AWS offers unmatched flexibility and scaleability, but its pay-as-you-go model can quickly rack up significant costs if you’re not careful. However, with strategic planning and a deeper understanding of cost management tools, you can reduce your cloud bill by up to 50%, if not more.
In this blog, we’ll explore not just the strategies but also the insights and nuances behind them, helping you gain mastery over AWS cost optimization.
1) Utilize Savings Plans for Long-Term Commitments
AWS Savings Plans provide a way to secure significant discounts by committing to a fixed usage level over a 1- or 3-year term. While the savings can reach up to 72% compared to On-Demand pricing, the true power of Savings Plans lies in their flexibility.
Why They Work:
- Wide Applicability: Savings Plans apply not just to EC2 instances but also to services like AWS Lambda and AWS Fargate, offering savings across multiple compute resources.
- Operational Flexibility: You can switch instance families, regions, or operating systems without losing the benefits, making them far more versatile than Reserved Instances.
A Real-Life Scenario:
Let’s say your organization runs multiple EC2 instances for a production workload, consuming 500 vCPUs consistently. At On-Demand pricing, this might cost $10,000 per month. By committing to a Savings Plan for 3 years, you can slash this cost to about $3,000 per month, freeing up $7,000 for other initiatives.
Insider Tips:
- Use AWS Cost Explorer to review past usage trends and identify the right commitment level.
- Start small. If you’re unsure of future growth, opt for a partial commitment and scale up as confidence grows.
2) Rightsize Instances to Match Actual Workloads
Many organizations fall into the trap of over-provisioning resources, running larger or more powerful instances than necessary. Rightsizing is the process of aligning resource allocation with actual usage patterns.
Beyond the Basics:
AWS Compute Optimizer can identify underutilized or over-utilized instances. But what happens next? Dive deeper into understanding your workload. For example:
- CPU-Intensive Applications: If CPU utilization rarely exceeds 20%, consider switching from an M6a instance to a smaller T4g instance, which offers burstable performance for less cost.
- Memory-Bound Applications: For databases or in-memory caches, select R instances designed for high memory workloads.
Example:
An e-commerce company using an m5.4xlarge instance for their web application might notice through monitoring that peak traffic only consumes 30% of CPU capacity. Downgrading to an m5.2xlarge reduces the monthly cost by 50% without affecting performance.
Pro Tip:
Don’t stop at EC2. Rightsize RDS databases, EBS volumes, and even load balancers. For example, scaling down provisioned IOPS on underutilized EBS volumes can result in significant savings.
3) Automate Cost Savings with S3 Intelligent-Tiering
Amazon S3 Intelligent-Tiering is more than just a storage class; it’s an intelligent solution that uses machine learning to optimize costs based on data access patterns.
Insights You Might Miss:
- No Retrieval Fees: Unlike S3 Standard-IA or Glacier, Intelligent-Tiering doesn’t penalize you with retrieval fees when accessing infrequently used data.
- Granular Tiers: Intelligent Tiering supports additional deep archive tiers for long-term, rarely accessed data, driving even deeper cost efficiencies.
Example in Action:
A media company stores high-resolution videos in S3 for streaming. While recent uploads are accessed frequently, older content sees declining usage. With Intelligent Tiering, AWS automatically transitions these files from the Frequent Access tier to Infrequent Access, and eventually to Archive, as the usage declines.
Pro Tip:
Enable Intelligent-Tiering with Lifecycle Policies to optimize costs across data lifecycles automatically.
4) Turn Off Idle Resources with Proactive Monitoring
Idle resources are one of the most pervasive sources of waste in AWS. From forgotten development environments to underused EC2 instances, they quietly accumulate costs.
Go Beyond Simple Audits:
While AWS Trusted Advisor is an excellent starting point, integrate monitoring tools like CloudWatch Alarms or third-party solutions (e.g., Datadog) to alert you in real time about unused or low-usage resources.
Creative Example:
Imagine a testing environment that requires EC2 instances during business hours but remains idle overnight. By automating the shutdown of these instances using Lambda or Instance Scheduler, you can save up to 70% of associated costs.
How to Automate:
- Use AWS Lambda to trigger scripts that turn off resources at specified times.
- Implement Auto Scaling Groups with proper scaling policies to spin up resources only when needed.
5) Replace Always-On Resources with Event-Driven Lambda Functions
AWS Lambda, with its serverless architecture, charges you only for the compute time used, making it a highly cost-effective alternative for intermittent or unpredictable workloads.
Beyond the Obvious:
Replacing EC2 instances with Lambda isn’t just about cost — it’s about agility. Lambda scales seamlessly with demand, eliminating the risk of over-provisioning.
Deep-Dive Use Case:
Consider a log-processing application that parses and analyzes logs uploaded to an S3 bucket. Running this on an EC2 instance incurs constant costs, even when logs aren’t being uploaded. By switching to Lambda, each log upload triggers the processing function, reducing costs to just a fraction of the EC2 equivalent.
Pro Tips for Maximizing Lambda Efficiency:
- Use Provisioned Concurrency for predictable workloads to avoid cold starts.
- Offload non-critical functions to asynchronous invocations to reduce runtime costs.
Note: Understand the frequency of logs that you are receiving. Decide based on this.
Additional Strategies to Push Savings Further
- Spot Instances for Batch Workloads: Use Spot Instances for non-critical tasks like testing or batch processing. These can be up to 90% cheaper than On-Demand instances.
- Use Consolidated Billing and Resource Sharing: Aggregate usage across accounts within an AWS Organization to benefit from volume discounts.
- Explore Cost Allocation Tags: Enable tags to categorize and analyze spend by department, project, or environment, helping you identify wasteful practices.
Disclaimer:
The strategies and tips shared in this blog are based on my personal experience, understanding, and research while learning and exploring AWS cost optimization techniques. Please note that every organization’s requirements and workloads are unique, and not all recommendations may apply universally.
I encourage you to analyze your specific use case, validate these insights, and adapt them to your needs for the best results. Optimization is a continuous journey, and I tried to share what I’ve learned so far.
Conclusion
AWS cost optimization is not a one-time effort but an ongoing practice. By understanding the intricacies of Savings Plans, rightsizing, storage tiers, idle resource management, and serverless computing, you can unlock significant savings while maintaining a robust cloud infrastructure. Start small, measure the impact of each change, and iterate as your workloads evolve. With the strategies shared in this blog, you’re well on your way to cutting your AWS costs in half — or even more. You may also like this article
Remember, every dollar saved on cloud infrastructure is a dollar that can be reinvested into innovation and growth!
