Workflow Execution Limits

Subprocess Execution Limit

The subprocess can be executed up to 100,000 times per hour.

If this limit is exceeded, the workflow execution will fail and display the following message:

The hourly execution limit for subprocesses has been reached.

Webhook Request Limit

A Webhook supports up to 10,000 requests per hour.

If this limit is exceeded, the system will display the following message:

Execution limit exceeded.

Slow Query Rate Limiting

When querying data in a workflow, the system tracks slow queries per worksheet on a per-minute basis.

Queries that complete within 1 second are not counted as slow queries. Queries that take longer are counted toward the slow query limit.

Each worksheet allows up to 300 slow queries per minute. Once the limit is reached, subsequent requests are temporarily rejected to prevent continuous consumption of database resources.

Workflows affected by rate limiting automatically retry up to 10 times. If all retry attempts fail, the workflow execution will fail.

While waiting for an automatic retry, the workflow status displays the following message:

Request rate limited. The workflow will retry automatically later.

Optimization Recommendations

If you frequently encounter query timeouts or request rate limits, consider the following optimization strategies:

• Add indexes to frequently queried fields: Create indexes for fields that are commonly used in filter conditions or sorting. This is one of the most effective ways to improve query performance by avoiding full table scans. Keep in mind that more indexes do not necessarily improve performance—only create indexes for fields that are queried frequently. For more information, see Create Indexes.

• Optimize workflow query conditions: For workflow nodes that query records (Get Single Data and Get Multiple Data), configure only the necessary filter conditions and apply record limits whenever possible.

• Avoid high-frequency access to the same worksheet: When processing data through APIs or workflows, execute operations in batches and control the request frequency.

• Reduce complex aggregation and relationship queries: If a query includes a large number of relationship fields, rollup fields, sorting operations, or aggregation calculations, consider narrowing the query scope to improve performance.

• Split large batch operations: For tasks such as data imports, bulk updates, and large-scale queries, process records in smaller batches instead of handling a large volume of data in a single operation.