Spot Instances

Definition

In cloud computing, Spot Instances refer to virtual machines offered by cloud service providers at significantly reduced prices compared to standard on-demand instances. These instances utilize the provider’s excess, unused capacity and are for workloads that can tolerate interruptions. 

Brief History

The concept of Spot Instances was introduced to enhance resource utilization and offer cost savings to users. Cloud service providers, such as AWS, often experience fluctuating demand for their computing resources, leading to periods where a significant portion of their infrastructure remains idle. To monetize this unused capacity, AWS introduced Spot Instances in December 2009, allowing users to bid on spare computing power at substantially reduced prices. The original AWS model involved a bidding system where users set maximum bid prices; however, in 2017, AWS shifted to a simplified current price model, enabling users to pay the fluctuating spot price without bidding. Following AWS's lead, other cloud providers, including Google Cloud and Microsoft Azure, have implemented similar models, offering their own versions of Spot Instances.

While AWS uses the term Spot Instances, Google Cloud initially referred to them as Preemptible VMs (now Spot VMs), and Azure uses Spot VMs. The term virtual machines (VMs) is accurate for Azure and Google, while AWS uses EC2 instances, which are functionally equivalent to VMs.

Key Features

Here are some of the Key features for Spot Instances that you need to understand:

• Cost Savings: Spot Instances can be up to 90% cheaper than On-Demand Instances, making them an attractive option for cost-conscious users.
• Interruption Risk: Cloud providers can reclaim Spot Instances with minimal notice (.eg., a two-minute warning from AWS) when they need the capacity back, leading to potential interruptions in workloads.
• Variable Availability: The availability and pricing of Spot Instances fluctuate based on supply and demand dynamics within the cloud provider’s infrastructure.
• Integration with Other Services: Spot Instances can be integrated with various cloud services, such as Auto Scaling groups and container orchestration tools, allowing for automated scaling and management workloads.
• Use Case Suitability: They are ideal for stateless, flexible, and fault-tolerant workloads that can handle interruptions, such as batch processing, big data analytics and development/testing environments.

Ideal Use Cases

Spot Instances are a cost-effective solution offered by cloud vendors, allowing users to utilize unused compute capacity at significantly reduced prices. However, due to their potential for sudden interruption, they are best suited for specific types of workloads.

• Fault-Tolerant Workloads: You can use Spot Instances for various fault-tolerant and flexible applications. 
• Big Data and Analytics: Use Spot Instances for processing large datasets using frameworks like Apache  Hadoop or Spark, where jobs can be distributed across multiple nodes. The distributed nature of these frameworks allows them to handle node interruptions gracefully.
• Containerized Workloads: Running containerized applications orchestrated by systems like Kubernetes or Amazon ECS. Containers are typically stateless and can be rescheduled on different nodes if an instance is interrupted.
• High-Performance Computing (HPC): Compute-intensive tasks like scientific simulations, financial modeling, and rendering that can benefit from parallel processing. While these tasks require significant computational power, they often tolerate interruptions by saving intermediate states.
• Web Services with Flexible Scaling: By combining Spot Instances with On-Demand Instances, businesses can scale out during peak time cost-effectively.
• Development and Testing Environments: Environments where applications are developed and tested, which do not require high availability. Utilizing Spot Instances can reduce costs during the development lifecycle.

How They Work

While the core concept is consistent across providers, each implements Spot Instances with unique features and policies.

Amazon Web Services (AWS): Spot Instances

Pricing Model: AWS Spot Instances offer savings of up to 90% compared to On-Demand prices. Spot prices fluctuate based on long-term supply and demand trends for EC2 capacity. Since AWS phased out its bidding system in 2017, users now pay the current spot price.

‍

Interruption Policies: AWS provides a two-minute warning before reclaiming Spot Instances, enabling graceful interruption management. These are ideal for fault-tolerant workloads such as batch processing, data analysis, and CI/CD operations.

Microsoft Azure: Spot Virtual Machines (Spot VMs)

Pricing Model: Azure Spot VMs offer significant discounts, up to 90% off compared to pay-as-you-go prices. Pricing depends on regional and instance availability (not real-time bidding), using a capacity-based pricing model.

Interruption Policy: Azure may deallocate Spot VMs when it needs the capacity back, providing a 30-second warning before reclaiming. Azure prioritizes reclamation based on capacity needs, not user bids. These are suitable for workloads that can tolerate interruptions, such as batch jobs, stateless applications, and development/testing environments.

Google Cloud Platform: Spot VMs

Pricing Model: Google Cloud's Spot VMs offer discounts of 60% to 91% off standard prices. Unlike the variable pricing of AWS and Azure, this fixed pricing provides cost predictability.

Interruption Policy: Google Cloud may preempt Spot VMs with a 30-second advance notice when resources are required elsewhere. They are well-suited for fault-tolerant workloads such as big data processing, containerized applications, and CI/CD pipelines.

Key Comparisons

Risk Limitations

Spot Instances offer significant cost savings by allowing users to utilize unused cloud resources at reduced price, however, they come  with certain risks and limitations that are important to consider:

Interruption Risk

• Potential for Termination: Cloud providers can reclaim Spot Instances with minimal notice when they need the capacity back, leading to potential interruptions in workload. Interruption varies by region, instance type, and provider demand. Some instance types (e.g., less common GPUs) may see higher interruption rates. 
• Impact on Applications: This makes Spot Instances unsuitable for applications requiring continuous uptime or those sensitive to interruptions.

Unpredictable Availability

• Variable Supply: The availability of Spot Instances fluctuates based on supply and demand, so prices can change accordingly.
• Planning Challenges: This unpredictability can complicate capacity planning and may require dynamic workload management.

Complexity Management

• Operational Overhead: Effectively utilizing Spot Instances often necessitates implementing strategies for handling interruptions, such as checkpointing, automated failover, and maintaining a balance between Spot and On-Demand Instances.
• Resource Constraints: Spot Instances may not always be available for every instance type or in every region, which can limit their applicability for certain workloads or geographic requirements. 

Additional Risks

• No SLA Guarantees: Spot Instances lack uptime/service-level agreements (SLAs).
• Partial Hour Billing: Most providers bill for partial hours if interrupted (except Google Cloud, which bills per second).
• Eviction Rates: They vary by provider; AWS publishes historical interruption rates while Azure and Google Cloud do not.

Conclusion

In summary, while Spot Instances can lead to substantial cost savings, they require a thorough assessment of workload suitability and a proactive approach to manage the associated risks. Organizations must weigh the benefits against the potential challenges to determine if Spot Instances align with their operational requirements and risk tolerance.

Unlock significant cloud cost savings with Octo today! Octo provides actionable recommendations, including the strategic use of Spot Instances, to optimize your cloud expenses. By identifying suitable workloads for Spot Instances, Octo enables you to reduce costs without compromising performance. Experience intelligent cloud cost management tailored to your needs. Learn more about Octo.

‍