Lucidscale can save a lot of time when creating large infrastructure diagrams, but it is much more than just an algorithm that translates data into shapes and lines. It is a powerful and dynamic visualization engine, and like other rendering engines, its operations can take time, processing power, and computer memory.

Here are our best tips to make the most out of working with large infrastructures to get the best performance in Lucidscale.

Import large datasets

Check Cloud Provider API rate limits

Lucidscale uses cloud provider APIs to import infrastructures. These API endpoints use customer account credentials and are bound to the API quotas of their cloud environment. Lucidscale currently calls these APIs as quickly as it can and in some cases may consume the available quota, resulting in throttling from your cloud provider. When this happens, the system will slow down and, if possible, continue importing at a slower pace.

Larger infrastructures can require more API calls to fetch data from the cloud provider. This increases the likelihood of exhausting API quotas, which can further increase wait times or cause the import to fail altogether.

If import wait times or failures become excessive, we recommend ensuring there is space available on your quota. For more information on quotas, or how to increase them, please refer to your cloud provider's documentation.

Narrow the dataset

A good practice is to keep imports small where possible. Methods for reducing import size vary depending on the cloud provider and the import method. Read the following information to see our recommended best practices for each provider.

For AWS Cross-account role imports, select only the accounts, regions, and resource types that are relevant as you go through the import process.
- To learn more, check out our Import and manage AWS infrastructure data in Lucidscale article.
For Entra ID (formerly Azure AD) Application imports, choose to only import subscriptions and resource types that you need.
- To learn more, check out our Import and manage Azure infrastructure data in Lucidscale article.
For Google Cloud (formerly GCP) Service Account Imports, choose to only import the resource types that you need.
- To learn more, check out our Import and manage Google Cloud infrastructure data in Lucidscale article.

Maximize workspace performance

Large diagrams not only require more computational power, but can also be difficult for viewers to interpret. We recommend limiting the number of shapes rendered in the model to the minimum required by setting filters, toggling resources, and summarizing shapes.

Set filters

Create filters in the main toolbar of a Lucidscale model.

To learn more about working with Filters in AWS, Azure, and Google Cloud, check out our articles.

Toggle Resources

toggle_eye_icon_in_resources_section_of_Lucidscale_data_panel.png

Show only the most relevant services by toggling the eye icon in the Resources section of the data panel.

To learn more about working with Resources in AWS, Azure, and Google Cloud, check out our articles.

Summarize shapes

toggle_on_summarize_shapes_in_display_options_section_of_layout_menu_in_Lucidscale.png

Summarize shapes of a particular resource type in the Layout menu.

To learn more about working with layout settings for resources in AWS, Azure, and Google Cloud, check out our articles.

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