Elastic Docs ›Elasticsearch Service Documentation ›Preparing a deployment for production ›Change your configuration
« What deployment settings are available? How can I customize the components of my deployment? »

Change hardware profilesedit

Deployment hardware profiles deploy the Elastic Stack on virtual hardware. Each hardware profile has a different blend of storage, RAM, and vCPU.

Elastic Cloud regularly introduces new hardware profiles to provide:

  • More optimal hardware for applications in the Elastic Stack.
  • Cost efficiencies when new hardware from Cloud providers becomes available.

The Elastic Cloud console indicates when a new version of a hardware profile is available in the overview page for your deployment, under the Hardware profile section.

Change the hardware profile using the Elastic Cloud consoleedit

Upgrade to the newest version of your current hardware profileedit

Note that if there’s no indication that a newer version is available, that means that your deployment is already running on the latest version of that hardware profile.

  1. On the deployment overview page, next to your current hardware profile where there is indication of a newer available version, select Edit.

    Badge indicating new hardware profile version

  2. Preview the changes for the new hardware profile version.

    Notification showing that a new profile version is there

    The configuration screen summarizes hardware changes for each component of your deployment.

    Preview of the changes between the 2 versions of the hardware profile
  3. Select Update to apply the change.

Change to a different hardware profileedit

When the current hardware profile of your deployment isn’t the most optimal one available for your usage, you can change it as follows:

  1. On the deployment overview page, next to your current hardware profile, select Edit.

  2. Select the hardware profile you wish to change to. The configuration screen summarizes hardware changes for each component of your deployment.

    Preview of the changes between the 2 hardware profiles
  3. Select Update to apply the change.

If your deployment is configured for high availability, the hardware profile change does not impact your ability to read and write from the deployment as the change is rolled out instance by instance.

Change the hardware profile using the APIedit

Prerequisites:

  • A valid Elastic Cloud API key ($EC_API_KEY)
  • The deployment ID of the deployment you wish to modify ({deployment_id})

Replace those values with your actual API key and deployment ID in the following instructions.

  1. Get the current API payload for your deployment.

    curl \
-H "Authorization: ApiKey $EC_API_KEY" \
"https://api.elastic-cloud.com/api/v1/deployments/{deployment_id}"

  2. Using the API payload for your deployment, determine the following:

    • Your current deployment_template ID. The template ID corresponds to the hardware profile used for your deployment.

      "resources":{
      "elasticsearch":[
         {
            "ref_id":"main-elasticsearch",
            "id":"$CLUSTER_ID",
            "region":"gcp-us-central1",
            "info":{
               "cluster_id":"$CLUSTER_ID",
               "cluster_name":"$CLUSTER_NAME",
               "deployment_id":"$DEPLOYMENT_ID",
               "plan_info":{
                  "current":{
                     "plan":{
                        "deployment_template":{
                           "id":"gcp-cpu-optimized-v5"
                        },

    • The region that your deployment is in:

      "resources":{
      "elasticsearch":[
         {
            "ref_id":"main-elasticsearch",
            "id":"$DEPLOYMENT_ID",
            "region":"gcp-us-central1",

  3. Check the hardware profiles available for the region that your deployment is in and find the template ID of the deployment hardware profile you’d like to use.

    If you wish to update your hardware profile to the latest version available for that same profile, locate the template ID corresponding to the deployment_template you retrieved at step 2, but without the version information. For example, if your deployment’s current hardware profile is gcp-cpu-optimized-v5, use gcp-cpu-optimized as a template ID to update your deployment.

  4. Get the API payload for your deployment based on the new template ID.

    curl -XGET https://api.elastic-cloud.com/api/v1/deployments/{deployment_id}/migrate_template?template_id={new_template_id} \
-H "Authorization: ApiKey $EC_API_KEY" > migrate_deployment.json

  5. Use the payload returned to update your deployment to use the hardware profile.

    curl -XPUT https://api.elastic-cloud.com/api/v1/deployments/{deployment_id} \
-H "Authorization: ApiKey $EC_API_KEY" \
-H 'Content-Type: application/json' \
-d @migrate_deployment.json

List of hardware profilesedit

Storage optimizededit

Your Elasticsearch data nodes are optimized for high I/O throughput. Use this profile if you are new to Elasticsearch or don’t need to run a more specialized workload. You can find the exact storage, memory, and vCPU allotment on the hardware details page for each cloud provider.

Ideal use case

Good for most ingestion use cases with 7-10 days of data available for fast access. Also good for light search use cases without heavy indexing or CPU needs.

Storage optimized (dense)edit

Your Elasticsearch data nodes are optimized for high I/O throughput. You can find the exact storage, memory, and vCPU allotment on the hardware details page for each cloud provider.

Ideal use case

Ideal for ingestion use cases with more than 10 days of data available for fast access. Also, good for light search use cases with very large data sets.

CPU optimizededit

This profile runs CPU-intensive workloads faster. You can find the exact storage, memory, and vCPU allotment on the hardware details page for each cloud provider.

Ideal use case

Consider this configuration for ingestion use cases with 1-4 days of data available for fast access and for search use cases with indexing and querying workloads. Provides the most CPU resources per unit of RAM.

CPU optimized (ARM)edit

This profile is similar to CPU optimized profile but is powered by AWS Graviton2 instances. You can find the exact storage, memory, and vCPU allotment on the hardware details page for each cloud provider.

Ideal use case

Consider this configuration for ingestion use cases with 1-4 days of data available for fast access and for search use cases with indexing and querying workloads. Provides the most CPU resources per unit of RAM.

Vector search optimized (ARM)edit

This profile is suited for Vector search, Generative AI and Semantic search optimized workloads. You can find the exact storage, memory, and vCPU allotment on the hardware details page for each cloud provider.

Ideal use case

Optimized for applications that leverage Vector Search and/or Generative AI. Also the optimal choice for utilizing ELSER for semantic search applications. Broadly suitable for all semantic search, text embedding, image search, and other Vector Search use cases.

General purposeedit

This profile runs CPU-intensive workloads faster . You can find the exact storage, memory, and vCPU allotment on the hardware details page for each cloud provider.

Ideal use case

Suitable for ingestion use cases with 5-7 days of data available for fast access. Also good for search workloads with less-frequent indexing and medium to high querying loads. Provides a balance of storage, memory, and CPU.

General purpose (ARM)edit

This profile is similar to the General purpose profile but is powered by AWS Graviton2 instances. You can find the exact storage, memory, and vCPU allotment on the hardware details page for each cloud provider.

Ideal use case

Suitable for ingestion use cases with 5-7 days of data available for fast access. Also good for search workloads with less-frequent indexing and medium to high querying loads. Provides a balance of storage, memory, and CPU.

« What deployment settings are available? How can I customize the components of my deployment? »