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Makini supports over 2,000 industrial systems across ERP, CMMS, and WMS categories. This includes major platforms like SAP (ECC, S4/HANA, Business One), Oracle NetSuite, Microsoft Dynamics, IBM Maximo, and specialized industrial systems. We support both cloud-based and on-premises installations. If you need to connect to a system we don't currently support, we're committed to building that integration for you at no additional charge—most new integrations are completed within one business day. You can view our full list of supported systems at makini.io/integrations.
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.
Makini provides webhook testing tools in the dashboard where you can trigger test webhook deliveries to verify your endpoint configuration. Test webhooks use sample payloads matching actual event structures. Verify your endpoint receives the webhook, validates the signature correctly, and responds with a 200 status code within 10 seconds. Test webhook retries by having your endpoint return error codes or timeout, then verify Makini retries as expected. Test duplicate handling by processing the same webhook multiple times. For local development, use tools like ngrok to expose your local endpoint for webhook testing. The webhook logs in the Makini dashboard show delivery attempts, response codes, and timing, helping debug delivery issues.
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.
