Monte Carlo GCP Agent Module (Beta)

This module deploys Monte Carlo's containerized agent (Beta) on GCP Cloud Run, along with storage, roles and service accounts.

See here for architecture details and alternative deployment options.

Prerequisites

• Terraform (>= 1.3)
• gcloud CLI. Authentication reference

Usage

Basic usage of this module:

module "apollo" {
  source = "monte-carlo-data/mcd-agent/google"
  version = "0.1.2"

  # Required variables
  generate_key      = true
  project_id        = "<GCP PROJECT>"
}

output "uri" {
  value       = module.apollo.mcd_agent_uri
  description = "The URL for the agent."
}

output "key" {
  value       = module.apollo.mcd_agent_invoker_key
  description = "The Key file for Monte Carlo to invoke the agent."
  sensitive   = true
}

After which you must register your agent with Monte Carlo. See here for more details, options, and documentation.

Note that setting generate_key = true will persist a key in the remote state used by Terraform. Please take appropriate measures to protect your remote state.

This module also activates the Cloud Run API in the project you specified. This resource (API) is not deactivated on destroy.

Inputs

Name	Description	Type	Default
project_id	The GCP project ID to deploy the agent into.	string	N/A
location	The GCP location (region) to deploy the agent into.	string	us-east4
image	The image for the agent.	string	montecarlodata/agent:latest-cloudrun
remote_upgradable	Allow the agent image to be remotely upgraded by Monte Carlo. Note that this sets a lifecycle to ignore any changes in Terraform to the image used after the initial deployment. If not set to 'true' you will be responsible for upgrading the image (e.g. specifying a new tag) for any bug fixes and improvements. Changing this value after initial deployment will replace your agent and require (re)registration.	bool	true
generate_key	Whether to generate a key for Monte Carlo to invoke the agent via Terraform. Note that this will persist a key in the remote state used by Terraform. Please take appropriate measures to protect your remote state. If not set to 'true' you will need to create a JSON key via another mechanism (e.g. GCP console) before registration.	bool	N/A

Outputs

Name	Description
mcd_agent_name	The name of the agent Cloud Run service.
mcd_agent_uri	The URL for the agent service. To be used in registering.
mcd_agent_storage	The GCS bucket for the agent.
mcd_agent_invoker_sa	The email of the invoker service account for the agent.
mcd_agent_invoker_key	The Key file for Monte Carlo to invoke the agent service. To be used in registering.

Releases and Development

The README and sample agent in the examples/agent directory is a good starting point to familiarize yourself with using the agent. These docs are also helpful to learn about provisioning resources in GCP.

Note that all Terraform files must conform to the standards of terraform fmt and the standard module structure. CircleCI will sanity check formatting and for valid tf config files. It is also recommended you use Terraform Cloud as a backend. Otherwise, as normal, please follow Monte Carlo's code guidelines during development and review.

When ready to release simply add a new version tag, e.g. v0.0.42, and push that tag to GitHub. See additional details here.

License

See LICENSE for more information.

Security

See SECURITY for more information.