Any modern computing-based business, whether graphics-heavy fields such as CAD, software engineering, online financial systems, artificial intelligence, or batch processing, requires large amounts of processing power.
Instead of investing in dedicated computing power, many companies rent virtual computers such as Amazon’s Elastic Compute Cloud (EC2), a part of Amazon Web Services (AWS) cloud. On-Demand capacity is relatively expensive; Spot Instances can save your enterprise up to 90 percent, but they come with their challenges.
Here are a few ways to use spot pricing effectively.
1. Optimize Capacity
Spot Instances allow AWS customers to use EC2 for fault-tolerant workloads to get many of the same benefits of acceleration and scale that On-Demand EC2 provides but at cost savings of 70 to 90 percent.
However, Amazon gives you only two minutes warning that they are taking back capacity; you will need to fall back on an on-demand configuration to prevent disruptions in reliability and performance. Capacity-optimized allocation helps reduce the possibility of this, as does instance-type flexibility and mixed instances.
As seen on this page, a solution that automates such fallback, configurations, and mixed-instance policies helps maximize the benefits while minimizing the management and potential reliability problems.
2. Get the Most Out of Prices
You pay the spot price in effect for the current hour wherein you launch any specific instances. Unlike the old model that meant you had to bid, this model (introduced in 2017) lets you see immediately what you will be paying.
You can employ several best practices to get the most out of Spot Instances. The primary one is to create a fault-tolerant application architecture that can handle interruption notices and EC2 recommendations regarding instance rebalancing.
3. Set Aggregate Capacity Targets
Thinking in terms of memory, vCPUs, and other measures of aggregate capacity rather than instances, allows you to set a target capacity and automate requests to maintain it.
Being flexible regarding the instance types and Availability Zones you request means you are more likely to receive the computing capacity you need.
Create blends with On-Demand, Savings Plans, and Reserved Instances to maximize optimization. When you receive a two-minute warning of interruption, you can terminate, stop, or hibernate these Spot Instances.
4. Choose an Allocation Strategy
Amazon recommends the price-capacity-optimized strategy, as AWS will provide you with instances from highly-available capacity pools at low prices. In other words, this strategy maximizes monetary savings.
The confusingly similarly-named price-capacity-optimized allocation strategy sources from pools with the optimal capacity to reduce the chances of interruption. This strategy minimizes potential disruptions.
5. Capacity Rebalancing
Capacity Rebalancing, if enabled, enables the identification of new Spot Instances to replace running ones before the running ones receive a two-minute interruption notice. As a result, your workload remains balanced.
6. Choose Suitable Use Cases
Spot Instances are suited for fault-tolerant, stateless, and flexible applications, such as rendering workloads, batch processing, HPC, big data, machine learning, stateless web servers, containerized workloads, other web applications and services, and CI/CD DevOps agile software engineering.
Spot Instances are unsuitable if the workload you need to run is fault-intolerant, stateful, or inflexible. Workloads that cannot tolerate occasional disruptions to total target capacity are also unsuitable.
Amazon emphatically warns against using Spot Instances in these cases; they also strongly discourage attempting to fail over to On-Demand to avoid interruptions.
Final Thoughts
Many companies benefit from renting virtual computers to execute enormous workloads at high speeds. However, this can become expensive. Amazon Web Services offers Spot Instances, which cost as much as 90 percent less than On-Demand Instances.
Managing them can quickly become a time-consuming and unproductive task. An automation solution provides the answer to this problem.