AWS empowers users to manage their cloud expenses effectively while building scalable and modern applications. The wide range of services and pricing models offered by AWS allows for flexibility in cost management while maintaining desired performance and capacity.
AWS Cost Optimization encompasses various best practices and strategies for minimizing cloud spending without sacrificing performance or functionality.
Reserved Instances
For services like Amazon EC2 and Amazon RDS, reserving capacity in advance can lead to significant cost savings.
Reserved Instances can offer discounts of up to 72% compared to on-demand pricing.
There are three options for Reserved Instances: All Upfront (AURI), Partial Upfront (PURI), and No Upfront (NURI), allowing users to choose the payment structure that best fits their budget.
AWS Cost Explorer provides recommendations for purchasing Reserved Instances based on usage patterns for Amazon RDS, Amazon Redshift, Elastic ache, and OpenSearch Service, helping users optimize their reserved capacity investments.
Amazon EC2 Cost Savings
Amazon Spot Instances provide a cost-effective option for running fault-tolerant and flexible workloads at significantly reduced prices.
Compute Savings Plans offer savings for Amazon EC2, Faregate, and Lambda usage, providing a flexible way to reduce compute costs.
Sage Maker Savings Plans are designed to help reduce the cost of using Amazon Sage Maker for machine learning workloads.
Identifying and addressing underutilized EC2 instances is crucial for cost optimization. AWS Cost Explorer’s Resource Optimization feature helps users identify idle or low-utilization instances.
Stopping or downsizing these instances can significantly reduce costs. AWS Instance Scheduler automates the process of stopping instances, while AWS Operations Conductor can automatically resize instances based on recommendations from Cost Explorer.
Optimizing Database Costs
Identifying and managing underutilized Amazon RDS and Amazon Redshift instances is essential for cost optimization.
Trusted Advisor’s Amazon RDS Idle DB Instances check can identify DB instances without connections for the past seven days, which can be stopped to reduce costs.
Trusted Advisor’s Underutilized Redshift clusters check helps find clusters with low utilization that can be paused to save costs.
Analysing DynamoDB usage patterns can lead to cost savings. Monitoring Consumed Read Capacity Units and Consumed Write Capacity Units in CloudWatch helps users understand their usage patterns.
DynamoDB Auto Scaling automatically adjusts table capacity based on demand, optimizing cost and performance.
The DynamoDB on-demand option allows users to pay only for the read and write requests they use, offering cost-effective scalability.
Amazon EBS Volume Optimization
Low-activity Amazon EBS volumes can indicate underutilization. Trusted Advisor’s Underutilized Amazon EBS Volumes Check helps identify such volumes.
Creating snapshots of underutilized volumes and then deleting them can reduce costs. Amazon Data Lifecycle Manager can automate the snapshot creation process.
Amazon S3 Cost Optimization
Analysing Amazon S3 usage with Amazon S3 analytics helps identify opportunities for cost reduction. S3 analytics provides insights into storage access patterns and recommends using lower-cost storage tiers.
Lifecycle policies can automate the movement of objects to S3 Infrequently Accessed (S3 IA) or other lower-cost storage tiers.
S3 Intelligent-Tiering automatically moves objects to the most cost-effective storage tier based on access patterns, simplifying cost optimization.
Networking Cost Reduction
Identifying and deleting idle load balancers can reduce networking costs. Trusted Advisor’s Idle Load Balancers check helps find load balancers with low request counts.
Analysing data transfer costs using AWS Cost Explorer can provide insights into opportunities for reducing data transfer expenses.