EC2 Fleet and Spot Fleet

EC2 Fleet and Spot Fleet are designed to be a useful way to launch a fleet of tens, hundreds, or thousands of Amazon EC2 instances in a single operation. Each instance in a fleet is either configured by a launch template or a set of launch parameters that you configure manually at launch.

Topics

• Features and benefits
• Which is the best fleet method to use?
• Configuration options for your EC2 Fleet or Spot Fleet
• Work with EC2 Fleet
• Work with Spot Fleet
• Monitor your EC2 Fleet or Spot Fleet
• Tutorials for EC2 Fleet
• Example CLI configurations for EC2 Fleet
• Example CLI configurations Spot Fleet
• Quotas for EC2 Fleet and Spot Fleet

Features and benefits

Fleets provide the following features and benefits, enabling you to maximize cost savings and optimize availability and performance when running applications on multiple EC2 instances.

Multiple instance types

A fleet can launch multiple instance types, ensuring it isn't dependent on the availability of any single instance type. This increases the overall availability of instances in your fleet.

Distributing instances across Availability Zones

A fleet automatically attempts to distribute instances evenly across multiple Availability Zones for high availability. This provides resiliency in case an Availability Zone becomes unavailable.

Multiple purchasing options

A fleet can launch multiple purchase options (Spot and On-Demand Instances), allowing you to optimize costs through Spot Instance usage. You can also take advantage of Reserved Instance and Savings Plan discounts by using them in conjunction with On-Demand Instances in the fleet.

Automated replacement of Spot Instances

If your fleet includes Spot Instances, it can automatically request replacement Spot capacity if your Spot Instances are interrupted. Through Capacity Rebalancing, a fleet can also monitor and proactively replace your Spot Instances that are at an elevated risk of interruption.

Reserve On-Demand capacity

A fleet can use an On-Demand Capacity Reservation to reserve On-Demand capacity. A fleet can also include Capacity Blocks for ML, allowing you to reserve GPU instances on a future date to support you short duration machine learning (ML) workloads.