Faster Page Loads
Initial page load dropped from 18 seconds to under 3 seconds, enhancing user experience and reducing frustration.
Technologies used
Angular
JQuery
Ruby
PostgreSQL
Heroku
Amazon Cloud Front
Heroku CI
Motivation
The staffing agency faced a decline in user base due to slow load times, unstable performance, and poor application architecture. Azati’s goal was to audit the platform, identify bottlenecks, improve back-end and front-end efficiency, and implement a roadmap for future improvements, ensuring scalability, stability, and better user experience.
Main challenges
Challenge 01
Bad Application Architecture
The initial solution lacked proper structure, relying on a mix of separate functions created with various paradigms. This caused unstable core features and made it difficult to scale the application or safely introduce new functionalities. Azati conducted a full architectural audit and proposed a modular, maintainable structure to stabilize core functionality and enable long-term scalability.
#1
Challenge 02
Outdated Technology Stack
The back-end was built with Ruby on Rails and the front-end used Angular.js (Angular 1), resulting in extremely slow page loads, up to 18 seconds initially, and poor responsiveness. Azati suggested optimizing the existing stack by refactoring code, removing outdated patterns, and enhancing front-end performance through pagination, caching, and optimized scripts, dramatically reducing load times.
#2
Challenge 03
Lack of Automated Tests
The absence of unit and functional tests made adding new features risky, as updates could break existing functionality. Azati implemented automated test coverage for critical application logic, allowing safer feature releases, reducing regression risks, and increasing overall reliability of the platform.
#3
Challenge 04
Overreliance on Premade Packages
The previous team used too many Ruby Gems for simple tasks, leading to high memory consumption, low performance, and inefficient data workflows. Azati proposed removing unnecessary packages, simplifying code workflows, and optimizing SQL queries and data processing, which improved back-end performance and reduced memory usage.
#4
Our approach
Audit and Prioritization
Conducted a detailed audit to identify the most critical performance and architecture issues, creating a clear roadmap for improvements.
Back-End Refactoring
Simplified the codebase, removed redundant patterns and packages, optimized workflows, and reduced memory consumption to improve performance and stability.
SQL Optimization
Refactored long SQL chains into efficient queries, reducing database calls and accelerating data retrieval.
Front-End Performance Improvements
Implemented pagination, asset caching, and optimized JS scripts to reduce initial load times and accelerate user interactions.
Multilingual Support
Introduced i18n localization for French and German users, extending platform accessibility to international teams.
Automated QA
Created automated unit and functional tests covering critical features to minimize regression risks and ensure reliability.
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Inquire for more infoSolution
01
Scalable Architecture
A redesigned application architecture that ensures reliability, long-term scalability, and optimal performance under load. Supports efficient modular expansion for future feature additions.
Key capabilities:
- Stable and maintainable architecture
- Supports high concurrency
- Facilitates modular development
- Improves overall system reliability
02
Localization Support
Implementation of multilingual capabilities using i18n, enabling users from multiple countries to access the platform seamlessly in their native languages.
Key capabilities:
- Multilingual interface for global teams
- Easy translation management
- Supports users in France and Germany
- Enhances accessibility and adoption
03
SQL and Memory Optimization
Refactored database workflows and optimized memory usage to improve application efficiency, reduce server load, and speed up data retrieval processes.
Key capabilities:
- Optimized SQL queries for faster data extraction
- Reduced RAM consumption by 20%
- Improved backend processing speed
- Minimized server downtime and performance bottlenecks
04
Enhanced Front-End Performance
Optimized the front-end by reducing page load times, implementing pagination, and caching assets to improve the user experience across all devices.
Key capabilities:
- Reduced initial page load to under 3 seconds
- Implemented efficient pagination for large datasets
- Advanced asset caching for faster rendering
- Improved responsiveness of user interface
05
Automated Quality Assurance
Introduced automated unit and functional tests covering critical application logic to reduce regression risks and ensure stability during feature updates.
Key capabilities:
- Unit and functional test coverage for main features
- Reduces risk of breaking existing functionality
- Facilitates safer release of new features
- Improves overall software quality and reliability
Results & business impact
Back-End Efficiency
Optimizations led to a 43% increase in back-end performance, supporting more concurrent users and higher workload.
Lower Resource Usage
RAM consumption decreased by 20%, lowering hosting costs and improving stability.
Higher User Satisfaction
Stabilized the platform and stopped the decline in user base, improving engagement and confidence in the system.
