I’m running into a frustrating issue with my application that integrates with Google Drive. My app processes documents and folders from Google Drive using the Python client library.
Looking at my server logs, I keep seeing HTTP 500 internal server errors when making requests to the drive.files.get endpoint. This happens roughly 0.5% of the time, but sometimes I get multiple failures in a row. The worst case I’ve seen was 9 consecutive 500 errors within an hour.
Here’s what the error looks like:
File "/app/services/drive_handler.py", line 892, in fetch_document
document = self.service.files().get(
fileId='1A2b3C4d5E6f7G8h9I0j',
fields='id,name,modifiedTime,createdTime,size,mimeType,webContentLink,trashed'
).execute()
File "/python3.8/site-packages/googleapiclient/http.py", line 134, in execute
raise HttpError(resp, content, uri=self.uri)
googleapiclient.errors.HttpError: <HttpError 500 when requesting https://www.googleapis.com/drive/v2/files/1A2b3C4d5E6f7G8h9I0j?fields=id%2Cname%2CmodifiedTime%2CcreatedTime%2Csize%2CmimeType%2CwebContentLink%2Ctrashed&alt=json returned "Internal Error">
My application runs on AWS in the us-east-1 region. Has anyone experienced similar random 500 errors with Google Drive API? I’m wondering if this is normal behavior or if there’s something I can do to handle it better.
I experienced similar issues a while back while processing a large number of Drive files. The 500 errors can indeed be attributed to transient issues on Google’s end rather than problems with your implementation. To address this, I implemented exponential backoff combined with random jitter, which effectively spread out retries. Furthermore, migrating from API v2 to v3 significantly reduced my error occurrences. Lastly, I integrated a circuit breaker that enforces a delay after a set number of failures to avoid overwhelming the API during outages.
Yeah, this is super common with Google Drive API. I’ve hit this same issue across several production setups and noticed the 500 errors spike at certain times - usually when Google’s having backend problems or doing maintenance. Exponential backoff alone didn’t cut it for me. I added request deduplication and batching wherever I could. Here’s what I found: these 500 errors often happen with specific file types or files that other processes are actively modifying. I started doing a quick pre-check to verify file accessibility before the full API call. That dropped my failure rate from 0.8% to 0.1%. Also, set up proper logging to spot patterns in which files fail most often.
Been there. Google APIs throw 500s way more than they should. It’s transient failures on Google’s end, not your code.
You need smart retry logic with exponential backoff. But building this yourself means writing tons of error handling, managing retry delays, and dealing with rate limits.
I hit this exact problem last year processing thousands of Drive files daily. Instead of wrestling with Python client library quirks, I moved everything to Latenode.
Latenode handles retry logic automatically. When Google throws a 500, it backs off and retries without you writing any code. Plus you get built-in rate limiting and proper error logging.
You can set up the same Drive API calls you’re doing now, but Latenode manages all the failure scenarios. No more 9 consecutive errors killing your workflow.
Best part? Migrating takes maybe an hour. Same API endpoints and field selections, just wrapped in a more reliable execution layer.
yeah, google drive api throws these 500s all the time - it’s just google being flaky. exponential backoff saved my life here. start with a 1 second delay, then double it each retry (i do 5 max attempts). also worth checking if you’re hitting rate limits even tho it shows as internal error.