Automated Connector Generation for Identity Provisioning Systems
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Solution Overview
Problem
The existing provisioning processes for user identities across multiple target systems are inefficient and prone to redundancy, human error, and high costs due to the need for custom-coded connectors and manual intervention, which cannot dynamically adjust to organizational changes.
Innovation Solution
A provisioning system with a connector creation module that analyzes the API of target systems to automatically generate connector modules, allowing for graphical mapping of parameters and routines, thereby automating the provisioning process across multiple systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual provisioning processes are used across multiple target systems, then flexibility in handling complex provisioning scenarios is maintained, but time consumption and human error increase significantly
Solution Approach 1:
The system enables self-service provisioning by allowing the provisioning system to automatically analyze target system APIs, generate appropriate connectors, and execute provisioning actions without requiring manual intervention for routine tasks. Users can define high-level provisioning rules and the system autonomously handles the complex technical details of connecting to multiple target systems.
Solution Approach 2:
Manual mechanical provisioning operations are replaced with automated software-based processes. The system uses programmatic API calls, automated connector generation, and rule-based decision-making to substitute manual administrative tasks, thereby increasing productivity while managing complexity through software intelligence rather than human operators.
2Reliability
If custom-coded connectors are created for each target system, then provisioning accuracy can be maintained, but development time and costs increase
Solution Approach 1:
The system performs preliminary analysis of target system APIs before actual provisioning occurs. By pre-analyzing API structures, authentication mechanisms, and data formats, the system generates ready-to-use connectors that are tailored to each target system's specific requirements, ensuring both accuracy and efficiency without time-consuming manual coding.
Solution Approach 2:
Instead of creating entirely new connectors from scratch for each target system, the system uses templates and parameter substitution. The connector framework allows dynamic adjustment of parameters such as API endpoints, authentication credentials, and data mapping based on the specific target system being connected to, thereby reducing development time while maintaining accuracy.
3Adaptability or versatility
If multiple separate provisioning processes are used for different target systems, then system-specific requirements can be met, but redundancy and inefficiency increase
Solution Approach 1:
The provisioning system implements a universal framework that can handle multiple different target systems through a single unified interface. The system analyzes the API of any target system and generates appropriate connectors automatically, allowing the same provisioning infrastructure to serve diverse target systems without requiring separate dedicated processes for each.
Solution Approach 2:
The system dynamically adapts its behavior based on the target system being provisioned. By analyzing the specific API characteristics of each target system in real-time, the system generates and executes appropriate provisioning processes on-the-fly, enabling high efficiency while maintaining the ability to handle diverse system requirements.
4Ease of operation
If manual provisioning is performed, then detailed control over provisioning parameters is maintained, but the likelihood of human error and compliance auditing requirements increase
Solution Approach 1:
The system incorporates feedback mechanisms that automatically validate provisioning parameters against predefined compliance rules and target system requirements. Before executing provisioning actions, the system verifies parameter validity, checks against organizational policies, and provides feedback on potential issues, thereby maintaining detailed control while significantly reducing human error and improving reliability.
Data Source
AI summary
Systems and methods for automating or at least partially automating the creation of connectors for a provisioning system are described. A provisioning system can include a connector creation module that analyzes an application programming interface (API) of a target system. Based on this analysis, the provisioning system can automatically create a connector module that can communicate with the target system. The connector creator may also provide a user interface that enables users to customize the functionality of the connector module. For example, a user can specify which routines of the target system API will be called by the connector module, which user identity parameters of the target system will be updated, and so forth. The connector creation module can automatically generate code for the connector module that implements the user-specified functionality. The finished connector module can be executed to provision the target system.