Worker configuration

• Workers are used to speed up builds and tests by evenly distributing pipeline load
• The server where Buddy On-Premises is first installed is the default worker (Primary).
• You can install more workers on other nodes for extra performance.

Requirements

Installing workers

Launch the terminal on the server where you want to install the worker and run the commands below:

curl -sSL https://get.buddy.works | sh 
buddy install-worker --token="$TOKEN" --standalone-host="$ADDRESS"
$$

Supported flags

Updating workers

To update the worker to the newest version of Buddy, sign in to the server that hosts the worker and run:

buddy update
$

Updating worker configuration

To update worker configuration (memory limits, tag, network settings, etc.), run this command on the worker server:

buddy update-worker-config
$

Supported flags

Removing workers

To delete a worker, run buddy delete-worker or buddy uninstall on the machine where the worker is installed.

Supported flags

Backup

Backing up workers follows the same process as backing up the main Buddy On-Premises instance.

Generating installation command

GUI

1. Sign in to your Buddy On-Premises instance as admin.
2. Go to the On-Premises Admin panel and switch to the Workers tab.
3. Click Add new worker and copy the installation command.
4. Proceed to the installation step to continue.

CLI

On the server with the main instance, run the following to generate the installation command and token and save it to an executable file:

buddy install-worker
$

Supported flags

Worker authorization token

The authorization token is used to authenticate the worker in the main instance of Buddy On-Premises. To display the token run buddy configure and select 15. (Worker token) on the server with the main instance of Buddy On-Premises.

buddy update-worker-config --token TOKEN_VALUE
$

Configuration file

Storing configuration in a file is a convenient way to set up new and update existing workers in non-interactive mode. To fetch the data from the config file, add the --config flag to the command. For example:

buddy --yes update —config="/home/buddy/config.yml"
$

What you need to know

• providing the --config flag requires an existing and parsable YAML file in the provided path
• all fields are optional and can be skipped or empty
• all flags overwrite the values from the config file

Supported flags

Example

standalone-host: "https://192.168.5.114"
name: "Worker-1"
tag: "tag-1"
cpus: 4
memory: 2048
shm: 256
concurrent: 4
token: 1a2b3c4d5e
internal-host: "0.0.0.0"
external-host: "3.3.3.3"
runner-internal-port: 1090
runner-external-port: 1090
registry-internal-port: 1091
registry-external-port: 1091

Management

CLI configuration options

Running buddy configure on the worker, shows the options listed below. To configure an option, type the corresponding number and press Enter.

1. Worker data path – allows to move the application data on the worker to a different partition or disk

2. IP & ports – allows to set IP & port addresses:

   • internal IP – the internal IP address to which the worker is bound
   • external host – the external IP address to which the primary instance is connecting to
   • registry listening port (default 1090)
   • runner listening port (default 1091)
   • registry external port (default 1091)
3. Primary instance address – displays the IP address of the primary instance of Buddy.
4. Worker token – displays the token used to authenticate in the primary instance of Buddy.
5. Application memory management – changes the amount of RAM allocated to the Buddy application on the worker.

Checking worker status

You can view the list of connected workers and their status in the Workers tab of the On-Premises Admin panel:

Workers tab

Locking

You can lock a worker and change its name in the worker settings.

Resources

The settings are also the place to adjust the resources consumed by the actions in the pipeline (vCPUs, RAM, and shared memory) and tag workers. If any pipeline is currently assigned to the worker, you will find it at the bottom of the page:

Worker settings

Offline workers

If a worker is offline or in a different version than the main instance, all pipeline executions end with an error. It is also impossible to browse the filesystems and view execution logs of the pipelines assigned to that worker.

You can remove an inactive worker from the worker list. When you remove a worker, pipelines assigned to that worker will be automatically assigned to a different worker on the next execution.