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Connecting to any system through Makini is straightforward. You select the product you want to connect to, log in with your credentials, and receive an API token. The process takes just a few clicks and works consistently across all 2,000+ supported systems. For most systems (85-90% of cases), you only need the instance URL, username, and password. Some systems may require additional steps like API token generation, and we provide detailed authentication guides for these cases. The connection experience is designed to be simple enough that non-technical users can complete it without IT support.
Makini's unified API acts as a common denominator across all connected systems. We map each system's data structure to a standardized data model, exposing consistent endpoints regardless of the underlying platform. This means you write the same code to retrieve purchase orders from SAP, NetSuite, or Dynamics—the API calls and response formats are identical. You always get data in the same structure, making it easy to build consistent business logic. The unified approach eliminates the need to learn each system's unique API, manage multiple authentication methods, or handle varying data formats.
Testing should cover authentication, data retrieval, data writing, error handling, and workflow logic. Start by connecting a test system through Makini's authentication flow. Use sandbox or non-production instances of your target systems when available. Test API calls for each entity type you'll use (purchase orders, work orders, etc.) to verify data mapping and field coverage. Test error scenarios by providing invalid inputs or attempting operations without proper permissions. For workflow-based integrations, test each workflow step independently before testing end-to-end. Verify webhook delivery and signature verification. Test with realistic data volumes to identify performance issues. Include tests for connection failure scenarios and verify your error handling and retry logic work correctly.
Makini provides several performance monitoring capabilities. API responses include timing information showing request processing time. The dashboard includes performance metrics showing average response times, throughput, and error rates over time. You can set up alerts for performance degradation or error rate increases. Each request generates a unique request ID that enables detailed performance analysis. For workflow-based integrations, execution logs show per-step timing, helping identify bottlenecks. We recommend implementing client-side monitoring to track end-to-end latency including network time. Monitor trends over time rather than individual requests—occasional slow requests are normal, but sustained increases may indicate issues requiring investigation.
