What are hardware profiles?edit

Elastic Cloud deploys Elastic Stack components into unique hardware profiles which provides a unique blend of storage, memory and vCPU. This gives you more flexibility to choose the hardware profile that best fits for your use case. For example, Compute Optimized deploys Elasticsearch on virtual hardware that provides high vCPU which can help search-heavy use cases return queries quickly.

Under the covers, hardware profiles leverage virtualized instances from a cloud provider, such as Amazon Web Services, Google Compute Platform, and Microsoft Azure. You don’t interact with the cloud provider directly, but we do document what we use for your reference. To learn more, check Elasticsearch Service Hardware.

The components of the Elastic Stack that we support as part of a deployment are called instances and include:

  • Elasticsearch data tiers and master nodes
  • Machine Learning (ML) nodes
  • Kibana instances
  • APM and Fleet instances
  • Integrations Server instances
  • Enterprise Search instances

Elastic Agent, Beats, and Logstash are components of the Elastic Stack that are not included in the hardware profiles as they are installed outside of Elastic Cloud.

While you create your deployment, you can choose the hardware profile that best fits your needs, and configure it with the Advanced settings option. Depending on the cloud provider that you select, you can adjust the size of Elasticsearch nodes, or configure your Kibana, APM & Fleet, and Enterprise Search instances.

The hardware profiles available are:

Storage optimized profileedit

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) profileedit

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 optimized profileedit

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) profileedit

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.

General purpose profileedit

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) profileedit

This profile is similar to 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.