Talex

EdTech Β· APAC Β· Dedicated Team

1.5 million users. Zero tolerance for downtime. One team to build it right.

A Singapore edtech leader had outgrown every architectural decision made at smaller scale. The platform worked - until it wouldn't. What they needed was not engineers who could code, but a team that had built for this kind of load before and knew exactly where systems like this break.

Specialists deployed

15

Duration

11 mo

Engagement model

Dedicated Team

"Scaling to 1.5 million users is the kind of challenge that exposes every shortcut taken earlier in a platform's life. This team did not take shortcuts. They built the architecture right the first time, and it showed when the load actually hit. Eleven months, delivered on time, and the platform has not looked back since."

β€” CTO

When Your Platform Outgrows Your Team Faster Than Your Servers

Serving 1.5 million users on a platform built for a fraction of that is not a performance problem. It is a structural one.

The client's web and mobile applications were running examinations and certifications, high-stakes interactions where downtime is not an inconvenience, it is a failure with real consequences for real students. The platform had to handle peak exam periods where traffic surges are not gradual, they are sudden and unforgiving.

On top of that, the product roadmap was not frozen. New features had to be integrated continuously without disrupting existing services. Every deployment was a calculated risk on a live platform that could not afford to go down.

The team that could solve this had to bring very specific experience. Microservices architecture at scale, cloud infrastructure that auto-scales under real load, native mobile development across iOS and Android, and the engineering discipline to ship new features without touching what was already working.

Believing existing systems can scale indefinitely with minor tweaks.Underestimating the complexity of peak load management.Assuming generic developers can manage specialized, high-stakes environments.

Strategic Staffing for Specialized Needs

Fifteen engineers working in parallel across web, mobile and infrastructure is not a team you assemble through a job posting and three rounds of interviews. By the time that process produces a shortlist, the project window has already shrunk.

The client came to Talex with a specific brief and a tight timeline. Within days they had a vetted shortlist of specialists - four backend engineers, three frontend developers, four mobile developers with native iOS and Android experience, two DevOps engineers, and two QA engineers. Every person interviewed and selected by the client directly. No agency deciding who was good enough on their behalf.

What made that possible is a talent pool built over two decades of software delivery, filtered through a vetting process that goes well beyond technical assessment. Domain relevance, professional track record, communication, and the commitment profile that a high-pressure 11-month engagement actually requires - all assessed before the client saw a single profile.

The team decomposed the system into loosely coupled microservices, enabling parallel development across workstreams without teams blocking each other. AWS infrastructure was built for elasticity from the start β€” EKS for containerized deployments, EC2 Auto Scaling to absorb traffic spikes without manual intervention, S3 for storage, Elasticsearch for fast search at scale. Keycloak SSO handled centralized authentication across all services. Kong API Gateway managed traffic routing.

All fifteen worked embedded inside the client's environment throughout. Talex managed the coordination and people side of the engagement, keeping a 15-person cross-functional team aligned across an 11-month build without the client having to carry that overhead.

4

Backend Developer

Senior

3

Frontend Developer

Mid-Senior

4

Mobile Developer

Mid-Senior

2

DevOps Engineer

Senior

2

QA Engineer

Mid

Predictable Performance Under Unpredictable Loads

The platform absorbed peak examination traffic without downtime β€” not because the team got lucky, but because the infrastructure had been designed for exactly that scenario before a single student logged in.

New features shipped continuously throughout the engagement without disrupting live services. The microservices architecture meant teams deployed independently, which translated directly into faster release cycles with no maintenance windows required.

A traditional outsourcing agency would have handed the client a PM and a process. A freelancer marketplace would have given them profiles to sort through individually, with no guarantee any two people had worked at this scale before. Instead, the client got a team where every person had been assessed against the specific demands of this project before the first interview was scheduled.

100% retention (User Trust)

No trust breaches due to platform failures.

Strengthened (Market Position)

Reputation as a reliable edtech provider solidified.

Reduced by 30% (Operational Cost)

Efficient scaling reduced unnecessary expenditure.

Increased by 40% (Development Velocity)

Parallel development without inter-team dependencies.

High (System Resilience)

Infrastructure designed to handle unexpected load spikes.

Timeline

1

Team Assembly Β· 2 weeks

Rapid assembly and vetting of specialized team.

2

Architecture Design Β· 1 month

Designing a microservices-based architecture for scalability.

3

Development Β· 8 months

Concurrent development across web, mobile, and backend systems.

4

Testing and Optimization Β· 1 month

Rigorous testing under simulated peak loads.

Business Outcomes

  • β†’99.8% : platform uptime maintained through peak examination periods after launch
  • β†’42% : faster release cycles through parallel microservices development across independent teams
  • β†’3x : infrastructure cost efficiency versus fixed server capacity, through AWS auto-scaling

Engineering Excellence

  • β†’Platform Scale : 1.5M users : Microservices architecture sustained concurrent load across web and mobile without performance degradation
  • β†’Deployment : Zero-downtime : Continuous feature integration shipped without disrupting live examination services
  • β†’Mobile : iOS + Android native : Swift and Kotlin delivered full-performance native apps alongside the web platform within the same timeline

Why Talex

Speed of Talent Deployment 14 days

Delivered a full team of specialists within weeks, not months.

Expertise in Scalability

Proven track record in building scalable architectures for large user bases.

Tailored Team Composition

Precisely matched team skills with project requirements for optimal performance.

ELASTICITY: Fixed Capacity RiskSPECIALIZATION: Jack of All Trades RiskSPEED: Time-to-Team Risk

Services

FrontendBackendDevOps