IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.

« Deploy Fleet Server on-premises and Elasticsearch on Cloud Fleet Server Secrets »

› ›

Fleet Server scalability

edit

Fleet Server scalability

edit

This page summarizes the resource and Fleet Server configuration requirements needed to scale your deployment of Elastic Agents. To scale Fleet Server, you need to modify settings in your deployment and the Fleet Server agent policy.

First modify your Fleet deployment settings in Elastic Cloud:

Log in to Elastic Cloud and go to your deployment.
Under Deployments > deployment name, click Edit.
Under Integrations Server:
- Modify the compute resources available to the server to accommodate a higher scale of Elastic Agents
- Modify the availability zones to satisfy fault tolerance requirements
For recommended settings, refer to Scaling recommendations (Elastic Cloud).

Next modify the Fleet Server configuration by editing the agent policy:

In Kibana, go to Management > Fleet > Agent Policies. Click the name of the Elastic Cloud agent policy to edit the policy.
Open the Actions menu next to the Fleet Server integration and click Edit integration.
Under Fleet Server, modify Max Connections and other advanced settings as described in Scaling recommendations (Elastic Cloud).

Advanced Fleet Server options

edit

The following advanced settings are available to fine tune your Fleet Server deployment.

cache

num_counters: Size of the hash table. Best practice is to have this set to 10 times the max connections.
max_cost: Total size of the cache.

server.timeouts

checkin_timestamp: How often Fleet Server updates the "last activity" field for each agent. Defaults to 30s. In a large-scale deployment, increasing this setting may improve performance. If this setting is higher than 2m, most agents will be shown as "offline" in the Fleet UI. For a typical setup, it’s recommended that you set this value to less than 2m.
checkin_long_poll: How long Fleet Server allows a long poll request from an agent before timing out. Defaults to 5m. In a large-scale deployment, increasing this setting may improve performance.

server.limits

policy_throttle: How often a new policy is rolled out to the agents.
action_limit.interval: How quickly Fleet Server dispatches pending actions to the agents.
action_limit.burst: Burst of actions that may be dispatched before falling back to the rate limit defined by interval.
checkin_limit.max: Maximum number of agents that can call the checkin API concurrently.
checkin_limit.interval: How fast the agents can check in to the Fleet Server.
checkin_limit.burst: Burst of check-ins allowed before falling back to the rate defined by interval.
checkin_limit.max_body_byte_size: Maximum size in bytes of the checkin API request body.
artifact_limit.max: Maximum number of agents that can call the artifact API concurrently. It allows the user to avoid overloading the Fleet Server from artifact API calls.
artifact_limit.interval: How often artifacts are rolled out. Default of 100ms allows 10 artifacts to be rolled out per second.
artifact_limit.burst: Number of transactions allowed for a burst, controlling oversubscription on outbound buffer.
artifact_limit.max_body_byte_size: Maximum size in bytes of the artficact API request body.
ack_limit.max: Maximum number of agents that can call the ack API concurrently. It allows the user to avoid overloading the Fleet Server from Ack API calls.
ack_limit.interval: How often an acknowledgment (ACK) is sent. Default value of 10ms enables 100 ACKs per second to be sent.
ack_limit.burst: Burst of ACKs to accommodate (default of 20) before falling back to the rate defined in interval.
ack_limit.max_body_byte_size: Maximum size in bytes of the ack API request body.
enroll_limit.max: Maximum number of agents that can call the enroll API concurrently. This setting allows the user to avoid overloading the Fleet Server from Enrollment API calls.
enroll_limit.interval: Interval between processing enrollment request. Enrollment is both CPU and RAM intensive, so the number of enrollment requests needs to be limited for overall system health. Default value of 100ms allows 10 enrollments per second.
enroll_limit.burst: Burst of enrollments to accept before falling back to the rate defined by interval.
enroll_limit.max_body_byte_size: Maximum size in bytes of the enroll API request body.
status_limit.max: Maximum number of agents that can call the status API concurrently. This setting allows the user to avoid overloading the Fleet Server from status API calls.
status_limit.interval: How frequently agents can submit status requests to the Fleet Server.
status_limit.burst: Burst of status requests to accomodate before falling back to the rate defined by interval.
status_limit.max_body_byte_size: Maximum size in bytes of the status API request body.
upload_start_limit.max: Maximum number of agents that can call the uploadStart API concurrently. This setting allows the user to avoid overloading the Fleet Server from uploadStart API calls.
upload_start_limit.interval: How frequently agents can submit file start upload requests to the Fleet Server.
upload_start_limit.burst: Burst of file start upload requests to accomodate before falling back to the rate defined by interval.
upload_start_limit.max_body_byte_size: Maximum size in bytes of the uploadStart API request body.
upload_end_limit.max: Maximum number of agents that can call the uploadEnd API concurrently. This setting allows the user to avoid overloading the Fleet Server from uploadEnd API calls.
upload_end_limit.interval: How frequently agents can submit file end upload requests to the Fleet Server.
upload_end_limit.burst: Burst of file end upload requests to accomodate before falling back to the rate defined by interval.
upload_end_limit.max_body_byte_size: Maximum size in bytes of the uploadEnd API request body.
upload_chunk_limit.max: Maximum number of agents that can call the uploadChunk API concurrently. This setting allows the user to avoid overloading the Fleet Server from uploadChunk API calls.
upload_chunk_limit.interval: How frequently agents can submit file chunk upload requests to the Fleet Server.
upload_chunk_limit.burst: Burst of file chunk upload requests to accomodate before falling back to the rate defined by interval.
upload_chunk_limit.max_body_byte_size: Maximum size in bytes of the uploadChunk API request body.

Scaling recommendations (Elastic Cloud)

edit

The following tables provide the minimum resource requirements and scaling guidelines based on the number of agents required by your deployment. It should be noted that these compute resource can be spread across multiple availability zones (for example: a 32GB RAM requirement can be satisfed with 16GB of RAM in 2 different zones).

Resource requirements by number of agents

Resource requirements by number of agents

edit

Number of Agents	Fleet Server Memory	Fleet Server vCPU	Elasticsearch Hot Tier
2,000	2GB	up to 8 vCPU	32GB RAM \| 8 vCPU
5,000	4GB	up to 8 vCPU	32GB RAM \| 8 vCPU
10,000	8GB	up to 8 vCPU	128GB RAM \| 32 vCPU
15,000	8GB	up to 8 vCPU	256GB RAM \| 64 vCPU
25,000	8GB	up to 8 vCPU	256GB RAM \| 64 vCPU
50,000	8GB	up to 8 vCPU	384GB RAM \| 96 vCPU
75,000	8GB	up to 8 vCPU	384GB RAM \| 96 vCPU
100,000	16GB	16 vCPU	512GB RAM \| 128 vCPU

A series of scale performance tests are regularly executed in order to verify the above requirements and the ability for Fleet to manage the advertised scale of Elastic Agents. These tests go through a set of acceptance criteria. The criteria mimics a typical platform operator workflow. The test cases are performing agent installations, version upgrades, policy modifications, and adding/removing integrations, tags, and policies. Acceptance criteria is passed when the Elastic Agents reach a Healthy state after any of these operations.

Policy scaling recommendations

edit

A single instance of Fleet supports a maximum of 500 Elastic Agent policies. If more policies are configured, UI performance might be impacted.

« Deploy Fleet Server on-premises and Elasticsearch on Cloud Fleet Server Secrets »