The inspiration to write this post came from the recent Linkedin Poll in which approximately 120 Engineers participated. I know the sample size may not be large, but still, the insights are drawn from over 110+ companies that are using AWS in their production workloads.

Yes — In Production (42%): An impressive 42% of respondents reported leveraging AWS Spot Instances in their production environments. This highlights the growing confidence in the stability and reliability of Spot Instances, which can significantly reduce operational costs while maintaining performance. By efficiently managing resource allocation, businesses can scale up their production workloads without breaking the bank.

Yes — In Dev Environment (37%): Coming in at a close second, 37% of the people who responded mentioned that they are using AWS Spot Instances in their development environments. This shows that Spot Instances bring advantages for quickly creating prototypes, testing, and making improvements to new applications and features. By saving costs and having the ability to easily scale up or down, developers can freely experiment and come up with innovative ideas without compromising on quality.

No — Fear of Interruption (11%): Interestingly, 11% of respondents expressed concerns about potential interruptions when using AWS Spot Instances. While it’s true that Spot Instances are subject to interruption based on market demand, advanced strategies such as diversifying across multiple availability zones or utilizing Spot Fleet can mitigate such risks. Understanding the best practices for managing interruptions can help businesses make the most of Spot Instances’ cost-efficiency

Working with those poll participants to understand the spot instance strategy which they are using in their environment — once I get a complete insight, I’ll add those details here — Stay tuned. :-)

No — Not Familiar with it (11%): Another 11% of respondents indicated that they were not familiar with AWS Spot Instances. This highlights the need for increased awareness and education about this powerful resource. Spot Instances provide a unique opportunity to optimize costs and enhance infrastructure scalability, and it’s crucial for professionals to explore and understand how they can leverage this technology.

Things you should know about Spot instances — before you start experimenting with them.

1. Bidding Process: When it comes to AWS Spot Instances, the bidding process is crucial. You have the opportunity to set your bid price, indicating the maximum amount you are willing to pay for the instance per hour. The current market price, also known as the Spot price, fluctuates based on supply and demand dynamics in the AWS infrastructure. If your bid price exceeds the Spot price, your Spot Instance is launched and you gain access to the requested computing resources. However, it’s important to note that the Spot price can change over time, and if it exceeds your bid price, your instance may be interrupted and terminated.

2. Time Before Termination: The duration of your Spot Instance depends on several factors, including the Spot price and the availability of capacity within the AWS infrastructure. AWS provides a termination notice, giving you a two-minute warning before your Spot Instance is reclaimed. This notice allows you to wrap up any ongoing processes or gracefully shut down your application.

3. Fulfillment and Capacity Availability: AWS prioritizes fulfilling Spot Instance requests based on the highest bids and the availability of capacity. If the Spot price increases and exceeds your bid, your instance may be interrupted and terminated to make room for higher-priced bids. It’s important to monitor the Spot price and adjust your bidding strategy accordingly to ensure a higher chance of fulfillment.

4. Instance Types and Availability Zones: Spot Instances are available across a wide range of instance types, allowing you to choose the most suitable option for your workload. Additionally, you can request Spot Instances in specific Availability Zones or let AWS handle the allocation across multiple zones for optimal resource utilization.

5. Integration with Other AWS Services: AWS Spot Instances seamlessly integrate with other AWS services, enabling you to leverage their power in various cloud computing scenarios. You can combine Spot Instances with services like Amazon EC2, Amazon EMR, and AWS Batch to enhance the performance, scalability, and cost efficiency of your applications and workloads.

6. Monitoring and Managing Spot Instances: AWS provides monitoring tools and APIs to help you track and manage your Spot Instances effectively. You can monitor the Spot price history, instance state, and termination notices using CloudWatch or programmatically via the AWS SDKs. These tools enable you to make informed decisions and take necessary actions to optimize your Spot Instance usage.
   Ref: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/spot-interruptions.html

Safe applications of Spot instances that won’t risk burning your hands.

Sourab’s comment stands out as it suggests a more targeted approach for utilizing spot instances. Instead of generic options like prod/nonprod, let’s delve into specific areas where we can confidently leverage spot instances without concerns of interruption and compromising customer experience.

1. Batch Processing: Spot instances are ideal for large-scale batch processing tasks, such as data analysis, data mining, or rendering. These workloads can be divided into smaller, independent tasks, and spot instances can be used to process them at a significantly reduced cost.

2. Testing and Development Environments: Spot instances can be utilized for creating testing and development environments, where uptime and availability are not critical. Developers can use spot instances to test new features, run automated test suites, or experiment with different configurations, saving costs on development infrastructure.

3. Web Crawling and Data Scraping: Spot instances are well-suited for web crawling and data scraping tasks. These processes often require a large number of instances to fetch and process data from various sources. Spot instances can be utilized to scale up and down the crawling infrastructure based on the availability and pricing of spot instances.

4. Media Processing and Encoding: Spot instances can be used for media processing and encoding tasks, such as transcoding videos or compressing images. These workloads can be easily parallelized, allowing spot instances to handle the processing workload efficiently while taking advantage of the cost savings.

5. High-Performance Computing (HPC) Workloads: Spot instances can be employed for HPC workloads that require significant computational power but are not time-sensitive. Examples include scientific simulations, genetic research, financial modeling, or climate modeling. By utilizing spot instances, organizations can access substantial compute resources at a fraction of the cost.

6. Machine Learning Training: Spot instances can be used for training machine learning models, especially for tasks that involve large datasets and require extensive computational resources. Training jobs can be split into smaller tasks and distributed across multiple spot instances to achieve faster model convergence.

As mentioned before, this article is still a work in progress. I am currently engaging in discussions with the participants of the poll to gain insights into their strategies and precautions for successfully running spot instances without fear of interruption. Once I have gathered sufficient data, I will incorporate additional details into this article.