Right Sizing is an Ongoing Process
Right sizing is the process of matching instance types and sizes to your workload performance and capacity requirements at the lowest possible cost. It’s also the process of looking at deployed instances and identifying opportunities to eliminate or downsize without compromising capacity or other requirements, which results in lower costs.
Right sizing is a key mechanism for optimizing AWS costs, but it is often ignored by organizations when they first move to the AWS Cloud. They lift and shift their environments and expect to right size later. Speed and performance are often prioritized over cost, which results in oversized instances and a lot of wasted spend on unused resources.
Identifying Opportunities to Right Size
Right sizing is the most effective way to control cloud costs. It involves continually analyzing instance performance and usage needs and patterns—and then turning off idle instances and right sizing instances that are either overprovisioned or poorly matched to the workload. Because your resource needs are always changing, right sizing must become an ongoing process to continually achieve cost optimization. You can make right sizing a smooth process by establishing a right-sizing schedule for each team, enforcing tagging for all instances, and taking full advantage of the powerful tools that AWS and others provide to simplify resource monitoring and analysis.
EC2 instance types
Amazon EC2 provides a wide selection of instance types optimized to fit different use cases. Instance types comprise varying combinations of CPU, memory, storage, and networking capacity and give you the flexibility to choose the appropriate mix of resources for your applications. Each instance type includes one or more instance sizes, allowing you to scale your resources to the requirements of your target workload.
AWS storage classes
Amazon S3 offers a range of storage classes designed for different use cases. These include S3 Standard for general-purpose storage of frequently accessed data; S3 Intelligent-Tiering for data with unknown or changing access patterns; S3 Standard-Infrequent Access (S3 Standard-IA) and S3 One Zone-Infrequent Access (S3 One Zone-IA) for long-lived, but less frequently accessed data; and Amazon S3 Glacier (S3 Glacier) and Amazon S3 Glacier Deep Archive (S3 Glacier Deep Archive) for long-term archive and digital preservation.
RDS instance types
Amazon RDS provides a selection of instance types optimized to fit different relational database use cases. Instance types comprise varying combinations of CPU, memory, storage, and networking capacity and give you the flexibility to choose the appropriate mix of resources for your database. Each instance type includes serveral instance sizes, allowing you to scale your database to the requirements of your target workload.
Are you looking for more ways to optimize your compute resources?
Learn how AWS Cost Explorer and AWS Compute Optimizer recommendations can help you identify opportunities to modify your instances and save money.
AWS Cost Explorer
AWS Cost Explorer helps you identify under-utilized EC2 instances that may be downsized on an instance by instance basis within the same instance family, and understand the potential impact on your AWS bill by taking into account your RIs and Savings Plans.
AWS Compute Optimizer
AWS Compute Optimizer gives downsizing recommendations within or across instance families, upsizing recommendations to remove performance bottlenecks, and recommendations for EC2 instances that are parts of an Auto Scaling group.
Ready to get started?
Monitor and analyze your usage to gain insight into instance performance and usage patterns.
Instantly get access to tips to help you right size your EC2 instances and RDS DB instances.
Learn more with AWS Architecture Center, whitepapers, blogs, videos, and more.