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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 implements automatic retry logic for failed webhook deliveries. If your endpoint is unavailable or returns an error status code, we retry delivery with exponentially increasing intervals starting at 30 seconds. Retries continue for up to 24 hours. If delivery ultimately fails, the webhook is logged but not delivered. You can view failed webhooks in the Makini dashboard and manually retry them. To prevent webhook loss during extended downtime, implement a polling backup strategy—periodically check the sync status and query for recent changes if no webhooks have been received within the expected time window. Design your webhook receiver to be idempotent, as retry logic may result in duplicate deliveries.
The `RATE_LIMIT_EXCEEDED` error indicates you've exceeded the API rate limit for the connection or account. Rate limits are typically set per connection and per time window (usually per minute). When you hit a rate limit, the response includes a `Retry-After` header indicating when you can retry the request. Implement exponential backoff in your retry logic to avoid immediately hitting the limit again. If you consistently hit rate limits, review your API usage patterns—you may be making unnecessary requests, polling too frequently, or could benefit from webhook-based synchronization. For legitimate high-volume needs, contact us to discuss increasing your rate limits.
Yes, through Makini Flows, which includes connectors for popular databases including Snowflake, PostgreSQL, MySQL, MongoDB, and others. This enables workflows that synchronize data between industrial systems and your data warehouse or analytics platforms. For example, you can sync purchase orders from SAP to Snowflake for analytics, or use database queries to drive integration logic. Database integrations use the same workflow builder as other integrations, making it easy to combine industrial system data with database operations. For direct database-to-database syncing, we can help design optimized workflows. Database connections are treated as custom integrations and may require additional workflow development.
