No-Code Integration Workspace From Configuration Files
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Solution Overview
Problem
Existing analytics platforms require trained integration engineers to create integrations with new digital software products, leading to bottlenecks and backlogs, and lack efficient access to real-time and historical data without straining public APIs.
Innovation Solution
A no-code system allows users to create integration templates using configuration files, which can be reviewed and published for others to access, utilizing endpoints and operations from vendor servers, and includes data management and visualization tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trained integration engineers are used to create integrations with new digital software products, then integration reliability is improved, but productivity deteriorates due to bottlenecks and backlogs
Solution Approach 1:
The system enables users to autonomously generate integrations without requiring trained integration engineers. Users can independently create integration templates by providing configuration files, selecting data fields, and defining workspaces through a no-code interface, thereby eliminating the bottleneck of expert dependency while maintaining integration quality through structured templates and automated validation
Solution Approach 2:
The system uses configuration files (such as Swagger or YAML files) as templates that define the structure and behavior of integrations. These templates are then instantiated multiple times with different parameters, allowing rapid replication of integration patterns without manual reconstruction, thus increasing productivity while preserving reliability through consistent template-based generation
2Ease of operation
If public APIs are used to access data, then ease of operation is improved, but productivity deteriorates due to rate limitations and strain on public APIs
Solution Approach 1:
The system introduces a private API layer that acts as an intermediary between users and public APIs. This private API provides authenticated access to data sources, enabling users to retrieve data without the rate limitations of public APIs. The private API handles authentication, authorization, and rate limiting internally, allowing high-volume data access while preserving the simplicity of programmatic access
Solution Approach 2:
The system segments data access into multiple authenticated instances, each with its own credentials and permissions. Instead of relying on a single public API endpoint with rate limits, the system creates multiple private API connections that can operate in parallel, thereby increasing overall data access capacity while maintaining ease of use through unified authentication mechanisms
Data Source
AI summary
A method for generating self-serve integrations includes receiving a network address of a configuration file that includes parameters to interface with a server. The method extracts, from the configuration file, endpoints and operation(s) available to manipulate each endpoint. The method displays a first table having a rows displaying (a) a given endpoint and (b) a menu for selecting a given operation to manipulate the given endpoint. The method, upon selection of a given row, displays input field(s) that accept a parameter, authorization, header, body, and/or response data. The method gathers, from the server, a data fields available at the given endpoint. The method displays a second table having rows that have data field(s), and input(s) for a data type, column type, a display name, unit, description, primary key, secondary key, and/or an indexing toggle.