




SAP Extended Warehouse Management (EWM) is a robust warehouse-logistics solution that supports complex warehouse operations, high-volume distribution, real-time tracking and multi-warehouse environments.
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Integration timelines vary by complexity. For standard implementations with no customizations, connections can be live within 1-2 weeks. This includes authentication setup and basic workflow configuration. For implementations requiring custom workflows or specific business logic, timelines typically range from 2-6 weeks depending on the scope. Complex enterprise deployments with multiple systems and custom requirements may take 6-10 weeks. These timelines are significantly shorter than traditional integration projects, which often take 2-24 months.
API tokens must be stored securely and should never be exposed on the client side or in public repositories. Store tokens in secure environment variables or dedicated secrets management systems like AWS Secrets Manager, HashiCorp Vault, or Azure Key Vault. Never hardcode tokens in application code or commit them to version control. Implement proper access controls so only authorized services can access stored tokens. For production environments, use separate tokens from development/testing environments. Rotate tokens periodically and immediately revoke tokens if you suspect they've been compromised. Makini tokens provide access to customer data, so treat them with the same security standards you'd apply to database credentials.
For bulk operations, we recommend batch processing with appropriate rate limiting and error handling. Makini Flows provides built-in batch processing capabilities with configurable batch sizes, delays between batches, and error handling. For API-based bulk operations, implement pagination when retrieving large datasets—our API returns results in pages with continuation tokens for fetching subsequent pages. When writing large volumes of data, break operations into smaller batches (typically 50-100 records per batch) with delays between batches to avoid overwhelming the target system. Implement comprehensive error logging to identify which specific records fail in a batch. For very large operations (thousands of records), consider asynchronous processing patterns where you queue operations and process them in the background.
When a system becomes unavailable, Makini detects the connectivity failure and marks the connection status accordingly. Scheduled syncs will fail with connectivity errors. API requests to the connection will return error responses indicating the system is unreachable. Makini continues attempting scheduled syncs using exponential backoff—initial retries happen frequently, then progressively less often to avoid overwhelming the system when it comes back online. Webhooks notify you of the connection status change. When the system comes back online, normal operations resume automatically. For temporary outages, no action is required. For extended outages, you may want to notify the customer. Connection credits remain consumed during outages since the connection configuration persists.
