Quick AWS Cost Savings Tactics You Can Implement
Cloud computing has become an indispensable tool for organizations striving to maintain their edge. Among the leading cloud service providers, Amazon Web Services (AWS) stands tall, offering unparalleled features and scalability. Yet, harnessing the full potential of AWS requires more than just an initial investment; it demands a continuous commitment to optimizing costs.
As a C-suite executive, you may be wondering how to navigate the intricacies of AWS cost management. How can your organization strike the perfect balance between operational efficiency and fiscal responsibility? How can you ensure that every dollar spent on AWS is a dollar well-invested?
In this blog post, we’ll address these questions and more, exploring the benefits of building a Cost Optimization culture within your business.
We’ll delve into strategies for AWS cost optimization and how they play a pivotal role in enhancing financial prudence and operational efficiency.
Chapter 1 - Elasticity - Scale and schedule your services based on your expected utilization pattern and needs
Implementing elasticity on Amazon Web Services (AWS) is a strategic approach that allows businesses to dynamically scale and schedule their services based on expected utilization patterns and needs. Core chapter sections are:
- Auto scaling
- AWS Lambda
- Databases
- Instance scheduler
- Spot instances
Elasticity is a core principle of cloud computing, enabling organizations to adapt their resources in real-time to meet changing demands, ensuring both cost-efficiency and performance optimization.
Auto Scaling
To start with, AWS offers Auto Scaling, a service that automatically adjusts the number of compute resources in response to changing application demand. By setting predefined metrics and thresholds, such as CPU usage or network traffic, Auto Scaling can scale out (add more resources) to handle spikes in demand, and scale in (remove resources) during quieter periods.
This means businesses pay only for the resources they use, avoiding the costs associated with over-provisioning.
AWS Lambda
AWS Lambda is another service that exemplifies elasticity. It allows businesses to run code without provisioning or managing servers, charging only for the compute time consumed. With Lambda, code execution scales automatically with the size of the workload, from a few requests per day to thousands per second, making it an ideal solution for unpredictable or sporadic workloads.
Databases
For database needs, Amazon RDS (Relational Database Service) and Amazon DynamoDB offer elastic solutions. RDS makes it easy to set up, operate, and scale a relational database in the cloud with resizable capacity. Similarly, DynamoDB, a NoSQL database service, offers fast and predictable performance with seamless scalability, adjusting throughput capacity in response to actual workload activity.
AWS Instance Scheduler
Scheduling is also an important part of elasticity. AWS provides tools like AWS Instance Scheduler to automate the start and stop times of instances
This is particularly useful for resources that are not required to run 24/7, such as development or test environments, allowing businesses to reduce costs by turning off resources when they are not in use.
Spot Instances
Spot Instances offer a compelling opportunity for businesses to maximize cost savings on AWS while maintaining high computational capacity. These instances provide access to unused AWS capacity at significantly reduced prices, often up to 90% lower than on-demand rates. This makes Spot Instances an excellent choice for applications that can tolerate interruptions, such as batch processing, data analysis, and testing environments. To enable Spot Instances, businesses can simply specify their preferences when launching EC2 instances, including the maximum price they are willing to pay per hour.
AWS then fulfills these requests when spare capacity is available.
Chapter 2 - Instance & Capacity Planning
Effective planning requires a thorough understanding of the application's requirements, such as CPU, memory, storage, and network capabilities. Businesses must analyze historical usage data and predict future demand to make informed decisions. Tools like AWS Cost Explorer and AWS Trusted Advisor can assist in this process by providing insights into resource utilization and recommendations for cost optimization.
Chapter 3 - S3 Intelligence Tiering
S3 Intelligent Tiering is a game-changer for businesses looking to optimize their cloud storage costs and efficiency.
This AWS feature automatically moves data to the most cost-effective access tier based on usage patterns, without performance impact or operational overhead.
For businesses dealing with vast amounts of data, this means significant savings, as data that is infrequently accessed is moved to lower-cost tiers, reducing storage costs.
Furthermore, S3 Intelligent Tiering eliminates the need for manual data analysis and movement, enabling businesses to focus on core activities rather than complex data management tasks. This automated tiering solution adapts to changing access patterns, making it ideal for unpredictable or evolving data usage. In summary, S3 Intelligent Tiering is crucial for businesses looking to achieve a balance between accessibility, performance, and cost in their data storage strategy.
Chapter 4 - Savings Plans
AWS Savings Plans offer a significant opportunity for businesses to reduce their cloud computing costs with flexibility and ease. These plans allow companies to commit to a consistent amount of compute usage (e.g., $10 per hour) for a 1 or 3-year period, in exchange for a lower rate compared to on-demand pricing. This commitment translates into substantial savings, making it an essential strategy for businesses with predictable workload patterns.
To enable Savings Plans, businesses first analyze their usage patterns via the AWS Cost Explorer, then select the appropriate plan based on their compute needs and budget. Once enabled, the savings are automatically applied to a wide range of AWS services, providing both cost efficiency and flexibility. This makes AWS Savings Plans an invaluable tool for organizations looking to optimize their cloud spending while maintaining operational agility.
https://docs.aws.amazon.com/sa...
- Compute Savings Plans provide the most flexibility and prices that are up to 66 percent off of On-Demand rates. These plans automatically apply to your EC2 instance usage, regardless of instance family (for example, m5, c5, etc.), instance sizes (for example, c5.large, c5.xlarge, etc.), Region (for example, us-east-1, us-east-2, etc.), operating system (for example, Windows, Linux, etc.), or tenancy (for example, Dedicated, default, Dedicated Host). They also apply to your Fargate and Lambda usage. With Compute Savings Plans, you can move a workload from C5 to M5, shift your usage from EU (Ireland) to EU (London), or migrate your application from Amazon EC2 to Amazon ECS using Fargate at any time. You can continue to benefit from the low prices provided by Compute Savings Plans as you make these changes.
- EC2 Instance Savings Plans provide savings up to 72 percent off On-Demand, in exchange for a commitment to a specific instance family in a chosen AWS Region (for example, M5 in Virginia). These plans automatically apply to usage regardless of size (for example, m5.xlarge, m5.2xlarge, etc.), OS (for example, Windows, Linux, etc.), and tenancy (Host, Dedicated, Default) within the specified family in a Region.
With an EC2 Instance Savings Plan, you can change your instance size within the instance family (for example, from c5.xlarge to c5.2xlarge) or the operating system (for example, from Windows to Linux), or move from Dedicated tenancy to Default and continue to receive the discounted rate provided by your EC2 Instance Savings Plan. - SageMaker Savings Plans provide savings up to 64 percent off of On-Demand rates. These plans automatically apply to your SageMaker instance usage regardless of instance family (for example, ml.m5, ml.c5, etc.), instance sizes (for example ml.c5.large, ml.c5.xlarge, etc.), Region (for example, us-east-1, us-east-2, etc.), and component (for example, Notebook, Training, etc.).
With SageMaker Savings Plans, you can move a workload from ml.c5 to ml.m5, shift your usage from Europe (Ireland) to Europe (London), or migrate your usage from Training to Inference at any time and continue to receive benefits.
Cost Optimization Closing Thoughts
In conclusion, mastering AWS cost optimization is not just a technical exercise; it's a strategic imperative. At Three Ventures, we understand the intricacies of AWS and are poised to guide you through optimizing your cloud investment. Whether it's elasticity, capacity planning, intelligent tiering, or savings plans, our expertise is your asset. Reach out to us, and let's ensure your AWS journey is both cost-effective and operationally sound.
