ERR_WORKDAY_SYNC_TIMEOUT on Workday: Workday integration sync times out — the SOAP or REST API call does not return within the expected window, the integration platform reports a connection timeout, or Workday returns a SOAP_FAULT: The request has timed out error. Root cause: Workday API timeouts occur when a request takes longer than the configured timeout threshold on either the client side (your integration platform) or the Workday side. Workday's SOAP API has a server-side timeout of approximately 5 minutes for synchronous operations. Common causes include: requesting too many records in a single API call without pagination (Workday recommends a maximum of 200 records per page); running large sync operations during Workday's weekly maintenance window (Friday evening to Saturday morning in the tenant's timezone); or the integration making synchronous calls for operations that Workday processes asynchronously. Step 1: Implement pagination for large data requests. Workday's Get_Workers and similar bulk operations support pagination via the Response_Filter element. Set Page and Count to limit results per request. The recommended page size is 200 records. Your integration should loop through pages until the response's Total_Pages value equals the current page number. For a workforce of 5,000 employees, this means 25 API calls of 200 records each rather than one call for all 5,000 — each individual call completes in seconds rather than timing out. Step 2: Avoid sync operations during Workday maintenance windows. Workday performs weekly system maintenance that can cause API degradation or timeouts. The maintenance window is typically Friday 6pm to Saturday 6am in the tenant's primary timezone. Schedule your sync jobs to avoid this window. Additionally, Workday performs daily background processing (payroll calculations, position management) during off-peak hours — if your sync runs during these periods, it may compete for resources and time out. Step 3: Use Workday's asynchronous integration framework for large syncs. For large data extractions (full workforce exports, historical data pulls), use Workday's built-in integration framework instead of direct API calls. In Workday, go to Workday Studio or Integration Cloud and create an EIB (Enterprise Interface Builder) integration or a Core Connector. These run as background processes within Workday, generate a file (CSV, XML, or JSON), and deliver it to your SFTP server or cloud storage. This approach has no timeout constraints and is the recommended pattern for bulk data extraction. Step 4: Switch from synchronous to event-driven integration. If your integration polls Workday for changes on a schedule, consider switching to an event-driven model using Workday's Business Process Framework. Workday can trigger outbound integrations automatically when specific business events occur (e.g., a new hire is completed, a position is changed, a termination is processed). This eliminates large batch syncs entirely and keeps your external system up to date in near-real-time. Step 5: Increase client-side timeout thresholds. Many integration platforms (MuleSoft, Boomi, Workato, custom code) have default HTTP timeout settings of 30–60 seconds, which is too short for large Workday API responses. Increase your client-side timeout to at least 300 seconds (5 minutes) to match Workday's server-side limit. In MuleSoft, set the responseTimeout attribute on the HTTP Request connector. In custom code, set the socket timeout on your HTTP client. Step 6: Monitor Workday API performance with the Integration Activity Report. Workday provides an Integration Activity Report (Workday search: Integration Activity) that shows the execution time and status of all integration runs. Use this report to identify which specific API operations are slow and whether timeouts are consistent or intermittent. Consistent timeouts on the same operation suggest a data volume or query scope issue. Intermittent timeouts suggest resource contention during peak usage periods. Share this report with your Workday administrator to investigate whether tenant-level performance tuning is needed.