ML Commons cluster settings

To enhance and customize your OpenSearch cluster for machine learning (ML), you can add and modify several configuration settings for the ML commons plugin in your ‘opensearch.yml’ file.

Run tasks and models on ML nodes only

If true, ML Commons tasks and models run machine learning (ML) tasks on ML nodes only. If false, tasks and models run on ML nodes first. If no ML nodes exist, tasks and models run on data nodes. We recommend that you do not set this value to “false” on production clusters.

Setting

plugins.ml_commons.only_run_on_ml_node: true

Values

• Default value: true
• Value range: true or false

Dispatch tasks to ML node

round_robin dispatches ML tasks to ML nodes using round robin routing. least_load gathers runtime information from all ML nodes, like JVM heap memory usage and running tasks, and then dispatches the tasks to the ML node with the lowest load.

Setting

plugins.ml_commons.task_dispatch_policy: round_robin

Values

• Dafault value: round_robin
• Value range: round_robin or least_load

Set number of ML tasks per node

Sets the number of ML tasks that can run on each ML node. When set to 0, no ML tasks run on any nodes.

Setting

plugins.ml_commons.max_ml_task_per_node: 10

Values

• Default value: 10
• Value range: [0, 10,000]

Set number of ML models per node

Sets the number of ML models that can be loaded on to each ML node. When set to 0, no ML models can load on any node.

Setting

plugins.ml_commons.max_model_on_node: 10

Values

• Default value: 10
• Value range: [0, 10,000]

Set sync job intervals

When returning runtime information with the profile API, ML Commons will run a regular job to sync newly loaded or unloaded models on each node. When set to 0, ML Commons immediately stops sync up jobs.

Setting

plugins.ml_commons.sync_up_job_interval_in_seconds: 3

Values

• Default value: 3
• Value range: [0, 86,400]

Predict monitoring requests

Controls how many predict requests are monitored on one node. If set to 0, OpenSearch clears all monitoring predict requests in cache and does not monitor for new predict requests.

Setting

plugins.ml_commons.monitoring_request_count: 100

Value range

• Default value: 100
• Value range: [0, 10,000,000]

Upload model tasks per node

Controls how many upload model tasks can run in parallel on one node. If set to 0, you cannot upload models to any node.

Setting

plugins.ml_commons.max_upload_model_tasks_per_node: 10

Values

• Default value: 10
• Value range: [0, 10]

Load model tasks per node

Controls how many load model tasks can run in parallel on one node. If set to 0, you cannot load models to any node.

Setting

plugins.ml_commons.max_load_model_tasks_per_node: 10

Values

• Default value: 10
• Value range: [0, 10]

Add trusted URL

The default value allows you to upload a model file from any http/https/ftp/local file. You can change this value to restrict trusted model URLs.

Setting

The default URL value for this trusted URL setting is not secure. To ensure the security, please use you own regex string to the trusted repository that contains your models, for example https://github.com/opensearch-project/ml-commons/blob/2.x/ml-algorithms/src/test/resources/org/opensearch/ml/engine/algorithms/text_embedding/*.

plugins.ml_commons.trusted_url_regex: <model-repository-url>

Values

• Default value: "^(https?|ftp|file)://[-a-zA-Z0-9+&@#/%?=~_|!:,.;]*[-a-zA-Z0-9+&@#/%=~_|]"
• Value range: Java regular expression (regex) string

Assign task timeout

Assigns how long in seconds an ML task will live. After the timeout, the task will fail.

Setting

plugins.ml_commons.ml_task_timeout_in_seconds: 600

Values

• Default value: 600
• Value range: [1, 86,400]

Set native memory threshold

Sets a circuit breaker that checks all system memory usage before running an ML task. If the native memory exceeds the threshold, OpenSearch throws an exception and stops running any ML task.

Values are based on the percentage of memory available. When set to 0, no ML tasks will run. When set to 100, the circuit breaker closes and no threshold exists.

Setting

plugins.ml_commons.native_memory_threshold: 90

Values

• Default value: 90
• Value range: [0, 100]