AWS- Placement Groups

Nidhi Ashtikar
4 min readJul 9, 2024

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Placement groups in AWS allow you to control how your EC2 instances are placed within the AWS infrastructure. This can enhance performance, minimize failure risk, or accommodate specific application needs.

Types of Placement Groups:

Cluster Placement Group:

Definition: Instances are grouped together within a single availability zone (AZ) to provide low-latency network connectivity.

Setup: All instances are placed in a single AZ.

Ideal For:

  • High-performance computing applications.
  • Applications requiring fast, low-latency networking.

High performance with up to 10 Gbps bandwidth between instances.

Low latency, high throughput networking.

Drawbacks:

  • High risk: If the AZ fails, all instances in the cluster fail.

Use Cases:

  • Big data jobs requiring fast completion.
  • Applications needing extremely low latency and high throughput between instances.

2. Spread Placement Group:

Definition: Instances are spread across different hardware to minimize the risk of simultaneous failures.

Setup: Instances are spread across multiple hardware racks.

Ideal For:

  • Applications requiring high availability and fault tolerance.
  • Critical applications where instance failure isolation is needed.

Reduced risk of simultaneous hardware failure.

Instances can span across multiple AZs.

Drawbacks:

  • Limited to seven instances per AZ per placement group.

Use Cases:

  • Critical applications where high availability is essential.
  • Applications needing isolation of instance failures.

3. Partition Placement Group

Definition: Instances are spread across multiple partitions, each consisting of separate racks of hardware within an AZ.

Setup: Instances are spread across partitions, each representing different hardware racks within an AZ.

Ideal For:

  • Big data and distributed applications.
  • Applications like HDFS, HBase, Cassandra, and Kafka that can leverage partition awareness.

Up to seven partitions per AZ, which can span multiple AZs.

Hundreds of instances can be accommodated.

Each partition is isolated from failures of other partitions.

Drawbacks:

  • More complex setup and management.

Use Cases:

  • Big data applications like Hadoop, Cassandra, or Kafka that can leverage partition awareness for data distribution.

Step-by-Step Guide:

Navigate to Placement Groups:

  • On the AWS Management Console, navigate to the EC2 Dashboard.
  • On the left-hand side, scroll down to Network & Security and click on Placement Groups.

Create Placement Groups:

  • Click Create Placement Group.
  • Name it my-high-performance-group.
  • Select Cluster as the placement strategy.
  • Click Create.

Spread Placement Group:

  • Click Create Placement Group.
  • Name it my-critical-group.
  • Select Spread as the placement strategy.
  • Ensure the spread level is set to Rack.
  • Click Create.

Partition Placement Group:

  • Click Create Placement Group.
  • Name it my-distributed-group.
  • Select Partition as the placement strategy.
  • Set the number of partitions (e.g., 4).
  • Click Create.

Launch Instances in Placement Groups:

  • Click Launch instances to start the instance creation process.
  • Select your desired Amazon Machine Image (AMI) and instance type.
  • Configure instance details. Scroll down to Advanced Details.
  • In the Placement group name dropdown, select the appropriate placement group (my-high-performance-group, my-critical-group, or my-distributed-group).
  • Configure any other necessary settings and complete the instance launch process.

Summary:

Cluster Placement Group (my-high-performance-group):

  • Used for high-performance applications needing low latency and high throughput.
  • Instances are grouped closely together in a single AZ.

Spread Placement Group (my-critical-group):

  • Used for critical applications requiring high availability and fault tolerance.
  • Instances are spread across different hardware racks, minimizing simultaneous failure risk.

Partition Placement Group (my-distributed-group):

  • Used for large-scale, partition-aware applications like big data processing.
  • Instances are spread across multiple partitions, each partition isolated from the failures of others.

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Nidhi Ashtikar
Nidhi Ashtikar

Written by Nidhi Ashtikar

Experienced AWS DevOps professional with a passion for writing insightful articles.

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