AWS Spot Instances: The Secret to Reducing Your Cloud Bill by Up to 90%

AWS Spot Instances allow users to take advantage of unused EC2 capacity in the AWS cloud at significantly reduced rates compared to On-Demand prices. By bidding on spare computing capacity, organizations can lower their AWS costs substantially. However, because Spot Instances can be interrupted with just a two-minute notice when AWS needs the capacity back, they are best used for specific types of workloads that can tolerate such interruptions. This blog post explores how companies can leverage Spot Instances to save money, highlights common pitfalls and how to avoid them, and shares realistic cost savings examples with estimated dollar amounts.

Understanding Spot Instances

What are Spot Instances?

Spot Instances are an AWS offering that allows you to purchase unused EC2 computing capacity at reduced rates. The price of Spot Instances fluctuates based on supply and demand, but it typically offers savings of up to 90% compared to On-Demand Instance prices. These instances are ideal for workloads that can be interrupted or that have flexible start and end times.

How do Spot Instances Work?

Users bid for Spot Instances by specifying the maximum price they are willing to pay per hour. If the bid exceeds the current spot price, the instance runs until either the user terminates it or the spot price exceeds the bid, at which point the instance is automatically stopped or terminated by AWS.

Comparison with On-Demand and Reserved Instances

• On-Demand Instances: Charged at a fixed rate per hour without any long-term commitment. Best for workloads with unpredictable usage patterns.
• Reserved Instances: Offer significant savings over On-Demand pricing in exchange for a commitment to use the instance for a one or three-year term. Ideal for steady-state workloads.

Common Use Cases for Spot Instances

1. Batch Processing Jobs

Batch processing jobs, such as image or video processing, data transformations, and scientific simulations, are ideal for Spot Instances. These jobs are typically flexible in terms of start and end times and can be interrupted without significant consequences. By leveraging Spot Instances, companies can process vast amounts of data at a fraction of the cost of On-Demand Instances.

2. Development and Testing Environments

Development and testing environments offer another perfect scenario for utilizing Spot Instances. These environments are often required for a limited period and can tolerate interruptions, making them suitable for Spot Instances. Developers can use Spot Instances to spin up multiple environments simultaneously, significantly reducing the cost of development and testing.

3. Big Data and Analytics

Big data and analytics workloads, including Hadoop clusters and data warehousing tasks, can benefit significantly from Spot Instances. These tasks, which often require substantial computing resources, can be run on Spot Instances to analyze large datasets while keeping costs low.

4. Stateful Applications with Checkpointing

Stateful applications that can manage their state and handle interruptions through checkpointing mechanisms can also use Spot Instances effectively. Applications can save their state at regular intervals, allowing them to resume from the last checkpoint after an interruption.

5. Kubernetes Workloads on AWS EKS

A growing number of organizations are adopting Kubernetes to manage their containerized applications efficiently. Amazon Elastic Kubernetes Service (EKS) simplifies the process of running Kubernetes on AWS. Spot Instances can be utilized within EKS clusters to run various workloads, including web applications, microservices, and batch processing tasks. This approach not only optimizes costs significantly but also ensures that the Kubernetes cluster can scale according to demand without incurring high expenses. By integrating Spot Instances into their EKS strategy, businesses can achieve both operational flexibility and cost efficiency.

👉 EKS Bonus Content: We also wrote a detailed guide on using spot instances on EKS

Realistic Cost Savings Examples

To provide a concrete understanding of the potential savings, let’s look at four realistic examples:

Example 1: Batch Processing Job

Scenario: A media company processes 100 hours of video content monthly, requiring 400 vCPUs.

• On-Demand Cost: 400 vCPUs * $0.24 per vCPU-hour * 100 hours = $9,600
• Spot Instance Cost: 400 vCPUs * $0.048 per vCPU-hour (80% savings) * 100 hours = $1,920
• Savings: $7,680 monthly

Example 2: Development Environment

Scenario: A startup uses 50 instances (8 vCPUs each) for development and testing, running 12 hours a day, 20 days a month.

• On-Demand Cost: 50 instances * 8 vCPUs * $0.24 per vCPU-hour * 12 hours * 20 days = $23,040
• Spot Instance Cost: 50 instances * 8 vCPUs * $0.048 per vCPU-hour * 12 hours * 20 days = $4,608
• Savings: $18,432 monthly

Example 3: Big Data Analysis

Scenario: A financial institution runs big data analytics jobs requiring 1000 vCPUs for 10 hours each weekend.

• On-Demand Cost: 1000 vCPUs * $0.24 per vCPU-hour * 10 hours * 4 weekends = $96,000
• Spot Instance Cost: 1000 vCPUs * $0.048 per vCPU-hour * 10 hours * 4 weekends = $19,200
• Savings: $76,800 monthly

Example 4: EKS Cluster (Kubernetes)

Scenario: A digital services company runs Kubernetes on AWS EKS, utilizing 100 EC2 instances.

• On-Demand Cost: Assuming each EC2 instance costs $1 per hour, for 100 instances running 24/7 over a month (720 hours), the total On-Demand cost would be 100 instances * $1/hour * 720 hours = $72,000.
• Spot Instance Cost: With a 55% savings, the cost for using Spot Instances would be 45% of the On-Demand rate, which calculates to $72,000 * 45% = $32,400.
• Savings: By using Spot Instances, the company saves $72,000 – $32,400 = $39,600 monthly.

Common Pitfalls and How to Avoid Them

1. Interruption Handling

Pitfall: Not being prepared for Spot Instance interruptions can lead to data loss or significant disruptions in application performance.

How to Avoid:

• Auto Scaling: Use AWS Auto Scaling to automatically adjust the number of instances in response to demand, ensuring that your application maintains its performance even if some Spot Instances are interrupted.
• Checkpointing: Implement checkpointing in your applications, especially for batch processing jobs, to save progress periodically. This way, if a Spot Instance is interrupted, the job can resume from the last checkpoint.
• Node Termination Handler (EKS): Install the node termination handler on your EKS cluster to monitor for and handle EC2 spot instance interruption signals as well as handling spot instance terminations gracefully and keeping your applications available.

2. Spot Instance Pricing Fluctuations

Pitfall: Bidding too low for Spot Instances can result in instances not being allocated or being terminated frequently, which disrupts operations.

How to Avoid:

• Use Spot Instance Advisor: Utilize AWS Spot Instance Advisor to understand the history of spot price fluctuations and choose instances with lower interruption rates.
• Setting a Maximum Price: Set your bid price close to the On-Demand rate for critical instances to reduce the likelihood of interruption.

3. Capacity Not Available

Pitfall: Sometimes, the desired Spot Instance types may not be available in the needed quantities, leading to delays or failures in starting your applications.

How to Avoid:

• Instance Pools Per Availability Zone (AZ): Each instance type (for example m6i.large or m6a.large) within an Availability Zone counts as a separate instance pool. Spreading your requests across multiple instance pools increases your chances of fulfillment by tapping into various pools with potentially different demand and availability levels.
  • To clarify, for example if you have 2 AZs in your VPC (us-east-1a and us-east-1b), and 3 instance types (m5.large, m6a.large, m6i.large), then you have a total of 6 spot instance capacity pools to pull from.
• Use On-Demand Instances as a Fallback: Design your application to fall back on On-Demand Instances if Spot Instances are not available, ensuring continuity of operations.

Best Practices for Maximizing Savings with Spot Instances

1. Diversify Your Instance Types: To reduce the risk of interruption and increase your chances of obtaining Spot Instances at a lower cost, spread your requests across multiple instance types and families (for example m5a.large, m5i.large, t3a.large).
2. Implement Spot Fleet and Spot Blocks: Use Spot Fleet to manage thousands of Spot Instances and On-Demand Instances in a single application, optimizing for the lowest cost while meeting your capacity requirements. For workloads that require a longer duration, consider using Spot Blocks to request Spot Instances without interruptions for a specified duration.
3. Use a Combination of Spot, On-Demand, and Reserved Instances: For the best cost optimization, blend Spot Instances with On-Demand and Reserved Instances. Use Reserved Instances for baseline capacity, On-Demand Instances for spikes in demand, and Spot Instances for flexible, non-critical workloads.
4. Monitor and Manage Your Spot Instances with AWS Tools: Leverage AWS tools like AWS CloudWatch and AWS Lambda to monitor your Spot Instances and automate responses to spot interruptions or price changes. Implement strategies such as auto-scaling, instance rebalancing, and automatic replacement to ensure high availability and cost efficiency.
5. Optimize Your Bids: While setting your maximum price, consider both the Spot price history and the urgency of your workload. Bidding slightly above the average Spot price can increase your chances of maintaining instance availability without significantly increasing costs.
6. Design for Fault Tolerance and Flexibility: Architect your applications to be resilient to Spot Instance interruptions. This may include using stateless applications, replicating data across multiple zones, and employing queuing services to manage workload distribution.

Wrapping Things Up

AWS Spot Instances present an excellent opportunity for businesses to dramatically reduce their cloud computing costs. By understanding and leveraging Spot Instances for suitable workloads, companies can enjoy cost savings of up to 90% compared to On-Demand Instances. However, to fully benefit from Spot Instances, it’s crucial to be aware of their potential pitfalls and implement strategies to mitigate these risks.

This guide has walked you through the essentials of Spot Instances, from understanding what they are and how they work to identifying common use cases and pitfalls. We’ve also shared best practices and realistic examples to help you visualize the potential savings. Remember, the key to maximizing the benefits of Spot Instances lies in strategic planning, continuous management, and adopting a flexible approach to your cloud resources.

As cloud computing continues to evolve, staying informed and adaptable will ensure your organization can capitalize on cost-saving opportunities while maintaining performance and reliability. By integrating Spot Instances into your cloud strategy, you’re taking a significant step towards optimizing your cloud spend and achieving greater financial efficiency.

We encourage you to start experimenting with Spot Instances for suitable workloads and to continuously refine your strategies based on your experiences and the evolving cloud landscape. With the right approach, Spot Instances can be a game-changer for your cloud economics, unlocking substantial savings and enabling you to invest more in innovation and growth.