GCP Cloud Run Memory Allocation Issues Causing OutOfMemoryError in Python 3.9 Application
I keep running into I'm stuck trying to I'm having trouble with I've been banging my head against this for hours... I'm experiencing memory allocation issues with my Cloud Run service written in Python 3.9. The service occasionally throws an `OutOfMemoryError`, especially when processing large JSON payloads from an HTTP POST request. My current configuration allocates 1 GB of memory, but this seems insufficient. Here’s a snippet of the code that handles the incoming request and processes the JSON: ```python import json from flask import Flask, request app = Flask(__name__) @app.route('/process', methods=['POST']) def process_data(): data = request.get_json() # Simulating heavy processing result = perform_heavy_computation(data) return json.dumps(result) def perform_heavy_computation(data): # Example of a heavy computation that consumes a lot of memory large_list = [item for item in data['items'] if item['value'] > 10] return {'count': len(large_list)} if __name__ == '__main__': app.run(host='0.0.0.0', port=8080) ``` When I deploy this to Cloud Run, I occasionally see the following error in the logs: ``` ERROR: 2023/10/15 12:34:56 Container failed to start: OutOfMemoryError: Container memory limit exceeded ``` I've tried increasing the memory to 2 GB, but this only slightly mitigated the issue. Additionally, I’ve added logging to track the size of incoming requests, which often exceed 500 KB. Based on Google’s documentation, the maximum memory limit for Cloud Run is 2 GB, and I don’t want to exceed that limit. I’m curious if there are any best practices or patterns to implement streaming or chunking in Python to process large payloads without running into memory constraints. Would using a task queue or breaking down the payload help? Any insights on best practices for optimizing memory usage in this context would be greatly appreciated! For context: I'm using Python on Linux. Is there a better approach? For context: I'm using Python on Linux. Has anyone else encountered this? I'm using Python 3.11 in this project. Am I approaching this the right way? Any pointers in the right direction? Am I missing something obvious?