AWS Placement Groups are how you influence where your EC2 instances are physically located within a data center. They’re not about availability across data centers (that’s Availability Zones), but about proximity and isolation within a single data center.
Here’s a quick demo of how they work. Imagine you have two EC2 instances and you want them to be as close as possible for low latency, or as far apart as possible for fault tolerance.
# Create a Cluster placement group
aws ec2 create-placement-group --group-name my-cluster-group --strategy cluster
# Launch an instance in the cluster group
aws ec2 run-instances --image-id ami-0abcdef1234567890 \
--instance-type t3.micro \
--placement GroupName=my-cluster-group \
--subnet-id subnet-0123456789abcdef0 \
--security-group-ids sg-0123456789abcdef0
# Launch another instance in the same cluster group
aws ec2 run-instances --image-id ami-0abcdef1234567890 \
--instance-type t3.micro \
--placement GroupName=my-cluster-group \
--subnet-id subnet-0123456789abcdef0 \
--security-group-ids sg-0123456789abcdef0
When you launch these instances, AWS tries to co-locate them on the same physical host or at least within the same rack for the cluster strategy. This is fantastic for tightly coupled workloads like HPC or databases that need sub-millisecond latency between nodes. The key guarantee here is that all instances in a cluster group will be placed on the same physical hardware, giving you predictable, low-latency network performance between them.
Now, let’s look at spread. This is the opposite of cluster.
# Create a Spread placement group
aws ec2 create-placement-group --group-name my-spread-group --strategy spread
# Launch an instance in the spread group
aws ec2 run-instances --image-id ami-0abcdef1234567890 \
--instance-type t3.micro \
--placement GroupName=my-spread-group \
--subnet-id subnet-0123456789abcdef0 \
--security-group-ids sg-0123456789abcdef0
# Launch another instance in the same spread group
aws ec2 run-instances --image-id ami-0abcdef1234567890 \
--instance-type t3.micro \
--placement GroupName=my-spread-group \
--subnet-id subnet-0123456789abcdef0 \
--security-group-ids sg-0123456789abcdef0
With spread, AWS actively tries to place each instance on different physical hardware, ideally in different racks. The guarantee is that no two instances in a spread group will share the same physical host. This is your go-to for critical workloads where you want to maximize fault tolerance. If one host fails, only one instance from your spread group is affected. The trade-off is potentially higher network latency between instances compared to cluster.
Finally, partition. This is a more nuanced strategy designed for large, distributed workloads where you need both isolation and a degree of fault tolerance across a larger set of hardware.
# Create a Partition placement group
aws ec2 create-placement-group --group-name my-partition-group --strategy partition --partition-count 3
# Launch instances in the partition group
# You would typically launch many instances across multiple subnets
aws ec2 run-instances --image-id ami-0abcdef1234567890 \
--instance-type t3.micro \
--placement GroupName=my-partition-group \
--subnet-id subnet-0123456789abcdef0 \
--security-group-ids sg-0123456789abcdef0
# ... launch more instances, potentially in different subnets
partition divides the available physical racks within a single Availability Zone into a specified number of partitions. AWS then places instances from your group into these partitions. The guarantee is that instances within the same partition may share a host or rack, but instances in different partitions are guaranteed to be on different physical hardware. This is useful for workloads like distributed databases (e.g., Cassandra, HBase) or big data processing (e.g., Spark) where you want to limit the blast radius of a single hardware failure to a subset of your nodes, but don’t need the extreme co-location of cluster or the strict isolation of spread for every single node. The partition-count parameter tells AWS how many partitions to create. For example, partition-count 3 means AWS will attempt to spread your instances across 3 distinct sets of physical hardware.
The most surprising thing about placement groups is how they interact with Auto Scaling groups and Elastic Beanstalk. You can associate a placement group with these services, and they will automatically launch new instances into the specified placement group, respecting its strategy. This means your fault tolerance or co-location guarantees are maintained even as your fleet scales up and down.
When you launch an instance into a cluster placement group, the network performance between instances in that group is enhanced. This is because AWS configures the network fabric to provide higher bandwidth and lower latency, effectively treating instances within the group as if they were on a single, high-performance cluster. This is achieved through dedicated network paths and optimized routing within the AWS data center.
The next thing you’ll want to understand is how placement groups integrate with Spot Instances and Reserved Instances, and the nuances of launching instances into them across different Availability Zones.