This topic is also discussed in episode #013 of our Cloud & DevOps Pod
How to Reduce Your AWS Costs: Practical Tips for DevOps Teams
For businesses running on Amazon Web Services (AWS), it’s easy to get caught off guard by escalating cloud costs. One minute you're taking advantage of AWS’s incredible scalability and diverse service offerings, and the next you’re facing an unexpectedly high bill. Whether you’re a startup, small business, or enterprise, controlling AWS costs is critical to maintaining your bottom line. In this blog, we’ll explore some practical strategies to help you reduce your AWS expenses while keeping your infrastructure efficient.
Understanding the AWS Cost Problem
When you first sign up for AWS, you might receive credits through a startup accelerator or during a proof-of-concept (POC) phase. During this time, you probably aren’t paying close attention to costs because those credits are covering everything. But as soon as those credits run out, reality hits hard—suddenly, what seemed like "free" services can balloon into a significant monthly expense. It’s common for businesses to overlook monitoring their AWS usage early on, only to find out later that they’ve been running services that are more expensive than they realized. This is particularly true for services like Amazon Aurora, Redshift, or serverless offerings that may be overkill for smaller companies or startups.
Start with the Basics: Monitor Your Costs Early
The first step to reducing your AWS bill is to monitor your costs from the very beginning. Even if you’re using credits, AWS provides cost dashboards that allow you to see how much each service is costing you in real-time. This visibility is crucial for identifying potential overspending early on. For example, some businesses opt for Amazon Aurora because it's often recommended as a top-tier relational database service. However, Aurora is designed for large-scale, high-performance needs, which may not be necessary for a smaller operation. Instead, Amazon RDS with PostgreSQL could be a much more cost-effective option, especially for those who don’t need the full capabilities of Aurora.
Choose the Right Services for Your Needs
Another common pitfall is choosing AWS services that are more suited for enterprise-level operations when a smaller, more affordable option would suffice. One area where this frequently happens is with serverless technologies. While serverless databases, like Aurora Serverless are powerful and scalable, they can end up being more expensive than traditional instance-based databases for most workloads. If you’re running a database with consistent demand, it might be more cost-effective to use a small instance rather than relying on serverless architecture, which charges per request. Additionally, Redshift is a popular data warehousing service, but it’s not always the best fit for startups. Unless your company is heavily focused on data analytics and can afford the high costs associated with Redshift, it may be wise to explore more economical data storage options like Amazon S3 or RDS.
Leverage Reserved Instances and Savings Plans
Once you have a better understanding of which services you actually need, consider leveraging AWS Reserved Instances (RIs) or Savings Plans to lock in lower prices.
- Reserved Instances allow you to reserve EC2 instances for a one- or three-year period, providing significant discounts compared to on-demand pricing. These are especially useful if you know exactly what instance types you’ll be using for a long period of time.
- Savings Plans, on the other hand, offer more flexibility by allowing you to commit to a minimum amount of compute spend per hour without being tied to a specific instance type or region. This is a great option if you're still scaling or testing different services but want to reduce costs in the meantime.
The key is to review your current usage and forecast your future needs. If you’re not ready to commit to a specific instance family, a Savings Plan gives you more wiggle room while still saving money.
Optimizing Your Database Costs
Databases are often one of the biggest contributors to AWS bills, but there are ways to optimize them.
For example, Amazon DynamoDB offers two pricing models: on-demand and provisioned capacity. On-demand pricing is convenient for workloads with unpredictable traffic, but it’s far more expensive than provisioned capacity if your workload has consistent demand. By switching to provisioned capacity and reserving capacity for one or more years, you can significantly reduce costs.
Additionally, RDS instances running on ARM64 architecture can save you money. ARM-based instances are cheaper to run than x86-based instances, and they often provide better performance as well. If your application is already running on a MacBook or other ARM-based machine during development, switching to ARM instances in production should be seamless.
Avoid Unnecessary Service Duplication
One of the most common mistakes businesses make is duplicating services, which unnecessarily drives up costs. For instance, many organizations use both AWS CloudWatch and third-party tools like Datadog for logging and monitoring. While Datadog offers a user-friendly interface, it comes at a higher cost, especially when you’re already paying for similar functionality in CloudWatch. If you absolutely need Datadog or another third-party tool, consider sending logs and metrics directly to that service instead of duplicating them in CloudWatch. This approach can help reduce costs while still giving you access to the features you need.
Use the Right Architecture for Your Scale
AWS offers a wide range of services designed for different scales of operation. As a startup or smaller company, you don’t need to immediately jump to enterprise-level solutions like Kubernetes or Amazon SageMaker. Kubernetes, for example, offers flexibility and control, but it can quickly become expensive when you factor in the costs of managing multiple nodes, load balancers, and data storage. Instead, services like AWS Fargate or ECS provide managed container solutions that are easier to maintain and cheaper to run at smaller scales. Similarly, while SageMaker is great for large-scale machine learning models, you can often build and train models locally using a smaller instance and only move to a managed service when necessary.
Regularly Review Your Architecture
Finally, one of the most important things you can do to keep your AWS costs down is to regularly review your architecture. As your business grows, your AWS infrastructure will evolve, and services that were once essential may no longer be necessary. It’s easy to let unused resources pile up, leading to higher bills. Consider having an external architect review your infrastructure periodically. AWS offers free architectural reviews through programs like the Well-Architected Framework, which can help identify areas where you can reduce costs or improve performance.
Conclusion: Keep It Simple and Cost-Efficient
Reducing AWS costs doesn’t require a complete overhaul of your infrastructure. In fact, many cost-saving strategies are about simplifying what you already have. By choosing the right services, leveraging savings plans and reserved instances, avoiding service duplication, and regularly reviewing your architecture, you can significantly lower your AWS expenses while maintaining the performance and reliability your business needs.
For DevOps teams, keeping AWS costs under control is all about being mindful of the services you use and making sure you only pay for what you need. With a few simple adjustments, you can reduce your cloud spend and free up resources to focus on growing your business.
