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The initial sync occurs when you first connect a system and retrieves historical data to establish a baseline. This includes records from a configurable time period (typically 30-90 days) and can take several minutes to hours depending on data volume. Initial syncs are complete snapshots of the requested data. Incremental syncs occur on subsequent runs and retrieve only records created or modified since the last successful sync. Makini tracks sync timestamps and uses them to query for changes efficiently. Incremental syncs are much faster, usually completing in seconds to minutes. This approach minimizes API load on source systems while keeping your data current.
Makini sends webhooks for several event types: sync completion (successful or failed), connection authentication required (when credentials need renewal), connection status changes (online/offline), and system errors requiring attention. Each webhook payload includes the event type, timestamp, connection ID, and event-specific details like error messages or affected entities. You can configure which events trigger webhooks on a per-connection basis. For workflow-based integrations using Makini Flows, you can also set up custom webhooks triggered by specific conditions in your business logic, providing granular control over real-time notifications.
500-level errors indicate issues on Makini's side or with the connected system. These are typically temporary and retrying the request after a brief delay often succeeds. Implement exponential backoff for retries—wait a few seconds, then progressively longer intervals. If errors persist beyond a few retries, check the Makini status page for service disruptions. The error may also stem from the connected system experiencing issues rather than Makini itself. For persistent 500 errors, contact support with the request ID from the error response. Include details about when the error started, which operations are affected, and which connections are impacted. Our support team can quickly identify whether the issue is systemic or connection-specific.
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.
