Lucidscale allows you to import cloud infrastructure data from Google Cloud (formerly GCP) and generate diagrams from that data in a Lucidscale model.

Lucidscale is available to Lucid Suite Enterprise accounts as an add-on purchase with the Cloud Accelerator. To learn more about the Cloud Accelerator, refer to our Cloud Accelerator overview article.

Watch: Import Google Cloud infrastructure

Supported resources and lines

Lucidscale supports the following Google Cloud resources:

Bigtable Instances
Big Query Datasets
Cloud DNS
Cloud functions
Cloud Routes
Cloud routers
Compute (Autoscalers, Instances, Instance Groups)
Database (SQL Instances)
Firewalls
GKE Cluster View
Google Kubernetes Engine (Google Cloud Side, not Kubernetes depth)
Interconnect ( Dedicated Interconnects + Partner Interconnects)
IPsec VPN
Manage (Project, Zone)
NAT Gateway
Network (Firewall, Network, Subnetwork)
Node Pools
Persistent disk
Shared VPC View
Storage (Bucket)
VLAN Attachments (interconnectAttachments)
VPN tunnels
VPN Gateways

We can draw lines between resources that explicitly reference another in the metadata:

Google Cloud VPC Network Peering [Network → Network]
Instance to Subnetwork (Shared VPC line)

Note: If you’ve elected to summarize resources within a Lucidscale View, you will need to un-summarize them in order for lines to be rendered in the model.

Import Google Cloud infrastructure

You can import Google Cloud Infrastructure using one of the two methods: providing a Google Cloud service account with the proper policies; or running a script from your Command Line Interface (CLI).

If you are working with a very large environment, use the instructions found in the Project configuration section of this article to help reduce the amount of data you are importing or reduce the number of API calls Lucidscale makes to Google Cloudx. The Data Hub supports up to five concurrent imports. If you want to import more than five projects, you will need to wait for one to finish and then start another.

Note: If you import using the service account method, Lucidscale saves service accounts in the Data Hub so that you can use them in the future without having to re-enter your account information.

To render Google Cloud infrastructure in a Lucidscale model:

Click + New on the Lucid Home Page.
Hover your cursor over "Lucidscale".
Select Google Cloud Model.
Choose to create a model with a previously imported Google Cloud project or click Open Data Hub to import a new project.
Click + New Project and choose an import method.
- After choosing an import method and completing the import, the project will be listed as a data source in the "Google Cloud” section in the Data Hub. You can also find it listed as an “imported” Google Cloud project in the modal after clicking + New > Lucidscale > Google Cloud Model.
Click the three-dot menu next to the account you want to create a model from.
From the menu, select Create new model.
Review details and select views to only add necessary resources.
Select Create Google Cloud Model.

The Lucidscale model will generate in the background of your Lucid account. We will notify you once it has been rendered through the status modal that appears in the bottom-right of the page.

You can open the model from the status modal that renders directly after creating a new model. The model (and previously created models) will also be stored and accessible in the "Documents" section of your Lucid Home Page after you generate it.

how

Learn more: To learn how to work with Google Cloud architecture in a Lucidscale Model once it is rendered, check out the linked article.

Import projects and create models via Service Account (Recommended)

To import Google Cloud infrastructure via service account and render a Lucidscale model, follow these steps:

On the Lucid Home Page, click + New.
Hover your cursor over Lucidscale.
Select Google Cloud Model.
Click + New Project.
Select Google Cloud Service Account (Recommended).
Click Create a new Service Account.
In Lucid, select between the two options to assign a role to the Service Account. Click the following link that corresponds with the selection you made in Lucid:
- Use a read-only role for all resources (Recommended)
- Create a custom role with minimum permissions

Step 2: Assign a role to the Service Account using a read-only role for all resources (Recommended)

In the next modal under “Step 1: Create a new Service Account”, click Create Service Account to open a new tab and log in to your Google Cloud account. Leave the Lucid browser tab open so you can return to it as needed.
Ensure the “Use a read-only role for all resources (Recommended)” option is selected.
In your Google Cloud console, click Create Service Account.
Add the Service Account Details and click Create and Continue.
Click the “Select a role” dropdown menu.
Select Basic.
Click Viewer.
Click Done.
Skip to Step 3: Generate a JSON key and add the service account to Lucidscale.

Step 2: Assign a role to the Service Account by creating a custom role with minimum permissions

In your Lucid tab, select the “Create a custom role with minimum permissions” option.
Click Download luciscale.yaml to download the yaml file to your computer.
Select the Organization Level or Project Level tab depending on which level of data you want to visualize within Lucidscale.
- In this example, we will be using the Project Level option.
Copy the resulting line of code displayed.
Navigate to your Google Cloud console and sign in.
Click on Activate Cloud Shell.
Click the three-dot icon above the Cloud Shell terminal and select Upload.
Browse to the previously downloaded yaml file and upload it.
Paste the copied line of code (from step 4 above) into the terminal and replace the following values within the line of code:
- role-id = the value that you want to use for your role ID
- project-id = your Google Cloud project ID
- yaml-file-path = path to the .yaml file
- The end result should look something like this (using fake values):
  - gcloud iam roles create lucidscalerole --project=test-project-id --file=lucidscale.yaml
- If you are using the Organizational Level line of code, the example would look something like this (also using fake values):
  - gcloud iam roles create lucidscalerole --organization=test-organization-id --file=lucidscale.yaml
Click Authorize.
In the terminal, you will be given the prompt “Are you sure you want to make this change (Y/N)?”. Type in “Y” and click Enter.
Continue on to Step 3: Generate a JSON key and add the Service Account to Lucidscale below.

Step 3: Generate a JSON key and add the Service Account to Lucidscale

In your Google Cloud console, select the Service Account you created in step 1.8.
Click the “Keys” tab.
Select Add Key and click Create new key.
Choose JSON as the “key type”.
Click Create.
A JSON file will be downloaded to your device.
Navigate back to your open Lucid browser tab.
Select Choose file.
Locate and select to upload the JSON file you downloaded in step 6.
Click Next.

Step 4: Add projects and create models

Select the project(s) you want to import to the Data Hub and use to generate a Lucidscale model.
Click Next.
Select resources to import.
Select Import Google Cloud projects.

Learn more: To learn how to work with Google Cloud architecture in a Lucidscale Model once it is rendered, check out the linked article.

Project configuration using a Service Account

When importing a Google Cloud project to the Lucid Data Hub using the service account method, you can omit chosen resource types or metadata from the import. This grants you the ability to visualize only resource types you’re interested in and in some cases can increase the speed of the import. Deselected resource types and metadata will not be imported or rendered in the diagram.

google-cloud-lucidscale-project-select-resources-to-import.png

Import projects and create models via Google Cloud CLI

Install Python if you don't have it already. Instructions can be found here. Ensure that you check the option “Add Python to PATH” in the installer. You can verify that Python was properly installed by trying the commands “python” or “python 3” in a terminal (MAC OS) or Command Prompt (Windows).

On the Lucid Home Page, click + New.
Hover your cursor over Lucidscale.
Select Google Cloud Model.
Choose to create a model from an existing Google Cloud project or click Open Data Hub to import and render a new project.
Click + New Project.
Select Google Cloud CLI Script.
Open your terminal or command prompt, and run the command: Pip3 install oauth2client google-api-python-client
Initialize the Gcloud SDK by running the command: gcloud init
Authenticate the Gcloud SDK by running the command: gcloud auth application-default login
In the “New Google Cloud Project” modal in Lucid, click Download Script.
- A file named “gcpcliscript.py” will be downloaded.
Browse to the downloaded location of the script, and run the command: python3 gcpcliscript.py --projects [project_id [project_ids...]] [-c] [-o <output file>]
- project_ids: Project ids, can be found on the Google Cloud console under project list
- -c: outputs the count.json file which contains the count of compute resources in the specified Google Cloud projects (optional)
- -o: name of the output file
- e.g. python3 gcpcliscript.py --projects bubbly-xxxxxx-233220 summer-alliance-254420 gcpdev-272652
Return to the “New Google Cloud Project” modal in Lucid and click Choose File.
Select and upload the gcp.json generated from the script.
Click Next.
Edit the name of the project and click Next.
- After the import completes, the project will be listed as an Imported Google Cloud project in the modal after clicking + New > Lucidscale > Google Cloud Model.
- The project will also be displayed in the Data Hub > Google Cloud: Imported Projects section.
Select Create new Model.
Review the details and add Filters to exclude unnecessary resources.
Select Create Google Cloud Model.

The Lucidscale model will generate in the background of your Lucid account. We will notify you once it has been rendered through the status modal that appears in the bottom-right of the page.

Learn more: To learn how to work with Google Cloud architecture in a Lucidscale Model once it is rendered, check out the linked article.

Use the Data Hub to manage imported Google Cloud Infrastructure data and credentials

Imported projects

After importing the Google Cloud project data, it will be listed as a data source with the project name you specified in the "Google Cloud: Imported Projects" section of the Lucid Data Hub. From this section you can also click + New Project to import a new project to the Data Hub. The Google Cloud projects you have imported will be listed individually in the Data Hub.

Projects listed in this section are data sources that can be used to create new Lucidscale models. Data sources (“Projects”) contain the Google Cloud project metadata used to create Lucidscale models. The “Last updated” field indicates when your data source was last refreshed to account for any updates in your connected Google Cloud project.

The Cloud Inventory of each project can be seen on the right-hand side after selecting a project from the list. This inventory allows you to see a full count of each type of resource that has been imported before creating a model. You can also download a CSV with the list of resources and count directly from the Data Hub by clicking Download CSV.

The inventory lists all resources that can be accessed by the role permissions assigned to your Service Account. If you elect to “Use a read-only role for all resources”, all resource types in your project which are accessible by Google Cloud's “Viewer” role will be rendered in the inventory. If you create a custom role, only the resource types specified in your assigned role permissions will be rendered in the inventory.

Select the three-dot menu rendered on a project to see up to six potential options: Create new Model, Update project from Google Cloud, Schedule update, Edit resources, Rename Project, and Delete Project.

Create new Model will start rendering the Google Cloud infrastructure associated with the project as a diagram in a new model’s workspace. The model will be generated in the background of your Lucid Home Page and you’ll be notified once it has been rendered through the status modal that appears in the bottom right of the page.

Update Project from Google Cloud and Schedule update allows you to manually or automatically update the Google Cloud project data you have imported to the Data Hub to reflect any changes in the connected Google Cloud project. New models created from the project after the update will reflect any changes in the connected Google Cloud project.

Learn more: For more information about updating projects from Google Cloud, refer to our Update and sync data in Lucidscale article.

Edit resources allows you to edit the resources included in each dataset. Selecting this option will open up a modal in which you can add or remove any resources from existing datasets. When you’ve finished with the selection, click Save and update Project. This will ensure that the dataset refreshes and models referencing that dataset are updated to the latest information.

Rename Project allows you to change the name of the selected dataset.

Delete Project removes the imported project from the Lucid Data Hub and any models created from that project would lose the ability to update data from Google Cloud.

Note: The options displayed above will vary depending on the import method you’ve used for an account. The update option is only available with Google Cloud Service Account import. CLI imports do not support this option.

Saved credentials

The Saved Credentials section in "Data Hub > Google Cloud" will list the Google Cloud service accounts you can use to import Google Cloud projects to the Data Hub. From this section you can click + New Service account to add a new set of credentials that can be used to import a Google Cloud project.

You can also share the service accounts you have created with other users. If you click the three-dot menu rendered on a service account, you will see two potential options: Share credential and Delete credential.

Share credential opens a modal where you can share a service account you created with another user on your Lucid account by specifying their email address. Granting them access to the service account will allow them to import the associated Google Cloud project to the Data Hub and create Lucidscale models. After a credential has been shared with another user, you can revoke their access to the credential by clicking the X next to their email address in the same modal.

Delete credential removes a service account from the Data Hub. After deleting a service account, all projects that were previously imported with that credential along with models created from those projects would lose the ability to update data from Google Cloud.

Learn more: You can only share credentials in the Data Hub that you own. Only Lucidscale users assigned a Creator license can import accounts and create models. For more details check out our Credential management, usage, and security in Lucidscale article.

FAQ

Once Lucidscale is purchased, will every user on the account have access?
If you are an existing Lucid customer (currently have a Lucidchart or Lucidspark subscription), depending on your account's licensing settings it is possible not all users on the account will have access to Lucidscale by default. An account admin may need to assign the Lucidscale licenses purchased to individual users or groups through the Users section of the Admin Panel in the same manner as Lucidchart and Lucidspark. Users added to an account that only has a Lucidscale Team subscription (no current Lucidchart or Lucidspark subscriptions) will be automatically assigned either a Creator or Explorer license depending on which licenses have been purchased. For instructions on how to grant licenses, check out Lucid admin panel: License settings article.

How does Lucidscale get access to our Google Cloud environment? What level of access does Lucidscale have?
The recommended method from Lucidscale and Google Cloud is through a Google Cloud Service Account. We provide a policy which gives us “describe and list” access to your environment so we can get an inventory of resources.

We also have a method using a python script you can run through the Command Line Interface (CLI) which generates a JSON file. Users can then upload this JSON file to Lucidscale and not populate any credential information into Lucidscale. Your imported JSON will be accessible in the Lucid Data Hub to use for creating Lucidscale models.

What APIs does Lucidscale access?
We primarily use describe and list API endpoints.

Can you choose which metadata (the fields and values shown in the Data panel) is imported? If not, what metadata is imported?
No, you can't currently choose what metadata is imported. However, we are looking to create some ability to do that in the future. All metadata from a describe API call is imported.

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