CiscoDevNet / cloud-cml

Run Cisco Modeling Labs on cloud infrastructure

README

Version 0.3.0, June 4 2024

With CML 2.7, you can run CML instances on Azure and AWS. We have tested CML deployments using this tool chain in both clouds. The use of this tool is considered BETA. The tool has certain requirements and prerequisites which are described in this README and in the documentation directory.

It is very likely that this tool chain can not be used "as-is". It should be forked and adapted to specific customer requirements and environments.

Important

Support:

• For customers with a valid service contract, CML cloud deployments are supported by TAC within the outlined constraints. Beyond this, support is done with best effort as cloud environments, requirements and policy can differ to a great extent.
• With no service contract, support is done on a best effort basis via the issue tracker.

Features and capabilities: Changes to the deployment tooling will be considered like any other feature by adding them to the product roadmap. This is done at the discretion of the CML team.

Error reporting: If you encounter any errors or problems that might be related to the code in this repository then please open an issue on the Github issue tracker for this repository.

Important

Read the section below about cloud provider selection (prepare script).

General requirements

The tooling uses Terraform to deploy CML instances in the Cloud. It's therefore required to have a functional Terraform installation on the computer where this tool chain should be used.

Furthermore, the user needs to have access to the cloud service. E.g. credentials and permissions are needed to create and modify the required resources. Required resources are

• service accounts
• storage services
• compute and networking services

The tool chain / build scripts and Terraform can be installed on the on-prem CML controller or, when this is undesirable due to support concerns, on a separate Linux instance.

That said, the tooling also runs on macOS with tools installed via Homebrew. Or on Windows with WSL. However, Windows hasn't been tested by us.

Preparation

Some of the steps and procedures outlined below are preparation steps and only need to be done once. Those are

• cloning of the repository
• installation of software (Terraform, cloud provider CLI tooling)
• creating and configuring of a service account, including the creation of associated access credentials
• creating the storage resources and uploading images and software into it
• creation of an SSH key pair and making the public key available to the cloud service
• editing the config.yml configuration file including the selection of the cloud service, an instance flavor, region, license token and other parameters

Important: Cloud provider selection

The tooling supports multiple cloud providers (currently AWS and Azure). Not everyone wants both providers. The default configuration is set to use AWS only. If Azure should be used either instead or in addition then the following steps are mandatory:

1. Run the prepare.sh script to modify and prepare the tool chain. If on Windows, use prepare.bat. You can actually choose to use both, if that's what you want.
2. Configure the proper target ("aws" or "azure") in the configuration file

The first step is unfortunately required, since it is impossible to dynamically select different cloud configurations within the same Terraform HCL configuration. See this SO link for more some context and details.

The default "out-of-the-box" configuration is AWS, so if you want to run on Azure, don't forget to run the prepare script.

Managing secrets

Warning

It is a best practice to not keep your CML secrets and passwords in Git!

CML cloud supports these storage methods for the required platform and application secrets:

• Raw secrets in the configuration file (as supported with previous versions)
• Random secrets by not specifiying any secrets
• Hashicorp Vault
• CyberArk Conjur

See the sections below for additional details how to use and manage secrets.

Referencing secrets

You can refer to the secret maintained in the secrets manager by updating config.yml appropriately. If you use the dummy secrets manager, it will use the raw_secret as specified in the config.yml file, and the secrets will not be protected.

secret:
  manager: conjur
  secrets:
    app:
      username: admin
      # Example using Conjur
      path: example-org/example-project/secret/admin_password

Refer to the .envrc.example file for examples to set up environment variables to use an external secrets manager.

Random secrets

If you want random passwords to be generated when applying, based on random_password, leave the raw_secret undefined:

secret:
  manager: dummy
  secrets:
    app:
      username: admin
      # raw_secret: # Undefined

Note

You can retrieve the generated passwords after applying with terraform output cml2secrets.

The included default config.yml configures generated passwords for the following secrets:

• App password (for the UI)
• System password for the OS system administration user
• Cluster secret when clustering is enabled

Regardless of the secret manager in use or whether you use random passwords or not: You must provide a valid Smart Licensing token for the sytem to work, though.

CyberArk Conjur installation

Important

CyberArk Conjur is not currently in the Terraform Registry. You must follow its installation instructions before running terraform init.

These steps are only required if using CyberArk Conjur as an external secrets manager.

1. Download the CyberArk Conjur provider.
2. Copy the custom provider to ~/.terraform.d/plugins/localhost/cyberark/conjur/<version>/<architecture>/terraform-provider-conjur_v<version>

   $ mkdir -vp ~/.terraform.d/plugins/localhost/cyberark/conjur/0.6.7/darwin_arm64/
   $ unzip ~/terraform-provider-conjur_0.6.7-4_darwin_arm64.zip -d ~/.terraform.d/plugins/localhost/cyberark/conjur/0.6.7/darwin_arm64/
   $

3. Create a .terraformrc file in the user's home:

   provider_installation {
     filesystem_mirror {
       path    = "/Users/example/.terraform.d/plugins"
       include = ["localhost/cyberark/conjur"]
     }
     direct {
       exclude = ["localhost/cyberark/conjur"]
     }
   }

Terraform installation

Terraform can be downloaded for free from here. This site has also instructions how to install it on various supported platforms.

Deployments of CML using Terraform were tested using the versions mentioned below on Ubuntu Linux and macOS.

$ terraform version
Terraform v1.8.0
on darwin_arm64
+ provider registry.terraform.io/ciscodevnet/cml2 v0.7.0
+ provider registry.terraform.io/hashicorp/aws v5.45.0
+ provider registry.terraform.io/hashicorp/azurerm v3.99.0
+ provider registry.terraform.io/hashicorp/cloudinit v2.3.3
+ provider registry.terraform.io/hashicorp/random v3.6.1
+ provider registry.terraform.io/hashicorp/vault v4.2.0
+ provider localhost/cyberark/conjur v0.6.7
$

It is assumed that the CML cloud repository was cloned to the computer where Terraform was installed. The following command are all executed within the directory that has the cloned repositories. In particular, this README.md, the main.tf and the config.yml files, amongst other files.

When installed, run terraform init to initialize Terraform. This will download the required providers and create the state files.

Cloud specific instructions

See the documentation directory for cloud specific instructions:

• Amazon Web Services (AWS)
• Microsoft Azure

Customization

There's two Terraform variables which can be defined / set to further customize the behavior of the tool chain:

• cfg_file: This variable defines the configuration file. It defaults to config.yml.
• cfg_extra_vars: This variable defines the name of a file with additional variable definitions. The default is "none".

export TF_VAR_access_key="aws-something"
export TF_VAR_secret_key="aws-somethingelse"

# export TF_VAR_subscription_id="azure-something"
# export TF_VAR_tenant_id="azure-something-else"

export TF_VAR_cfg_file="config-custom.yml"
export TF_VAR_cfg_extra_vars="extras.sh"

A typical extra vars file would look like this (as referenced by extras.sh in the code above):

CFG_UN="username"
CFG_PW="password"
CFG_HN="domainname"
CFG_EMAIL="[e-mail]"

In this example, four additional variables are defined which can be used in customization scripts during deployment to provide data (usernames, passwords, ...) for specific services like configuring DNS.

See the AWS specific document for additional information how to define variables in the environment using tools like direnv ("Terraform variable definition").

Additional customization scripts

The deploy module has a couple of extra scripts which are not enabled / used by default. They are:

• request/install certificates from LetsEncrypt (03-letsencrypt.sh)
• customize additional settings, here: add users and resource pools (04-customize.sh).

These additional scripts serve mostly as an inspiration for customization of the system to adapt to local requirements.

Requesting a cert

The letsencrypt script requests a cert if there's none already present. The cert can then be manually copied from the host to the cloud storage with the hostname as a prefix. If the host with the same hostname is started again at a later point in time and the cert files exist in cloud storage, then those files are simply copied back to the host without requesting a new certificate. This avoids running into any certificate request limits.

Certificates are stored in /etc/letsencrypt/live in a directory with the configured hostname.

Limitations

Extra variable definitions and additional scripts will all be stored in the user-data that is provided via cloud-init to the cloud host. There's a limitation in size for the user-data in AWS. The current limit is 16KB. Azure has a much higher limit (unknown what the limit actually is, if any).

All scripts are copied as they are including all comments which will require even more space.

A potential solution to the data limit is to provide the scripts in storage by bundling them up into a tar file or similar, store the tar file in S3 and then only reference this file in the user-data. However, this hasn't been implemented, yet.

EOF