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Industrial systems are often heavily customized, and Makini is built to handle this. For reading data, Makini can access virtually any field or custom table in connected systems. Through the connection settings interface, you can specify custom fields, tables, or entities to include in API responses. These show up alongside standard fields in the unified model. For custom objects not in our default model, you can request them through the interface and they'll be available immediately. For writing data, customization support varies by system but covers most common scenarios. During implementation, we work with you to identify required customizations and ensure they're properly configured before going live.
Makini provides a `/sync-status` API endpoint that returns the current synchronization state for a connection. The response includes the last successful sync timestamp, sync status (in progress, completed, failed), any error messages, and the next scheduled sync time. You can query this endpoint to monitor sync health and detect issues. For workflow-based syncs using Makini Flows, each workflow execution is logged with detailed status information including start time, completion time, success/failure status, and any errors encountered. The Makini dashboard also provides visual sync status monitoring across all connections.
Write operation limitations vary by system. Common limitations include: field-level restrictions (some fields may be read-only), business rule validation (orders may require certain fields or valid vendor codes), permission requirements (the connected account needs specific permissions), timing restrictions (some systems prevent modifications after certain workflow states), and rate limits on write operations. Custom fields in target systems may not be writable through standard APIs. Some systems have transactional requirements—for example, purchase order line items must be created in the same transaction as the order header. During implementation, we identify write operation limitations for your specific use cases and design workflows that work within those constraints.
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.
