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Rhino Fleet Tracking is a GPS fleet tracking solution providing vehicle location, geofencing, idle reporting, and driver behavior for small fleets.
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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.
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 uses cursor-based pagination for retrieving large datasets. API responses include a next_cursor field when additional results are available. To retrieve the next page, include the cursor value in your next request: GET /api/v1/purchase-orders?cursor=CURSOR_VALUE. Cursor-based pagination is more reliable than offset-based pagination because it handles data changes between requests—if records are added or deleted while you're paginating, you won't miss records or see duplicates. Page size is configurable up to a maximum limit (typically 100-500 records per page depending on entity type). For optimal performance, use the largest page size your application can handle efficiently. The API response also includes total count when available from the source system.
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.
