I doubled my API Gateway… and my system crashed twice as fast. 🚨
Sounds impossible? That’s exactly what I thought too.
Within minutes of deploying the “fix”:
• Error rates spiked 📈
• Latency went through the roof
• Downstream services started failing one by one
And the worst part?
👉 The architecture looked more scalable on paper.
**👉 Read the full breakdown here: **https://medium.com/@pramod.er90/i-added-a-second-api-gateway-and-my-system-still-failed-heres-the-real-fix-936d60676473
Here’s the uncomfortable truth:
Most scaling decisions are based on assumptions, not actual bottlenecks.
I assumed the API Gateway was the problem.
So I scaled it.
But all I really did was:
→ Push more traffic into an already struggling system
→ Exhaust database connections faster
→ Overwhelm internal services even harder
I didn’t remove the bottleneck… I weaponized it.
That failure forced me to rethink everything I knew about scaling distributed systems.
In this post, I break down:
• Why adding another gateway made things worse
• The hidden bottlenecks I completely missed
• The exact fixes that actually stabilized the system
• How to avoid this trap in your own architecture
If you’re building systems that need to handle real traffic, this lesson hits hard.
Top comments (1)
Have you ever “fixed” the wrong bottleneck and made things worse?