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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 Flows is our embedded workflow automation platform, built on n8n, which we consider the best workflow automation tool available. It's fully integrated into Makini and runs on our infrastructure. Flows allows you to build complex integration logic using a visual workflow builder—no code required, though code is supported for advanced use cases. Workflows can be triggered by schedules, webhooks, API calls, or events from connected systems. You can perform data transformations, implement conditional logic, call external APIs, and orchestrate multi-step processes. Flows includes over 1,000 pre-built connectors beyond Makini's industrial systems, enabling integrations with databases, messaging platforms, cloud services, and more. Most customer activations are completed using Flows due to its flexibility and ease of use.
Connection-specific errors often relate to system configuration, permissions, or connectivity issues. Common scenarios include: the system is offline or unreachable, credentials have expired, API rate limits on the source system, or permission changes in the source system. Use the connection status endpoint to check connection health before making API calls. Implement circuit breaker patterns—if a connection repeatedly fails, temporarily stop making requests to avoid cascading failures. Log connection-specific errors separately to identify problematic connections. When errors occur, check if the issue affects all operations or specific entity types, which helps narrow down permission or configuration issues. For on-premises systems, verify network connectivity and firewall rules. Contact support if connection errors persist, providing the connection ID and affected 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.
