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Yes, Makini supports both cloud-based and on-premises systems. For on-premises installations, connections require double the connection credits compared to cloud systems. The connection process typically requires opening specific ports and whitelisting Makini's IP addresses in your firewall configuration. For some on-premises systems, VPN tunnels may be necessary. We provide detailed technical requirements during implementation planning. In cases where security policies prohibit external connections, we offer self-hosted deployment options where Makini runs entirely within your infrastructure, eliminating the need for external network access to on-premises systems.
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.
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.
If you continue to experience problems with your NetSuite M2M connection after following the troubleshooting steps, contact Makini support at support@makini.io. You can also refer to the NetSuite API Documentation and Makini Documentation for additional technical details.
