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Makini is SOC 2 Type 2 compliant and undergoes penetration testing twice annually. We use industry-standard encryption protocols including TLS 1.2+ for data in transit and AES-256 for data at rest. Customer credentials are encrypted using secure key management practices. Our infrastructure follows security best practices including network segmentation, access controls, and regular security audits. For highly regulated industries or customers with strict compliance requirements, we offer self-hosted deployment options that keep all data within your infrastructure. We've successfully met security requirements for enterprises including financial institutions and government contractors.
Makini uses standard HTTP status codes and structured error responses. Error responses include an error code (e.g., `AUTHENTICATION_FAILED`, `RATE_LIMIT_EXCEEDED`), error type for categorization, a human-readable error message, and a unique request ID for support inquiries. Common status codes include 400 for invalid requests, 401 for authentication failures, 403 for permission issues, 429 for rate limiting, 500 for server errors, and 503 for service unavailability. Use the error code for programmatic error handling rather than parsing error messages. The request ID helps our support team quickly identify and investigate specific issues.
Yes, customers can connect as many systems as needed. Each connection is independent with its own API token, allowing you to manage multiple ERP systems, CMMS platforms, or other integrations for a single customer. This is common in organizations with multiple subsidiaries, regional systems, or during migration periods when legacy and new systems run in parallel. Each connection consumes connection credits based on the system type and deployment model. There's no technical limit on the number of connections per customer. For customers using multiple instances of the same system (like regional SAP instances), each instance requires a separate connection with its own credentials and token.
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.
