GAMECOST02-BP03 Select the appropriate compute pricing option to reduce costs

Run performance tests of your game server software across a variety of instance types and compute options to determine which option is most cost-effective for your game.

Level of risk exposed if this best practice is not established: Medium

Implementation guidance

In addition to efficiently utilizing the right EC2 instance types for your workload, consider which of the available compute pricing options is most suitable for your cost optimization goals. There are several pricing options available, including On-Demand Instances, Spot Instances, Reserved Instances, and Savings Plans.

Savings Plans (SPs) provide discounts for compute by making usage commitments and are ideal for scenarios when you cannot forecast your expected usage for a 1-year or 3-year period. They provide discounts like Reserved Instances with the flexibility to apply these discounts across Regions, instance family, operating system, tenancy. They can also be applied to AWS Fargate, who can be a game server hosting option for casual games or AWS Lambda who is used as a great option for turn-based game that do not require game servers. For more information, see Building a serverless multi-player game that scales.

Savings Plans are introduced during game launches to save costs for game servers workloads that are contributing to EC2 instances spend when the game is released to the audience. Savings Plans can also be introduced post-launch when game operations team have a better understanding of the player traffic after the game has been running in production for an extended period.

Since Savings Plans provide regional flexibility, they are particularly ideal to optimize game servers spend for games with unpredictable usage across geographies.

For example, if your daily player usage pattern requires at least 20 servers to support your player base, but periodically requires up to 40 servers, then consider purchasing Savings Plan commitments to cover the 20 servers' baseline, because that usage demand is predictable and consistent, and will result in maximum utilization of the usage commitment that you have purchased.

Maximize the utilization of Savings Plans and augment them with other purchase options that provide more flexibility for unpredictable game server usage spikes, such as on-demand and Spot Instances to achieve optimal savings.

Spot Instances are ideal for running game servers because they offer the largest compute discounts, do not require usage commitments, and they provide flexibility for unpredictable and spiky workload types. However, Spot Instances can be interrupted, so they are best suited for game server workloads with short game session duration or situations where the tolerance for interruption is higher.

For more information on guidance for running game servers using Kubernetes on Amazon EKS with EC2 Spot Instances, see How to run massively multiplayer games with EC2 Spot using Aurora Serverless.

Use Amazon EC2 Spot Instances to determine pools with the least chance of interruption that will deliver maximum savings compared to on-demand rates.

When using Spot, it is also recommended to run game server workloads across multiple EC2 instance types and Availability Zones in an AWS Region to diversify your usage of capacity and reduce interruption risk.

Consider using Spot Instances in combination with On-Demand Instances to minimize the impact of potential disruptions to active game sessions and use capacity optimized allocations strategy to further reduce the risk of interruption.

Refer to the Best practices for Amazon EC2 Spot for additional best practices. Capacity Rebalancing in Auto Scaling to replace at-risk Spot Instances can be used to proactively monitor and add additional capacity when Spot Instances are at increased risk of interruption.

Amazon GameLift FleetIQ integrates with Spot Instances to optimize the use of low-cost Spot Instances while reducing the risk of interruptions. If you are hosting your game using GameLift, review the GameLift documentation for choosing computing resources. For more information, see Choose compute resources for a managed fleet.

The following diagram provides an example to illustrate the use of multiple compute pricing options for game server workloads:

In the diagram, the player concurrency fluctuates over time which makes it difficult to manage utilization and achieve cost optimization. To address this fluctuation, consider adopting a mixture of different compute pricing options, using Savings Plans for EC2 to meet the needs of your minimum usage requirements while relying on EC2 On-Demand and EC2 Spot Instances to meet the needs of your player demand.

Implementation steps