-based instances using the AWS cost calculator by analyzing their Amazon EC2 Linux-based workloads and specific instance types. They must input their computing requirements, including Memory, vCPU, Networking, and more, and identify potential cost savings.
Switching to Amazon EC2 M6g, C6g, and R6g instances can save you up to 40% compared to current generation M5, C5, and R5 instances. The benefits are significant, and you’ll be amazed by the improved performance and cost savings.
Assumptions with Linux-Based Migration
With 25 x t3.large instances, 25 x c5.xlarge instances, 25 x r5.xlarge instances, and 25 x m5.2xlarge instances, what will be the outcome?
Businesses can witness potential monthly and yearly savings by moving to Linux-based workloads and Graviton-based Amazon EC2.
Cost Optimization Without Extensive Overheads – At A Glance
Many companies find it challenging to establish the right balance between performance and cost efficiency. You can take a few simple steps to optimize costs on AWS without doing too much engineering work. Let’s evaluate some quick and practical techniques to help you reduce your AWS expenses and get the most out of your investment.
· Right Sizing Resources
To effectively manage AWS cost optimization, right-size your resources. Identify usage patterns, downsize underused instances, or switch to more economical options like reserved or spot instances. Use AWS cost optimization tools like Trusted Advisor and Cost Explorer to help analyze usage and make informed choices.
· Charms of Auto-Scaling
Another cost optimization technique without engineering overhead comes with auto-scaling and load balancing. These tools adjust resource capacity based on demand and distribute traffic evenly across instances. This improves app performance and availability while preventing overprovisioning. Plus, scaling down during low-demand periods helps reduce costs.
· AWS Cost Explorer and AWS Budget Saving It All!
AWS provides cost management tools like AWS Cost Explorer and AWS Budgets to help you save money and stay on top of your expenses. With these tools, you can analyze your AWS costs over time, set custom budgets, and receive alerts when you’re close to reaching those limits.
· Implementing Cost-Effective Storage Solutions
Consider using Amazon S3 Glacier for long-term archiving and data backup to reduce storage costs. With lower storage costs compared to standard S3 storage classes, it’s a cost-effective option. Data lifecycle policies can also help automatically transfer infrequently accessed data to lower-cost storage tiers. You can effectively reduce AWS storage expenses by selecting appropriate storage options based on data access patterns.
· Monitoring Data Transfer Associated Costs
Don’t forget about data transfer costs – they can accumulate fast. Monitor your usage and consider using CDNs or caching to save money. AWS Direct Connect is another option for dedicated connections and better performance.
· The Perfect Combo – AWS Spot Instances & Reserved Instances
As mentioned earlier, AWS pricing models, especially Spot Instances and Reserved Instances, can save much money. Spot Instances let you bid on unused EC2 instances for flexible workloads. Reserved Instances give significant discounts for stable workloads. Use these models to reduce costs without compromising performance.
Forget Engineering Overheads with Ninja Cost Optimization Techniques!
Optimizing AWS costs doesn’t always involve complex engineering efforts or sacrifices in performance. By implementing these easy-win techniques and AWS cost optimization tools, you can progress significantly toward cost efficiency without overwhelming your engineering team. From right-sizing resources and leveraging auto-scaling to utilizing cost management tools and taking advantage of cost-effective storage and instance options, there are numerous strategies you can employ to optimize costs on AWS.
Continuously monitor and refine your approach, and ensure that your AWS infrastructure remains cost-effective and high-performing, resulting in a more efficient cloud environment and improved return on investment.
Contact NETSOL today to get help and assistance with AWS cost optimization solutions!