Configure Docker agents

If you installed Datalore using Docker, 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.
`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:2022.2`	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: 100000000`	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: 20 June 2022