Skip to content

Latest commit

 

History

History
91 lines (67 loc) · 6.69 KB

README.md

File metadata and controls

91 lines (67 loc) · 6.69 KB
Raw

Monte Carlo AWS Agent Module

This module deploys Monte Carlo's containerized agent* on AWS Lambda, along with storage, roles etc.

See here for architecture details and alternative deployment options.

Prerequisites

Usage

Basic usage of this module:

module "apollo" {
  source = "monte-carlo-data/mcd-agent/aws"
}

output "function_arn" {
  value       = module.apollo.mcd_agent_function_arn
  description = "Agent Function ARN. To be used in registering."
}

output "invoker_role_arn" {
  value       = module.apollo.mcd_agent_invoker_role_arn
  description = "Assumable role ARN. To be used in registering."
}

output "invoker_role_external_id" {
  value       = module.apollo.mcd_agent_invoker_role_external_id
  description = "Assumable role External ID. To be used in registering."
}

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

Inputs

Name Description Type Default
image URI of the Agent container image (ECR Repo). Note that the region is automatically derived from the region variable. string 590183797493.dkr.ecr.*.amazonaws.com/mcd-agent:latest
cloud_account_id For deployments on the V2 Platform, use 590183797493. Accounts created after April 24th, 2024, will automatically be on the V2 platform or newer. If you are using an older version of the platform, please contact your Monte Carlo representative for the ID. string 190812797848
private_subnets Optionally connect the agent to a VPC by specifying at least two private subnet IDs in that VPC. list(string) []
region The AWS region to deploy the agent into. string us-east-1
remote_upgradable Allow the agent image and configuration 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 might replace your agent and require (re)registration. bool true

Outputs

Name Description
mcd_agent_function_arn Agent Function ARN. To be used in registering.
mcd_agent_invoker_role_arn Assumable role ARN. To be used in registering.
mcd_agent_invoker_role_external_id Assumable role External ID. To be used in registering.
mcd_agent_security_group_name Security group ID.
mcd_agent_storage_bucket_arn Storage bucket ARN.
mcd_agent_execution_role The role the MCD agent will use to execute actions.

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.

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.

*Note that due to an AWS limitation the agent image is also uploaded and then sourced from AWS ECR when executed on Lambda.