Allocation strategies for Spot Instances
Your launch configuration determines all the possible Spot capacity pools (instance types and Availability Zones) from which EC2 Fleet can launch Spot Instances. However, when launching instances, EC2 Fleet uses the allocation strategy that you specify to pick the specific pools from all your possible pools.
Note
(Linux instances only) If you configure your Spot Instance to launch with AMD SEV-SNP turned on, you are charged an
additional hourly usage fee that is equivalent to 10% of the On-Demand hourly rate
Allocation strategies
You can specify one of the following allocation strategies for Spot Instances:
price-capacity-optimized
(recommended)-
EC2 Fleet identifies the pools with the highest capacity availability for the number of instances that are launching. This means that we will request Spot Instances from the pools that we believe have the lowest chance of interruption in the near term. EC2 Fleet then requests Spot Instances from the lowest priced of these pools.
The
price-capacity-optimized
allocation strategy is the best choice for most Spot workloads, such as stateless containerized applications, microservices, web applications, data and analytics jobs, and batch processing. capacity-optimized
-
EC2 Fleet identifies the pools with the highest capacity availability for the number of instances that are launching. This means that we will request Spot Instances from the pools that we believe have the lowest chance of interruption in the near term. You can optionally set a priority for each instance type in your fleet using
capacity-optimized-prioritized
. EC2 Fleet optimizes for capacity first, but honors instance type priorities on a best-effort basis.With Spot Instances, pricing changes slowly over time based on long-term trends in supply and demand, but capacity fluctuates in real time. The
capacity-optimized
strategy automatically launches Spot Instances into the most available pools by looking at real-time capacity data and predicting which are the most available. This works well for workloads that may have a higher cost of interruption associated with restarting work, such as long Continuous Integration (CI), image and media rendering, Deep Learning, and High Performance Compute (HPC) workloads that may have a higher cost of interruption associated with restarting work. By offering the possibility of fewer interruptions, thecapacity-optimized
strategy can lower the overall cost of your workload.Alternatively, you can use the
capacity-optimized-prioritized
allocation strategy with a priority parameter to order instance types from highest to lowest priority. You can set the same priority for different instance types. EC2 Fleet will optimize for capacity first, but will honor instance type priorities on a best-effort basis (for example, if honoring the priorities will not significantly affect EC2 Fleet's ability to provision optimal capacity). This is a good option for workloads where the possibility of disruption must be minimized and the preference for certain instance types matters. Note that when you set the priority forcapacity-optimized-prioritized
, the same priority is also applied to your On-Demand Instances if the On-DemandAllocationStrategy
is set toprioritized
. diversified
-
The Spot Instances are distributed across all Spot capacity pools.
lowest-price
(not recommended)-
Warning
We don't recommend the
lowest-price
allocation strategy because it has the highest risk of interruption for your Spot Instances.The Spot Instances come from the lowest priced pool that has available capacity. This is the default strategy. However, we recommend that you override the default by specifying the
price-capacity-optimized
allocation strategy.If the lowest priced pool doesn't have available capacity, the Spot Instances come from the next lowest priced pool that has available capacity.
If a pool runs out of capacity before fulfilling your desired capacity, EC2 Fleet will continue to fulfill your request by drawing from the next lowest priced pool. To ensure that your desired capacity is met, you might receive Spot Instances from several pools.
Because this strategy only considers instance price and not capacity availability, it might lead to high interruption rates.
InstancePoolsToUseCount
-
The number of Spot pools across which to allocate your target Spot capacity. Valid only when the allocation strategy is set to
lowest-price
. EC2 Fleet selects the lowest priced Spot pools and evenly allocates your target Spot capacity across the number of Spot pools that you specify.Note that EC2 Fleet attempts to draw Spot Instances from the number of pools that you specify on a best effort basis. If a pool runs out of Spot capacity before fulfilling your target capacity, EC2 Fleet will continue to fulfill your request by drawing from the next lowest priced pool. To ensure that your target capacity is met, you might receive Spot Instances from more than the number of pools that you specified. Similarly, if most of the pools have no Spot capacity, you might receive your full target capacity from fewer than the number of pools that you specified.
Choose the appropriate allocation strategy
You can optimize your fleet for your use case by choosing the appropriate Spot
allocation strategy. For On-Demand Instance target capacity, EC2 Fleet always selects the least
expensive instance type based on the public On-Demand price, while following the
allocation strategy—either price-capacity-optimized
,
capacity-optimized
, diversified
, or
lowest-price
—for Spot Instances.
Balance lowest price and capacity availability
To balance the trade-offs between the lowest priced Spot capacity pools
and the Spot capacity pools with the highest capacity availability, we
recommend that you use the price-capacity-optimized
allocation
strategy. This strategy makes decisions about which pools to request Spot Instances
from based on both the price of the pools and the capacity availability of
Spot Instances in those pools. This means that we will request Spot Instances from the pools
that we believe have the lowest chance of interruption in the near term,
while still taking price into consideration.
If your fleet runs resilient and stateless workloads, including
containerized applications, microservices, web applications, data and
analytics jobs, and batch processing, then use the
price-capacity-optimized
allocation strategy for optimal
cost savings and capacity availability.
If your fleet runs workloads that might have a higher cost of interruption
associated with restarting work, then you should implement checkpointing so
that applications can restart from that point if they're interrupted. By
using checkpointing, you make the price-capacity-optimized
allocation strategy a good fit for these workloads because it allocates
capacity from the lowest priced pools that also offer a low Spot Instance
interruption rate.
For an example configuration that uses the
price-capacity-optimized
allocation strategy, see Example 10: Launch Spot Instances in a
price-capacity-optimized fleet.
When workloads have a high cost of interruption
You can optionally use the capacity-optimized
strategy if you
run workloads that either use similarly priced instance types, or where the
cost of interruption is so significant that any cost saving is inadequate in
comparison to a marginal increase in interruptions. This strategy allocates
capacity from the most available Spot capacity pools that offer the
possibility of fewer interruptions, which can lower the overall cost of your
workload. For an example configuration that uses the
capacity-optimized
allocation strategy, see Example 8: Launch Spot Instances in a capacity-optimized
fleet.
When the possibility of interruptions must be minimized but the preference
for certain instance types matters, you can express your pool priorities by
using the capacity-optimized-prioritized
allocation strategy
and then setting the order of instance types to use from highest to lowest
priority. For an example configuration, see Example 9: Launch Spot Instances in a capacity-optimized fleet
with priorities.
Note that when you set priorities for capacity-optimized-prioritized
, the
same priorities are also applied to your On-Demand Instances if the
On-Demand AllocationStrategy
is set to
prioritized
.
When your workload is time flexible and capacity availability is not a factor
If your fleet is small or runs for a short time, you can use
price-capacity-optimized
to maximize cost savings while
still considering capacity availability.
When your fleet is large or runs for a long time
If your fleet is large or runs for a long time, you can improve the
availability of your fleet by distributing the Spot Instances across multiple pools
using the diversified
strategy. For example, if your EC2 Fleet
specifies 10 pools and a target capacity of 100 instances, the fleet
launches 10 Spot Instances in each pool. If the Spot price for one pool exceeds your
maximum price for this pool, only 10% of your fleet is affected. Using this
strategy also makes your fleet less sensitive to increases in the Spot price
in any one pool over time. With the diversified
strategy, the
EC2 Fleet does not launch Spot Instances into any pools with a Spot price that is equal to
or higher than the On-Demand
price
Maintain target capacity
After Spot Instances are terminated due to a change in the Spot price or available
capacity of a Spot capacity pool, an EC2 Fleet of type maintain
launches
replacement Spot Instances. The allocation strategy determines the pools from which the
replacement instances are launched, as follows:
-
If the allocation strategy is
price-capacity-optimized
, the fleet launches replacement instances in the pools that have the most Spot Instance capacity availability while also taking price into consideration and identifying lowest priced pools with high capacity availability. -
If the allocation strategy is
capacity-optimized
, the fleet launches replacement instances in the pools that have the most Spot Instance capacity availability. -
If the allocation strategy is
diversified
, the fleet distributes the replacement Spot Instances across the remaining pools.