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Gupshup – Conversational Platform Modernization

Modernized Gupshup's legacy PHP monolith into a scalable multi-tenant SaaS platform, achieving 50% reduction in memory usage, 2× throughput capacity, and 99.9% uptime while enabling enterprise growth.

Project Overview

Modernized Gupshup's legacy PHP monolith into a scalable multi-tenant SaaS platform, achieving 50% reduction in memory usage, 2× throughput capacity, and 99.9% uptime while enabling enterprise growth.

Technologies Used

Node.jsExpress.jsMongoDBRedisBullMQRabbitMQDockerKubernetesJenkinsJestRestAssuredCucumberJMeter

Key Results Achieved

The project delivered exceptional results across multiple metrics, demonstrating the effectiveness of our approach and the value delivered to the client.

50%
Memory Usage Reduction
Optimized caching and data handling reduced infrastructure costs while boosting efficiency
Throughput Capacity
Message node optimizations enabled the platform to handle 1M+ requests/messages at peak load
99.9%
System Uptime
Improved monitoring and Kubernetes resiliency ensured near-continuous availability
50%
Release Cycles
Faster automated CI/CD pipelines accelerated feature rollouts and reduced human error
Enhanced
Client Satisfaction
Faster issue resolution and smoother enterprise onboarding improved customer experience
Multi-Tenant
Platform Scalability
Transformed from single-tenant to multi-tenant SaaS architecture supporting enterprise growth

Challenges Faced

Every successful project comes with its unique set of challenges. Here are the key obstacles we identified and overcame during this project.

1.Legacy Monolithic Codebase: Backend built on PHP monolith lacking modularity, making updates slow and complex
2.Performance Bottlenecks at Scale: Message processing slowed significantly as usage grew, with high memory consumption creating costly inefficiencies
3.Single-Tenant Architecture: System could only serve one tenant per instance, limiting enterprise growth and requiring multi-tenant SaaS model
4.Limited Testing & Observability: Manual QA slowed releases and left bugs undetected, with no centralized monitoring to track errors or performance
5.Deployment Delays: Manual deployment processes risked downtime and lack of automation slowed feature delivery to customers

Solutions Implemented

Our team developed innovative solutions to address each challenge, ensuring the project's success and exceeding client expectations.

1.Backend Migration to Node.js: Rebuilt backend services using Node.js + Express, transitioning from PHP monolith to modern microservices with MongoDB integration
2.Multi-Tenant SaaS Enablement: Redesigned architecture to serve multiple organizations within one platform with tenant isolation for secure data separation
3.Advanced Job Scheduling & Queues: Introduced BullMQ (Redis) and RabbitMQ for background processing with robust scheduling system for message delivery
4.System Optimization with Redis: Integrated Redis caching to cut memory usage by 50% and reduced database load by caching frequently accessed data
5.Testing & Quality Automation: Built automated test suites using Jest, Cucumber, and RestAssured integrated into CI/CD pipelines for regression prevention
6.Containerization & DevOps Automation: Dockerized all services and deployed microservices on Kubernetes cluster with Jenkins CI/CD pipelines for seamless deployments

Project Impact & Success Metrics

The project's success is measured not just by technical achievements, but by the real-world impact it created for our client and their users.

Key Achievements:

  • 50% - Optimized caching and data handling reduced infrastructure costs while boosting efficiency
  • - Message node optimizations enabled the platform to handle 1M+ requests/messages at peak load
  • 99.9% - Improved monitoring and Kubernetes resiliency ensured near-continuous availability
  • 50% - Faster automated CI/CD pipelines accelerated feature rollouts and reduced human error

Conclusion

Through this collaboration, Legresca successfully transformed Gupshup's legacy system into a modern, scalable, multi-tenant SaaS platform. By optimizing system performance, automating deployments, and enabling enterprise-ready architecture, we positioned Gupshup to support millions of global conversations reliably and efficiently. This case study highlights Legresca's expertise in platform modernization, SaaS architecture design, and performance optimization—helping clients unlock the full potential of their digital products.

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Frequently Asked Questions

Got questions? We've got answers. Find quick solutions to common queries below.

Gupshup is a global leader in conversational messaging solutions, enabling over 50,000+ businesses to interact with customers through engaging chat experiences. As the company scaled globally, their existing PHP backend infrastructure showed limitations in performance, scalability, and maintainability, requiring a major modernization initiative.

The main challenges included a legacy PHP monolithic codebase lacking modularity, performance bottlenecks at scale with high memory consumption, single-tenant architecture limiting enterprise growth, limited testing and observability slowing releases, and manual deployment processes risking downtime.

We rebuilt backend services using Node.js + Express, transitioning from PHP monolith to modern microservices architecture. We integrated MongoDB for scalable document-oriented storage and redesigned the system for multi-tenant SaaS enablement with secure tenant isolation.

Gupshup achieved 50% reduction in memory usage through optimized caching, 2× throughput capacity enabling 1M+ requests/messages at peak load, 99.9% uptime through improved monitoring and Kubernetes resiliency, and 50% faster release cycles through automated CI/CD pipelines.

The multi-tenant architecture transformed Gupshup from a single-tenant system to a scalable SaaS platform that can serve multiple organizations within one instance. This enabled enterprise growth, streamlined client onboarding, and provided secure data separation while reducing infrastructure costs.

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Gupshup – Conversational Platform Modernization | Legresca Case Study