Real Stories of Cost Optimization on AWS
In this post, we will unveil best practices and real-life customer sagas where businesses harnessed the power of AWS to supercharge their savings
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- Establish a FinOps Practice: Create a framework for managing cloud costs that includes budget planning, forecasting, and cost allocation. Empower teams to make informed trade-offs between cost, speed, and quality.
- Use AWS Budgets and Cost Anomaly Detection: Set up budgets to monitor and manage costs in real time, and detect anomalous spending patterns before they escalate.
- Implement Tagging Strategies: Adopt a comprehensive resource tagging strategy for cost attribution and accountability. This helps identify cost drivers by team, project, or environment.
- Leverage AWS Cost Management Tools: Utilize tools such as the AWS Cost Explorer, AWS Billing Console, and Trusted Advisor to analyze spending patterns, set alerts, and take corrective actions.
- Enable AWS Cost Explorer and Reports: Use the AWS Cost Explorer to visualize cost and usage trends over time. Dive into granular details, such as service-level spending or account-level charges.
- Set Up Detailed Billing and Resource Grouping: Enable detailed billing with cost and usage reports for a comprehensive breakdown of your expenses. Use resource grouping to aggregate costs by function or team.
- Monitor Reserved Instance and Savings Plan Utilization: Ensure your reserved resources are being utilized optimally. Regularly review commitment-based plans to align with usage patterns.
- Educate Teams on Cost Awareness: Foster a culture where teams actively monitor their resource usage and take steps to eliminate waste.
- Leverage Spot Instances: Take advantage of AWS Spot Instances for fault-tolerant and flexible workloads, such as batch processing and big data analysis, to achieve significant savings.
- Right-Sizing Resources: Regularly assess your EC2 instance types, storage volumes, and database configurations to ensure they match workload requirements. Avoid over-provisioning.
- Use Managed Services: Shift to AWS-managed services like Amazon RDS, AWS Lambda, or Amazon ECS to minimize operational overhead and reduce costs.
- Employ Storage Tiering: Use storage classes such as Amazon S3 Intelligent-Tiering or Glacier for data that doesn’t require frequent access.
- Implement Auto-Scaling: Use AWS Auto Scaling to dynamically adjust compute and storage resources based on real-time demand. This prevents under-utilization and reduces over-provisioning costs.
- Leverage Queue-Based Architectures: For workloads with variable traffic, queue-based systems like Amazon SQS can help smooth out demand spikes and ensure efficient resource utilization.
- Use Predictive Scaling: Take advantage of AWS predictive scaling to anticipate future demand based on historical data and adjust resources proactively.
- Schedule Resource Usage: Identify non-critical workloads and schedule their usage during off-peak hours using AWS Instance Scheduler or EventBridge rules.
- Regularly Review and Refactor: Conduct periodic reviews of your architecture using AWS Well-Architected Tool to identify cost optimization opportunities. Refactor workloads to take advantage of new AWS services and pricing models.
- Adopt Elastic and Serverless Architectures: Serverless solutions like AWS Lambda and managed services like Fargate allow you to pay only for what you use, reducing costs over time.
- Monitor and Adapt to New AWS Features: Stay updated with AWS announcements to leverage new features or services that could offer cost benefits.
- Optimize Data Transfer Costs: Minimize cross-region data transfers by architecting for locality and using Amazon CloudFront for caching and delivery.
We also set up AWS Cost and Usage reports to provide granular insights into Cost and Usage, and we were able to identify the key driver behind the cost increase. This proactive approach allowed the company to identify and address cost anomalies in real-time, saving them thousands of dollars. Additionally, it helped the customer gain visibility into escalating Compute and Database costs. AWS Trusted Advisor is a service that inspects your AWS environment and provides recommendations for optimizing your resources. For one of our largest social media customers, we utilized AWS Trusted Advisor, which identified Underutilized and Idle resources that could potentially be terminated savings the customer $200k monthly across Amazon EC2, EBS, RDS and Load Balancers. Furthermore, the tool also provided recommendations around. Lastly with AWS Compute Optimizer, the customer was able to uncover $60k in monthly savings achieved through EC2 Rightsizing recommendations.
Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.