Use Lucidscale to import cloud infrastructure data from AWS and generate diagrams in a Lucidscale model.

To learn more about functionality available with a Lucidscale license, see our Lucidscale Plans article. To purchase a license, view the Lucidscale pricing page.

Watch: Import AWS cloud infrastructure

Supported regions, resources, and lines

You can import AWS accounts hosted in any of the following AWS regions:

ap-northeast-1
ap-northeast-2
ap-northeast-3
ap-south-1
ap-southeast-1
ap-southeast-2
ca-central-1
eu-central-1
eu-north-1
eu-west-1
eu-west-2
eu-west-3
sa-east-1
us-east-1
us-east-2
us-west-1
us-west-2

Lucidscale supports the following AWS resources:

ALB (Load Balancers v2, Target Groups, Target Health Description)
API Gateway (v1, v2)
AWS Managed Streaming for Kafka
Autoscaling (Groups, Launch Configurations)
CloudFront (Distributions)
CloudTrail
Curated data for Transit Gateway Routes and NACLS
Customer Gateway
DocumentDB
DynamoDB (Tables)
EC2 (Instances, NAT Gateways, Network ACLs, Route Tables, Security Groups, Subnets, Transit Gateway, Volumes, VPC Endpoints, VPC Peering Connections, VPCs, VPN Gateways)
ECS: This is located in a designated view called “ECS View”. The current functionality will provide a view of the clusters, services and tasks running in your environment. It also splits clusters into EC2 and Fargate containers.
EFS File System
EKS clusters
Elasticache
Elastic Network Interface
Elastisearch
ELBs (Load Balancers)
EMR
Glacier
Kinesis Data Streams
Kinesis Firehose
Lambda (Functions)
Network Firewalls
RDS (Clusters, Instances)
Redshift (Clusters)
Route 53
S3 (Buckets - Additional Metadata: roles, groups, etc.)
SNS (Topics, met)
SQS (Queues)
Step Functions
Transit Gateway Routes Metadata

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

Elastic Load Balancers (ELBs) to Auto Scaling Groups (ASGs) [ELB→ ASG]
ELBs to EC2 instances [ELB → EC2]
CloudFront Distributions to S3 Buckets [CloudFront → S3]
Application Load Balancers (ALBs) to EC2 [ALB → EC2]
VPC Peering Connections
Route 53 Hosted Zones to ELBs, S3 Buckets and CloudFront Distributions [Route 53 Hosted Zones → ELBs, S3, CloudFront]
SNS Topic to SQS Queue [SNS → SQS]
SQS Queue to Lambda Function [SQS → Lamba]
Transit Gateway to Peered Transit Gateway and Virtual Private Cloud (VPC) attachments [Transit Gateways → Transit Gateways, VPCs]
Route Table to Internet Gateways and NAT Gateways [Route table → Internet Gateways, NAT Gateways]
API Gateway to Lambda [API Gateway → Lambda]
VPN Connections via Transit gateway [Transit Gateway → VPN Connection → Customer Gateway]
VPN Connections via VPN gateway [VPN Gateway → VPN Connection → Customer Gateway]
HostedZones → ALBs

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

Import AWS infrastructure

You can import data about your AWS cloud infrastructure using one of the two following methods:

provide a cross-account IAM role with the proper policies
run a script from your CLI (which pulls the data locally) then provide the generated JSON file.

If you are working with a very large environment, use the information in the Account configuration section of this article when using cross-account roles to help reduce the amount of data you are importing, or reduce the number of API calls Lucidscale makes to AWS. The Data Hub supports up to five concurrent imports. To import more than five accounts, you will need to wait for one to finish and then start another.

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

To import and render AWS infrastructure in a Lucidscale model, follow these steps:

Click + New on the Lucid Home Page.
Hover your cursor over Lucidscale.
Select AWS.
Choose to create a model with a previously imported AWS account or click Open Data Hub to import a new account to the Lucid Data Hub and render it in a Lucidscale model.
Select Open Data Hub.
Click + New Account and you choose an import method.
- After choosing an import method and completing the import, the account will be listed as a data source in the "AWS: Imported Accounts" section of the Data Hub. You can also find it listed as an imported AWS account in the modal after clicking + New > Lucidscale > AWS.
Click the three-dot menu next to the account you want to create a model from.
Select Create new model.
Review the details and add Filters to exclude unnecessary resources.
Select Create AWS 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.

modal_confirming_successful_creation_of_aws_lucidscale_model.png

Learn more: To learn how to work with AWS architecture in a Lucidscale model once it is rendered, read our article.

Import AWS accounts and create models via cross-account role (recommended)

To import AWS infrastructure via cross-account role and render a Lucidscale model, follow the steps below.

You’ll need to create a separate role for each new AWS account you want to import. You can do this by selecting the + New Cross-account Role in the “Select Credential” section of the Cross-account role import page.

Note: If you are on the Lucid GovSuite environment, you will only be able to import AWS GovCloud accounts via cross-account role. The Lucid commercial environment cannot access AWS GovCloud accounts via cross-account role. Refer to the FAQ section below for more details.

Create a new cross-account role

On the Lucid Home Page, click + New.
Hover your cursor over Lucidscale.
Select AWS.
Choose to create a model from a previously imported AWS account or click Open Data Hub to import and render a new account.
After clicking Open Data Hub, click + New Account.
Select Cross-account Role.
Click Create a new Cross-Account Role in the upper-right corner of the import modal.

On the next page of the modal, you have two options to create a new role:

To create a new role automatically with CloudFormation, follow these steps:

Ensure “Include ReadOnlyAccess” is enabled.
- This setting is enabled by default and is required for all resources to appear correctly in your rendered Lucidscale models.
Click Launch CloudFormation to open a new browser tab and log in to your AWS account. Leave your Lucid browser tab open so you can return to it later.
Click Create Stack.
After the stack has been created, navigate to the Resources tab and select the “LucidscaleImportRole”.
Skip to the steps to Add a cross-account role to Lucidscale.

To manually create a new role in the AWS IAM Console, follow these steps:

Under “Step 1: Start creating a role” select Create role.
- You will be navigated to your AWS account. Leave your Lucid browser tab open so you can return to it later.
- Lucidscale will auto-generate a unique External ID associated with your Lucidscale account. This is in alignment with AWS security recommendations.
In AWS, click Next: Permissions.
On the “Add Permissions” page, search and select the ReadOnlyAccess policy.
- This setting is enabled by default in Lucid and is required for all resources to appear correctly in your rendered Lucidscale models.
Navigate back to the Lucid tab to "Step 2: Add custom permissions" and click Copy permissions to copy the JSON text file.
Navigate back to the “Create Role” page in AWS and click Create Policy. You will be directed to a new browser tab to create the policy.
On the “Create Policy” page, toggle to the JSON tab and paste the file you copied into the JSON tab into your AWS Console.
Click Next: Tags.
Add tags to the policy if you want, and click Next: Review.
Give the policy a name and description.
Click Create policy.
In the previous AWS tab where you were creating a new cross-account role, click the refresh button, and search for the name of the policy you just created.
Select the policy and click Next: Tags.
Add IAM tags to the role if you want, then click Next: Review.
Give the role a name and description and click Create role.

Add a cross-account role to the Data Hub

Click the role’s name to navigate to the role’s summary page.
Copy the string next to “Role ARN”.
Navigate back to your Lucid tab and scroll down to the "Add the Cross-Account Role to Lucidscale" section of the New AWS Account page.
Paste the string into the “Role ARN” field, populate the “Account Name” field, and click Next to save the cross-account role.
- The new role will then be displayed in the New AWS Account page with the “Role Name” you used.
- The cross-account role will also be displayed in the "AWS: Saved Credentials" section of the Data Hub.
Select the role and click Next.

Import accounts and create models

Select the account(s) you want to import to the Data Hub to generate a Lucidscale model.
Click Next.
- Using the instruction detailed in at the end of this section under "Account configuration," you can specify the regions you want to import and omit chosen resource types or metadata from the import by deselecting them. Deselected resource types and metadata will not be imported or rendered in a model created from the account.
Click Import AWS Account.

To find your AWS account after the import completes:

Click + New
Hover your cursor over Lucidscale and select AWS.
Select Create new model.
Review the details and add Filters to exclude unnecessary resources.
Select Create AWS 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 AWS architecture in a Lucidscale model once it is rendered, read our article.

Account configuration using a cross-account role

When importing an AWS account to the Lucid Data Hub using a cross-account role, you have the option to 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 a diagram.

use_the_check_boxes_to_select_the_resource_types_that_should_be_included_in_your_new_aws_account_in_lucidscale.png

Import AWS accounts and create models via IAM user credentials

To import AWS infrastructure via IAM user credentials, follow these steps:

On the Lucid Home Page, click + New.
Hover your cursor over Lucidscale.
Select AWS.
Choose to create a model with a previously imported AWS account or click Open Data Hub to import a new account to the Lucid Data Hub and render it in a Lucidscale model.
Select Open Data Hub and click + New Account.
Choose an import method.
Select + New Account.
Click IAM User.
Select Next.
Create or use an IAM user with at least the policy permissions given in the IAM Permissions section attached.
Choose to enter the IAM user credentials to Lucidscale or upload a CSV or AWS credentials file.
Click Next.
- You can specify the regions you want to import and omit chosen resource types or metadata from the import by deselecting them. Deselected resource types and metadata will not be imported or rendered in a model created from the account.
Click Import AWS Account.
- After the import completes, the account will be listed as an “imported” AWS account in the modal after clicking + New > Lucidscale > AWS.
- The account will also be displayed in the "AWS: Imported Accounts" section of the Data Hub.
Select Create new model.
Review the details and add Filters to exclude unnecessary resources.
Select Create AWS 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.

Learn more: To learn how to work with AWS architecture in a Lucidscale model once it is rendered, read our article.

Security note: Lucidscale will not store your AWS IAM credentials after performing the initial scan of your AWS infrastructure. Your credentials will be transferred to our servers using standard encryption methods. Clients may negotiate encryption protocols up to AES-256. We can store a cross-account role that only gives us “describe and list” access to your environment(detailed in the section above).

Create an IAM user

In order for Lucidscale to access your AWS infrastructure, you need to give Lucidscale the credentials for a new IAM user. See below for instructions on how to create these in your AWS console.

To create an IAM user with an inline policy for Lucidscale’s AWS import, follow these steps:

Open the AWS console.
Navigate to the Users section of Identity Access and Management (IAM).
Click Add Users and enter a name for the user.
- Check the box next to “Access Key - Programmatic access” so Lucidscale can use the access key to retrieve the information about your infrastructure.
Click Next: Permissions.
Select Attach existing policies directly.
Click Create policy and toggle to the JSON window in the newly opened browser tab.
In the Imported Accounts section of the Lucid Data Hub, click + New Account.
Select IAM User from the list of import methods.
Click Next.
Copy the json policy file from the modal.
Paste the json policy file into the JSON window on the “Create Policy” page in AWS.
Click Next: Tags.
Add IAM tags to the role if you want, then click Next: Review.
Give the policy a name and description.
Click Create Policy.
In the previous IAM console browser tab where you started creating a new user, click the refresh button and then search for the name of the policy you just created.
Select the policy and click Next: Tags.
Add IAM tags to your user if you want, then click Next: Review.
Review user details and click Create user.
Click Download .csv to store the access key ID and secret access key, and copy/paste these or upload the csv into Lucidscale.
Click Next.
- You can specify the regions you want to import and omit chosen resource types or metadata from the import by deselecting them. Deselected resource types and metadata will not be imported or rendered in the model created from the account.
Specify an alias name for your account and click Import AWS Account.
- After the import completes, the account will be listed as an “imported” AWS account in the modal after clicking + New > Lucidscale > AWS.
- The account will also be displayed in the "AWS: Imported Accounts" section of the data hub.
Select Create new model.
Review the details of your model and add Filters to exclude unnecessary resources.
Select Create AWS 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 AWS architecture in a Lucidscale model once it is rendered, read our article.

Import AWS accounts and create models via CLI

To import AWS infrastructure via CLI, follow these steps:

On the Lucid Home Page, click + New.
Hover your cursor over Lucidscale.
Select AWS.
Choose to create a model from an existing AWS account or click Open Data Hub to import and render a new account.
After clicking Open Data Hub, click + New Account.
Select AWS CLI Script.
Click Next.
Copy and run the provided script using your terminal’s command line interface to generate a JSON file.
- For step-by-step instructions, refer to the CLI Script Instructions below.
Upload the resulting JSON to Lucidscale, then click Next.
Give the account you are importing a name, then click Next.
- The account will be listed as an imported AWS account in the modal after clicking + New > Lucidscale > AWS.
- The account will also be displayed in the "AWS: Imported Accounts" section of the Data Hub.
Select Create new model.
Review the details and add Filters to exclude unnecessary resources.
Select Create AWS 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 AWS architecture in a Lucidscale model once it is rendered, read our article.

Streamlined CLI Script Instructions

Install Python 3.0-3.9.
Install the AWS CLI.
Run pip3 install botocore==1.27.77.
Configure the AWS CLI (instructions from AWS can be found here).
Run python3 awscliscript.py --profile “profile name” --regions us-east-1 us-west-1 which would produce an aws.json file.
Click + New.
Hover your cursor over Lucidscale and select AWS.
Choose to import an existing account
- You can also click Open Data Hub, + New Account, and select AWS CLI Script.
Upload the aws.json file into Lucidscale and click Next.
Give the account you are importing a name, then click Next.
- The account will be listed as an imported AWS account in the modal after clicking + New > Lucidscale > AWS.
- The account will also be displayed in the "AWS: Imported Accounts" section of the Data Hub.
Select Create new 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.

Detailed CLI script instructions

Install Python 3.0-3.9 (instructions can be found here). Ensure that you check the option Add Python to PATH in the installer.
Install the AWS CLI (instructions from AWS can be found here).
- Use the left panel to click through instructions such as Installing the AWS CLI and Configuring the AWS CLI.
Install botocore version 1.27.77 with pip3 by running pip3 install botocore==1.27.77.
- Lucidscale - AWS was developed off of botocore version 1.27.77, however, if you have a different version already installed, the import should still work. If it doesn't, then consider running the script in a python virtual environment which allows you to manage separate package installations for different projects. After running the script you can delete the virtual environment. Instructions for creating a Python virtual environment can be found here.
Configure the AWS CLI (instructions from AWS can be found here).
- A named profile is a collection of settings and credentials that you can apply to a AWS CLI command.
- Running aws configure will store the entered credentials into the profile named default. If you have multiple accounts we recommend creating named profiles for them. For example, if I have two accounts, preprod and prod and I store their credentials as two separate profiles, then I could easily describe the ec2 instances in preprod by doing aws ec2 describe-instances -- profile preprod. Then, to describe instances in prod I can change the profile argument to aws ec2 describe-instances -- profile prod.
- Instructions for setting up named profiles from AWS can be found here.
- The Lucidscale - AWS script will require you to supply the name of the profile(s) you want to import.
Run the Lucidscale - AWS script
1. -c or --count
  - Output a JSON file with details about the number of resources. Running the script with this flag takes a different path through the import script and will not output a JSON file which can be uploaded to Lucidscale - AWS
2. -a or --anon
  - Anonymize the data (hashes all strings)
3. -o or --output
  - Output the data to the supplied filename
4. -p or --profile
  - The name of the profile to use
5. -r or --regions
  - The regions to import
    - (example) python3 awscliscript.py --profile preprod --regions us-east-1 us-west-1
    - The command above runs the script and generates data for resources in the preprod profile living in the regions us-east-1 and us-west-1
    - The Lucidscale - AWS script has additional flags which can be used
6. An aws.json will be generated as output. Upload this file into Lucidscale to import your infrastructure to the Lucid Data Hub.
  - The account will be listed as an imported AWS account in the modal after clicking + New > Lucidscale > AWS.
  - The account will also be displayed in the "AWS: Imported Accounts" section of the Data Hub.
7. Select Create 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 AWS architecture in a Lucidscale model once it is rendered, read our article.

Note:

Windows users: use “Windows CMD” to run the script commands
MacOs users: use the terminal

Use the Data Hub to manage AWS infrastructure data and credentials

Access imported accounts

After importing your AWS account, it will be listed as a data source with the account name you specified in the "AWS: Imported Accounts" section of the Data Hub. From this section you can also click + New account to import a new account to the Data Hub.

Accounts listed in this section are data sources that can be used to create new Lucidscale models. Data sources (“Accounts”) contain the AWS account 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 AWS account.

The Cloud Inventory of each account can be seen on the right-hand side after selecting an account 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 your permissions policy attached to the cross-account role. If you elect to use “Create a new role automatically” with our CloudFormation Stack template, all resources in your account which are accessible by AWS’s ReadOnlyAccess policy will be rendered in the inventory. If you create a role manually with a custom policy, only the resource types specified in your attached permissions policy will be rendered in the inventory.

Click the three-dot menu rendered on an account to see six potential options: Create New Model, Update Account from AWS, Schedule update, Edit resources, Rename Account, and Delete account.

Create New Model will start rendering the AWS infrastructure associated with the account as a diagram in a new model’s workspace. The model will be generated in the background of your Lucid Home Page and we will notify you once it has been rendered through the status modal that appears in the bottom-right of the page.

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

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

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

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

Delete Account removes the imported account from the Lucid Data Hub and any models created from that account would lose the ability to update data from AWS.

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 AWS cross-account role import. IAM and CLI imports do not support this option.

Share and delete saved credentials

The Saved Credentials section in "Data Hub > AWS" lists the cross-account roles you can use to import your AWS accounts to the Data Hub. From this section, click + New Cross-account role to add a new set of credentials that can be used to import an AWS account.

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

example_of_aws_saved_credentials_page_in_the_lucidscale_data_hub.png

Share credential opens a modal where you can share a cross-account role with another user on your Lucid account by specifying their email address. Granting them access to the credential will allow them to import the associated AWS account 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 the cross-account role from the Data Hub. After deleting a credential, all accounts that were previously imported with that credential along with models created from those accounts will lose the ability to update data from AWS.

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.

Security information

Cross-Account roles

Cross-Account roles are the preferred method from AWS for granting 3rd party access to your account. This method allows Lucidscale to securely store credentials that allow you to easily refresh a diagram. See these resources for more information:

Enforced External ID

Following the best security practices provided by AWS, Lucid enforces that External IDs remain unique in Lucid's database. Therefore, Lucid provides a unique External ID to the user and disallows the user from entering in their own External ID.

Secure, limited access for IAM users

We request limited, “describe”-level permission for the IAM user you create. An IAM user created with these permissions cannot change settings in your AWS infrastructure or read data in your databases. We only use the IAM user to read the structural metadata of your AWS infrastructure.

CLI script alternative

If you wish to review and control the actions we take during our AWS infrastructure scan, you can download and use our provided Python script instead of creating an IAM user. In this scenario, your IAM credentials will never be passed to Lucidscale, and you can review both the code that will run in your environment and the resulting metadata before uploading the metadata to Lucidscale. The imported JSON will be accessible in the Lucid Data Hub to use for creating Lucidscale models.

Safe storage of documents (models)

Lucidscale stores the AWS imported metadata and generated models using industry standard protections for confidential data. Imported AWS data is embedded as part of the Lucidscale model, so you can control access to the data using Lucid’s standard sharing permissions. For additional information regarding how we protect your documents, please refer to our Content Security page or contact our sales team.

No storage of access keys

Lucidscale will not store your AWS IAM credentials after performing the initial scan of your AWS infrastructure. Your credentials will be transferred to our servers using standard encryption methods. Clients may negotiate encryption protocols up to AES-256. We can store a Cross-Account Role that only gives us “describe and list” access to your environment.

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 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 AWS environment? What level of access does Lucidscale have?

The recommended method from Lucidscale and AWS is through a Cross-Account Role. We provide a policy which gives us “describe and list” access to your environment so we can get an inventory of resources. The credentials stored in Lucid can only be accessed by your Lucid account. This import method will allow you to update data from the account with one action. The permissions policy we provide allows you to determine exactly what data the Cross-Account role will have access to request from AWS.

If you use our IAM user method, credentials are not stored at all, but rather are used once and discarded. Generally our users use this import method along with AWS temporary credentials, as this method doesn't allow for additional data updates.

We also have a method using a python script you can run through the Command Line Interface (CLI) which generates a JSON file. After generating the JSON file, users can review the contents and remove data if desired prior to importing. Users can then upload this JSON file to Lucidscale and not populate any credential information into Lucidscale.

How do Lucidscale commercial and Lucidscale for Gov interact when importing via cross-account roles?

While the functionality of the product is the same for each, AWS sets up security differently for these two environments. AWS IAM roles and resource-based policies delegate access across accounts only within a single partition. Lucid GovSuite is in a separate AWS partition, and thus can’t import AWS data via cross-account role from non-GovCloud AWS accounts. Cross-account roles, our recommended import method, only allow access to accounts of the same type—so if you are on the Lucid commercial environment you can access and import commercial AWS cloud accounts via cross-account role, and if you are on the Lucid GovSuite environment you can access and import AWS GovCloud accounts via cross-account role.

We do support the ability to import commercial AWS accounts to Lucidscale for Gov via IAM user or a JSON created from our CLI script.

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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