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All API requests require authentication via bearer token. After successfully connecting a system through Makini's authentication module, you receive an API token. Include this token in the Authorization header of your requests: Authorization: Bearer YOUR_API_TOKEN. Each connection has a unique token, allowing you to manage multiple customer connections independently. Tokens remain valid as long as the underlying system credentials are valid and the connection is active. If a customer changes their system credentials, you'll need to reconnect to obtain a new token.
Webhooks allow Makini to notify your application of events in real-time. To set up webhooks, configure a webhook URL in your connection settings or during the initial connection flow. Your webhook endpoint must accept POST requests, respond within 10 seconds with a 200 status code, and use HTTPS with a valid SSL certificate. Makini will send webhook payloads to your endpoint when configured events occur, such as sync completion, connection status changes, or errors requiring attention. We recommend keeping your webhook receiver lightweight—ideally just writing the payload to a queue for asynchronous processing—to avoid timeouts and ensure reliable delivery.
Yes, Makini supports write operations including creating, updating, and in some cases deleting records in connected systems. Common write operations include creating purchase orders, updating work order status, modifying inventory levels, and creating vendor records. Write support varies by system and entity type—core entities like purchase orders have comprehensive write support across major systems, while more specialized entities may have limited write support in some systems. Write operations use the same unified API, so the code to create a purchase order in SAP is identical to creating one in NetSuite. Validate write requirements during implementation to ensure your target systems support needed operations.
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.
