The Challenge: Growing Pains at Scale

Questt, a fast-rising star in the EdTech sector, hit a pivotal moment common to successful startups: their user base was growing faster than their infrastructure could handle. With over 2 million students joining the platform, the existing server architecture began to buckle under the pressure.

The engineering team faced two major hurdles. First, traffic was unpredictable; usage would skyrocket during exam hours, overwhelming the servers. Second, the deployment process was manual and fragile. The developers were spending nearly half their week managing operations—patching servers and fixing downtime—instead of building new features. Questt needed a way to scale effortlessly while reducing the operational burden on their team.

The Solution: An AWS-Native, Automated Ecosystem

Doremon Labs stepped in to re-architect Questt’s foundation using a “Cloud-Native” approach. We moved away from manual server management to a fully automated environment powered by Amazon Web Services (AWS).

1. Intelligent Auto-Scaling with AWS We migrated the application to a microservices architecture hosted on Amazon. Instead of running on static servers that hit capacity limits, the system was configured to “breathe.” During peak exam times, the infrastructure automatically spins up additional resources to handle the load. When students log off, it scales back down to save costs. This ensured stability for millions of users without requiring a human operator to flip a switch.

2. Streamlining the Flow with CI/CD To solve the deployment bottleneck, we built a robust Continuous Integration and Continuous Deployment (CI/CD) pipeline. We automated the entire software delivery lifecycle. Now, when a developer commits code, it automatically passes through security checks and testing protocols before being deployed to production. This reduced the release time from hours of manual work to just minutes of automated processing.

3. Implementing “NoOps” through Automation We eliminated manual configuration drift by using automations to manage the infrastructure. By defining the entire environment in code, we made the infrastructure reproducible and self-healing. This shift significantly reduced the need for day-to-day operations, moving the team toward a “NoOps” model where the system manages itself.

The Outcome: Stability Meets Agility

The transformation was a complete success. Questt was able to comfortably support over 2.3 million concurrent users without performance degradation. The automated pipelines transformed their workflow, allowing the engineering team to release updates multiple times a day with confidence.

Most importantly, Doremon Labs liberated Questt’s developers from operational firefighting. With the system handling the heavy lifting of scaling and monitoring, the Questt team shifted their focus back to what matters most: creating an exceptional learning experience for students.