Datalore 2022.3 Help

Configure agents

You can change the default agents configuration by mounting a config file into /opt/datalore/configs/agents-config.yaml inside the Datalore container. This config has the following format:

docker: network: <name-of-agents-network> dataloreHost: <host-of-datalore-server> instances: - <instance1-definition> - <instance2-definition> ... - <instanceN-definition>

By default, <name-of-agents-network> is datalore-agents-network, and <host-of-datalore-server is datalore.

Each instance definition has the following fields:

Mandatory fields

id: basic-agent

Specifies the unique id for the instance.

default: true

Specifies whether the instance is default. Make sure exactly one instance has this parameter set to true.

label: "docker-base"

Specifies the instance name shown in the UI.

description: "docker-base"

Specifies the instance description shown in the UI.

image: docker.io/jetbrains/datalore-agent:2022.3

URI of the agent docker image, changed only to specify a custom agent image

Optional fields

pullPolicy: "IF_ABSENT"

Specifies when the image will be pulled. Acceptable values are: NEVER, ALWAYS, IF_ABSENT (default).

cpus: 1.5

Specifies how much of the available CPU resources a container can use. For example, if the host machine has two CPUs and you set cpus to 1.5, the container is guaranteed at most one and a half of the CPUs.

memory: 1000000004G

Specifies the maximum amount of memory the container can use.

env: - <env1-definition> - <env2-definition> ... - <envN-definition>

Defines environment variables on the agent. Each env definition contains a name and a value.

Example:

env: - name: DATALORE_SKIP_WARMUP value: true

In the example, the DATALORE_SKIP_WARMUP environment value is set to true on the agent. In this case, the analysis server warmup is skipped on agent initialization, which leads to faster initialization at the cost of slower code completion for some time.

Last modified: 06 December 2022