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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.
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.
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.
Yes, Makini supports multi-region deployments for customers requiring data residency in specific regions or needing high availability across geographies. Each region runs an independent instance of Makini with its own infrastructure, ensuring data remains within the specified region. Multi-region deployments are most common for self-hosted installations where customers want instances in multiple AWS regions or data centers. For cloud deployments, we can discuss region-specific hosting based on your requirements. Multi-region support ensures compliance with data localization regulations and provides geographic redundancy for mission-critical integrations.
