Based on the error you're encountering and my research, this is definitely a case of hitting size limits with task results being too large. The '413 Request Entity Too Large' error occurs when trying to send data that exceeds the maximum allowed request size to Prefect Cloud. Here are a few recommended approaches to resolve this: 1. Use External Storage - Instead of passing large data directly between tasks, store the data in external storage (like S3, GCS, or local filesystem) - Pass references (paths/URLs) between tasks instead of the actual data - Example pattern:

python
   @task
   def process_data(data):
       # Process the data
       result = do_processing(data)
       # Save to external storage
       path = save_to_storage(result)
       # Return the path instead of the data
       return path

   @task
   def next_step(result_path):
       # Load data from storage when needed
       data = load_from_storage(result_path)
       # Continue processing

2. Process Data in Chunks - Break down large datasets into smaller chunks - Use task mapping to process chunks in parallel - Aggregate results at the end if needed 3. Configure Result Storage - Set up a result storage block (like S3ResultStorage) to handle large results - This moves result handling out of Prefect Cloud and into your chosen storage Here's a refactored example:

python
from prefect import flow, task
from prefect.artifacts import create_markdown_artifact

@task
def process_chunk(chunk_data):
    # Process smaller chunk of data
    result = do_processing(chunk_data)
    # Save to temp storage and return reference
    return save_to_temp_storage(result)

@flow
def main_flow():
    # Break data into chunks
    chunks = split_data_into_chunks(your_large_data)
    
    # Process chunks in parallel
    result_paths = process_chunk.map(chunks)
    
    # Create summary without storing full results
    create_markdown_artifact(
        "Processing Summary",
        f"Processed {len(chunks)} chunks of data. Results stored at: {result_paths}"
    )

This approach will help you avoid the 413 error while still maintaining visibility into your workflow's execution. Would you like me to provide more specific examples based on your particular use case or data storage preferences?