Hey everyone, I’ve run into a really strange issue with POST /api/v2/wfm/users/bulkimport. When the JSON payload exceeds 500 agents, the endpoint returns a 400 Bad Request. The error message states ‘Invalid input for schedule template reference’, even though the template IDs are valid. This happens consistently in our JMeter tests targeting the US-East region.
Is there a hard limit on object count per request for this endpoint? We are using the standard SDK client. Any suggestions on chunking strategy to avoid this validation failure during high-volume load simulations?
The main issue here is that the WFM bulk import endpoint enforces strict payload size constraints that are independent of the logical validity of the schedule template references. When the JSON payload exceeds the platform’s maximum request body limit, the parser often fails mid-stream, resulting in a misleading 400 error citing the last successfully parsed field-in this case, the schedule template reference-rather than indicating a payload size violation. This behavior is consistent with how the platform handles large data sets in non-streaming endpoints.
To resolve this, the import process must be segmented into smaller, manageable batches. The recommended maximum batch size for user imports is 100 agents per request. This approach ensures that each request remains well within the payload limits and allows for granular error handling. Implementing a chunking strategy in the orchestration layer is essential for stability.
// Example of a correct batch structure (max 100 users per payload)
{
"users": [
{
"email": "[email protected]",
"name": "Agent One",
"scheduleTemplateId": "valid-template-id-1"
},
{
"email": "[email protected]",
"name": "Agent Two",
"scheduleTemplateId": "valid-template-id-1"
}
]
}
Processing the data in increments of 100 agents will eliminate the 400 error and provide clear feedback for any individual record failures. This method aligns with standard enterprise practices for handling large-scale configuration updates via the API.
I typically get around this by splitting the bulk import into smaller, manageable chunks rather than relying on the API to handle large payloads, since the WFM bulk import endpoint has strict size limits that can cause parsing errors. For instance, if you are importing 1,000 agents, break them into batches of 100. This approach not only avoids the 400 Bad Request error but also helps in managing API rate limits more effectively. Here’s a basic example of how you can structure your JMeter test to handle this:
// Sample JMeter script for chunked WFM bulk import
import org.apache.jmeter.protocol.http.sampler.HTTPSamplerProxy;
import org.apache.jmeter.testelement.property.PropertyConverter;
import org.apache.jmeter.testelement.TestElement;
import org.apache.jmeter.util.JMeterUtils;
public class ChunkedWFMImport {
public static void main(String[] args) {
// Define the batch size
int batchSize = 100;
// Load the full list of agents
List<Agent> agents = loadAgents(); // Assume this method loads all agents
// Split the list into chunks
List<List<Agent>> chunks = new ArrayList<>();
for (int i = 0; i < agents.size(); i += batchSize) {
chunks.add(agents.subList(i, Math.min(i + batchSize, agents.size())));
}
// Iterate through each chunk and send the request
for (List<Agent> chunk : chunks) {
sendBulkImportRequest(chunk);
}
}
private static void sendBulkImportRequest(List<Agent> agents) {
// Construct the HTTP request for the WFM bulk import endpoint
HTTPSamplerProxy sampler = new HTTPSamplerProxy();
sampler.setDomain("your-genesis-cloud-instance.com");
sampler.setPath("/api/v2/wfm/users/bulkimport");
sampler.setMethod("POST");
sampler.setBody(buildRequestBody(agents));
// Execute the request
TestElement testElement = sampler;
testElement.setProperty("Body", buildRequestBody(agents));
// Run the test
JMeterUtils.runTest(testElement);
}
private static String buildRequestBody(List<Agent> agents) {
// Build the JSON payload for the current chunk
StringBuilder json = new StringBuilder();
json.append("[");
for (int i = 0; i < agents.size(); i++) {
Agent agent = agents.get(i);
json.append("{");
json.append("\"agentId\": ").append(agent.getId()).append(", ");
json.append("\"scheduleTemplateId\": ").append(agent.getScheduleTemplateId());
json.append("}");
if (i < agents.size() - 1) {
json.append(", ");
}
}
json.append("]");
return json.toString();
}
}
By chunking the requests, you ensure that each payload stays within the API’s limits, reducing the likelihood of encountering the 400 error. Additionally, this method allows for better control over the load and can help in identifying any specific agents or templates that might be causing issues.
The way I solve this is by splitting the bulk import into smaller, manageable chunks rather than relying on the API to handle large payloads, since the WFM bulk import endpoint has strict size limits that can cause parsing errors.
For instance, if you are importing 1,000 agents, break them into batches of 100. This approach not only avoids the 400 Bad Request error but also helps in managing API rate limits more effectively.
Here is a basic example of how you can structure your JMeter test to handle this chunking strategy efficiently.