EC2 cost optimization:15 ways to save on Amazon EC2

Introduction

The Challenge

15 Steps for Solution

Choosing Instance Families

• Use Case: An e-commerce platform team needs to host its product catalog on EC2 instances required high memory capacity to handle database operations efficiently. I consulted them to select instances from the memory-optimized R instance family, by doing this the platform achieves optimal performance and cost-effectiveness for its workload.
• Practical Steps: Evaluate application requirements, including CPU, memory, storage, and networking considerations. Utilize AWS Instance Selector tools and documentation to compare instance families and select the most suitable option based on workload characteristics.
• Useful Link

Reserved Instances

• Use Case: A Product Stream running a database server experiences consistent usage patterns with minimal fluctuation. By purchasing Reserved Instances for the specific instance type and term length matching the database server's requirements, they saved up to 75% compared to On-Demand pricing.
• Practical Steps: Analyze historical usage data to identify instances suitable for Reserved Instances. Opt for Standard RIs for steady-state workloads and Convertible RIs for flexibility in instance attributes.
• Useful Link

AWS Savings Plans

• Use Case: A SaaS provider hosts multiple microservices on EC2 instances, each with varying utilization patterns. By recommending them to purchase Compute Savings Plans, which offer flexibility across instance families and regions, they achieved significant savings compared to On-Demand pricing.
• Practical Steps: Analyze historical usage data to understand spending patterns and choose the appropriate Savings Plans type (Compute or EC2 Instance) based on workload characteristics and deployment models.
• Useful Link

Spot Instances

• Use Case: A data processing pipeline requires substantial computing power but can tolerate interruptions. By utilizing Spot Instances for batch processing tasks, the company reduces costs by up to 90% compared to On-Demand pricing.
• Practical Steps: Utilize Spot Fleet to diversify instance requests across different instance types, AZs, and pricing pools to improve availability and mitigate the risk of interruptions.
• Useful Link

AWS Graviton instances

• Use Case: A containerized microservices architecture requires cost-effective compute resources to handle variable workloads efficiently. By migrating containerized workloads to AWS Graviton-based EC2 instances, the company reduced costs without compromising performance.
• Practical Steps: Assess application compatibility with ARM architecture and verify performance benchmarks using AWS Graviton-powered instances. Migrate workloads gradually, starting with non-production environments, and monitor performance metrics to ensure compatibility and cost savings.
• Useful Link

Right Sizing

• Use Case: There was a web application hosted on EC2 instances. Initially, the application might be provisioned with larger instance types to accommodate potential growth. However, regular monitoring reveals that CPU and memory utilization rarely exceed 50%. By downsizing to a smaller instance type, such as switching from a m5.large to a t3.medium, they achieved significant cost savings without sacrificing performance.
• Practical Steps: Utilize AWS tools like CloudWatch to monitor instance metrics such as CPU utilization, memory usage, and network traffic. Rightsize instances based on observed utilization patterns to match workload requirements more closely.

AWS Instance Scheduler

• Use Case: A development team utilizes EC2 instances for testing and development purposes. By scheduling instances to start and stop during work hours only, they prevent unnecessary spending on idle resources outside of business hours.
• Practical Steps: Implement AWS Instance Scheduler, a solution that automates start and stop actions based on predefined schedules. Configure rules to apply to specific instances or tags, ensuring precise control over resource utilization.
• Useful Link

Elastic Load Balancing

• Use Case: An online marketplace experienced fluctuating traffic patterns with peak periods during promotional events. By deploying EC2 instances behind an Application Load Balancer (ALB) or Network Load Balancer (NLB), the marketplace ensured efficient traffic distribution, scalability, and cost optimization.
• Practical Steps: Provision an Application Load Balancer or Network Load Balancer using the AWS Management Console or AWS CLI. Configure target groups and health checks to route traffic to healthy instances dynamically. Monitor ELB metrics and adjust capacity settings based on traffic patterns to optimize resource utilization and cost efficiency.

Auto Scaling

• Use Case: An e-commerce website experienced fluctuating traffic throughout the day, with peak demand during specific hours. By configuring Auto Scaling to add or remove EC2 instances based on demand metrics, the company ensured optimal performance while minimizing costs during periods of low traffic.
• Practical Steps: Define scaling policies based on metrics such as CPU utilization, request latency, or custom application metrics. Set up CloudWatch alarms to trigger scaling actions automatically.

Monitoring and Optimization Tools

• Use Case: A financial services company deployed multiple applications on EC2 instances across different environments. By leveraging AWS Cost Explorer and Trusted Advisor, they gain visibility into resource usage, identify underutilized instances, and optimize costs proactively.
• Practical Steps: Set up Cost Explorer to analyze spending patterns by service, instance type, or usage type. Use Trusted Advisor recommendations to optimize performance, security, and cost based on AWS best practices.

Delete stopped instances

• Use Case: A development environment consisted of several EC2 instances used sporadically for testing. Over time, developers stop using some instances but forget to terminate them. By implementing a policy to automatically delete stopped instances after a defined period of inactivity, the company avoided paying for idle resources.
• Practical Steps: Set up AWS Lambda functions triggered by CloudWatch Events to identify and delete stopped instances based on predefined criteria, such as tags or instance state.

Hybernation Mode

• Use Case: A data analysis platform required extensive initialization processes and data loading upon instance startup. By enabling hibernation mode, the platform reduced startup time and avoids repeating resource-intensive initialization tasks, improving overall efficiency and cost-effectiveness.
• Practical Steps: Enable hibernation mode for compatible instance types using the AWS Management Console, AWS CLI, or AWS SDKs. Configure instance settings and storage options to ensure seamless hibernation and resume functionality.

EC2 Unnecessary Data Transfer

• Use Case: A multinational corporation operates EC2 instances in multiple AWS regions, resulting in significant cross-region data transfer costs. By consolidating resources within a single region and utilizing AWS Direct Connect for inter-region communication, the company reduced data transfer fees substantially.
• Practical Steps: Analyze data transfer patterns using AWS Cost Explorer and AWS CloudWatch metrics. Consolidate resources within the same region where feasible and leverage AWS Direct Connect or VPN connections to reduce cross-region data transfer costs.

Serverless Architectures

• Use Case: A web application relied on EC2 instances to handle user requests, resulting in significant infrastructure management overhead and operational costs. By migrating to a serverless architecture using AWS Lambda for compute, API Gateway for endpoint management, and DynamoDB for database storage, the company achieved cost savings and operational simplicity.
• Practical Steps: Assess application requirements and identify components suitable for serverless migration. Refactor code to leverage serverless services, optimize performance, and minimize costs. Utilize AWS SAM or the Serverless Framework for deployment and management automation.

Continuously Review and Refine

• Use Case: A DevOps team operates a multi-tier application on EC2 instances, continuously optimizing costs and performance based on evolving business requirements. By conducting regular cost reviews, monitoring usage trends, and refining optimization strategies, they ensure ongoing cost efficiency and resource optimization.
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Conclusion