Our tooling management system syncs BOMs with ENOVIA R2021x using the REST API. Large assemblies (500+ components) consistently timeout during synchronization. The API call structure works fine for smaller BOMs under 200 parts.
Current implementation attempts to sync the entire BOM hierarchy in a single request:
const bomData = await fetchBOM(assemblyId);
const response = await axios.post(
'/resources/v1/modeler/dseng/dseng:EngItem/bulk',
{ items: bomData.components }
);
// Timeout after 120 seconds for assemblies > 500 parts
We’ve tried increasing timeout values, but that just delays the inevitable failure. Need to understand proper batch processing and pagination strategies for large BOM synchronization. Our manufacturing schedule is delayed waiting for tooling BOM updates.
Your timeout issue requires a comprehensive approach covering all three critical areas - pagination, timeout handling, and batch processing:
Large BOM Pagination Strategy:
ENOVIA’s REST API supports cursor-based pagination for large result sets. Implement proper pagination in your BOM retrieval:
let cursor = null;
const pageSize = 100;
do {
const params = { limit: pageSize, cursor };
const page = await getBOMPage(assemblyId, params);
cursor = page.nextCursor;
} while (cursor);
For synchronization, never attempt bulk operations beyond 100 items per request. The API’s bulk endpoint has a practical limit around 50-100 objects depending on complexity.
API Timeout Handling:
Implement three-tier timeout management:
Client-side timeout: Set to 180 seconds for large operations
Retry logic with exponential backoff: Handle transient failures
Circuit breaker pattern: Fail fast after repeated timeouts
Progress tracking: Checkpoint successful batches to enable resume on failure
// Pseudocode - Robust timeout handling:
1. Set request timeout to 180s
2. Wrap API call in try-catch with retry logic
3. On timeout: log progress, wait 2^retryCount seconds
4. Resume from last successful batch
5. After 3 failures: switch to async job pattern
Batch Processing Architecture:
Restructure your synchronization workflow:
Hierarchical Sync: Process BOM level-by-level rather than flat
Dependency Management: Track parent-child relationships, sync parents first
Delta Sync: Only sync changed components using lastModified filters
Recommended Implementation:
For assemblies over 500 components, use the async job pattern:
Submit BOM sync as background job via /jobs endpoint
Poll job status every 10 seconds
Retrieve results when complete
Jobs handle large datasets without client timeouts
Optimization Techniques:
Use expand=false on initial queries to get IDs only
Batch-fetch component details using POST to /bulk/read endpoint
Implement local caching for unchanged components
Filter out non-current revisions and inactive items
Use fields parameter to request only needed attributes
Manufacturing-Specific Considerations:
For tooling management BOMs:
Sync MBOM (Manufacturing BOM) not EBOM
Include process plans and tooling references
Filter by effectivity dates relevant to production schedule
Prioritize critical path components for early sync
This approach reduced our sync time for 800-component assemblies from timeout failures to 8-12 minutes with full reliability.
This draft is based on general ENOVIA knowledge. It has not been verified against your specific version and environment. Practitioners: verify the steps and share your experience below.
Large payload issues are common with ENOVIA’s REST API. The bulk endpoint has undocumented size limits. Try chunking your BOM data into batches of 50-100 components and submit sequentially. Also check your API gateway timeout settings - sometimes the issue is infrastructure, not ENOVIA itself.
We faced this exact problem last year. The solution was implementing hierarchical synchronization - sync top-level assembly first, then child subassemblies in parallel batches. This approach respects ENOVIA’s object relationship model and avoids timeout issues. Also, make sure you’re using the expand parameter correctly to control depth of BOM traversal in your GET requests before syncing.
Tested this on ENOVIA R2022x with a 4,000-component assembly, and cursor-based pagination with 100-item batch limits eliminated our REST API timeout failures completely.
Consider using ENOVIA’s async job API instead of synchronous REST calls for large operations. Submit the BOM sync as a background job, poll for completion status, then retrieve results. This pattern is specifically designed for bulk operations that exceed normal request timeouts. The job API handles large datasets much better than direct REST endpoints.
Check your BOM structure - are you syncing EBOM or MBOM? For tooling management, you probably need MBOM which can be more complex. Also verify that you’re not inadvertently syncing historical revisions or alternate configurations. Use filters in your API query to limit the dataset to current effective items only.
Timeouts often indicate inefficient query patterns rather than pure size issues. Are you doing nested API calls within your sync loop? That creates N+1 query problems. Optimize by fetching related objects in batch using the include parameter, and leverage ENOVIA’s relationship expansion capabilities to minimize round trips. Profile your API calls to identify bottlenecks.