On a sunny Tuesday morning, everything seemed fine at Writesonic. AI content was flowing, users were smiling, and developers were sipping their well-deserved coffee. But then—boom! Batch generations started failing. People saw mysterious errors that read: “API 502 Bad Gateway”. Uh-oh!
TLDR:
Writesonic’s API started throwing 502 errors during large batch content generation. This caused serious slowdowns and failed requests. The engineering team implemented a smart retry queue system to fix the mess and keep content flowing. In the end, they restored throughput and resilience without losing their cool.
But wait… what is a 502 Bad Gateway?
Let’s break it down. A 502 Bad Gateway error means that one server got a bad response from another server. It’s like asking your friend to get pizza, and they return with… a rock. Something definitely broke in the chain.
In Writesonic’s case, the interface that manages API calls was expecting great results from the AI engine server. But sometimes, the engine was overwhelmed or rebooting, and it sent back an error instead of data. That’s how batch generations started showing those scary 502s.
Why did this happen during batch generation?
Batch generation is when a lot of content tasks are grouped together and generated at once. This is super helpful for businesses or anyone needing tons of content quickly. But this also means more stress on the servers.
Imagine trying to make 100 pancakes on one frying pan—fast. Things get messy, and some pancakes (or content) might just fall on the floor (or trigger errors).
During this hiccup, Writesonic’s system queued lots of tasks for the AI engine. But the engine couldn’t handle them all. It slowed down, gasped for air… and dropped a bunch of 502 errors like hot potatoes.
How bad did it get?
- Almost 40% of batch jobs failed at peak error time
- Average response time tripled
- User success rate dropped by over 25%
- Customer support tickets surged within hours
Things were not looking good. Users were annoyed. Tasks were piling up. The dev team canceled lunch. And something had to be done—fast.
Enter: The Retry Queue System
Instead of stressing out, the team got smart. They built a new retry queue system. It’s a bit like having a second chance basket. If something fails the first time, it doesn’t just disappear—it gets another try!
Here’s how it worked:
- Requests that hit a 502 error were not discarded.
- They were moved into a special retry queue.
- A delay timer was added before retrying to avoid flooding.
- Tasks were retried up to 3 times with increasing delay.
- If everything still failed, it was logged and flagged for manual review.
Thanks to smart timing and retry logic, this reduced failure rates by over 90%. Throughput came back to normal levels, almost like magic. But it wasn’t magic—it was just good engineering!
Making it simple with exponential backoff
The secret sauce was something called *exponential backoff*. It’s like how you try to reconnect Wi-Fi: wait a bit, then try again. If that doesn’t work, wait longer, and try again once more.
Instead of retrying instantly—making the bottleneck worse—the system spaced out requests. Like this:
- First retry: wait 1 second
- Second retry: wait 2 seconds
- Third retry: wait 4 seconds
This gave the backend time to breathe and recover. And it worked like a charm!
How did the retry queue change performance?
Before the retry system, users had to manually resend failed tasks. That wasted time and often caused duplicates. After the fix?
- Automatic retries fixed most failed tasks silently
- Success rate rebounded to almost 98%
- Batch jobs completed without human effort
- Customer complaints dropped significantly
The team also added smarter logging, so they could track which retries succeeded, which failed after 3 tries, and why.
Bonus: Prioritization and batching upgrade
While they were at it, the team made the queuing even better.
They added priority levels. High-priority tasks—like paid plans—were pushed to the front of the retry line. Everyone else still got served, just a bit slower.
They also adjusted the batch handler to break big jobs into smaller mini-batches. Instead of sending 100 tasks at once, it sent 10 sets of 10. That helped balance the load.
Lessons learned (and fun analogies!)
- Don’t flood the kitchen: Too many pancake orders at once will overwhelm the chef. Space them out!
- Give second chances: Sometimes, a failed attempt just needs a breather and another go.
- Slow is smooth, smooth is fast: With exponential backoff, retries don’t cause chaos.
- Track your stuff: Logs and dashboards helped them fix what wasn’t obvious.
What’s next for Writesonic?
Now that the retry queue saved the day, the Writesonic team is going a step further. They’re building smarter load prediction models. These will detect high-load periods and allocate resources in advance—like beefing up the kitchen before a breakfast rush.
They’re also thinking of letting users see retries in real-time. That way, customers can feel confident their tasks are being managed, even after a hiccup.
Final thoughts
The 502 Bad Gateway errors were frustrating for everyone. But with clever thinking, something better came out of it. The retry queue didn’t just fix a problem—it made the system more resilient, more efficient, and even more user-friendly.
At the end of the day, Writesonic didn’t just bounce back. It bounced forward.
So remember:
When your next big batch task runs smooth as butter, thank the retry queue—quietly working behind the scenes, saving the day like a superhero in slippers.
Now go enjoy that coffee. The system’s got your back.