Autonomous Component Installation Overview

Modified on Tue, 2 Jun at 9:36 AM

The IDE Autonomous Client is a background application used to automate scheduled data exchange between host systems. It operates without user interaction and is typically deployed as an Azure App Service.

The client continuously monitors pending transfers, executes data exchange operations, maintains transfer history, and provides operational visibility through the Hangfire dashboard.

Purpose

The primary purpose of the Autonomous Client is to automate the exchange of data between external systems and ILAP Data Exchange while minimizing manual intervention.

Automate scheduled data transfers.
Monitor and process connector events.
Provide visibility into background processing through Hangfire.
Optionally store transferred ILAP files using SharePoint Online or local storage.

Azure Resources

A standard deployment provisions the following Azure resources:

Resource	Purpose
App Service Plan	Hosts the Autonomous Client application.
App Service	Runs the Autonomous Client and Hangfire dashboard.
Azure SQL Server	Database server hosting application data.
Azure SQL Database	Stores application configuration, state, and Hangfire metadata.
Azure Storage Account	Stores logs, artifacts, and transferred files.
Azure File Share	Stores application logs and generated files.
Azure Key Vault (Optional)	Stores certificates and encryption secrets.

Hosting Requirements

The required hosting capacity depends on the size and complexity of the schedules being processed. Based on internal testing, the following recommendations can be used as a starting point when sizing the Autonomous Client environment.

Schedule Size	Recommended Memory	Typical Azure App Service Tier
Up to 60,000 activities	Up to 16 GB RAM	Equivalent Azure App Service plan with approximately 16 GB memory capacity
60,000 to 150,000 activities	Up to 32 GB RAM	Equivalent Azure App Service plan with approximately 32 GB memory capacity

The number of activities is not the sole parameter used when estimating hosting requirements.

Actual memory consumption may vary depending on several factors, including:

• Number of links and relationships
• Number of resource assignments
• Number of destination activities
• Connector type and processing complexity
• Data volume being transferred

The recommendations above should therefore be considered a rough sizing guideline based on internal testing and should be validated during implementation.