Mobile App Performance
Reduced load times from 15s to 4-6s, enhancing user experience.
Technologies used
D3
Oracle
WSO2
Java
Motivation
The client faced slow mobile app load times (≈15 seconds) due to a heavily loaded monolithic backend. Their goal was to improve performance, stability, and scalability. Azati’s mission was to split the monolith into microservices, optimize SQL queries, and redesign the architecture for smoother, faster user interactions.
Main challenges
Challenge 01
Infrastructure Decision
The client needed a secure, compliant, and fast cloud architecture. Azati evaluated third-party cloud options versus self-managed solutions, ultimately recommending an independent microservice setup to meet legislation and performance requirements.
#1
Challenge 02
Transition to Microservices
Breaking a large monolithic service into microservices required careful planning, approvals from stakeholders, and precise orchestration. Azati proposed splitting the service into independent blocks, ensuring isolated failures didn’t affect the entire system.
#2
Challenge 03
Unoptimized SQL Requests
The monolith performed multiple small SQL queries instead of optimized complex queries, causing slow responses and extra resource usage. Azati refactored these queries and reduced post-processing to improve system throughput.
#3
Our approach
Architecture Analysis
Analyzed the existing monolithic system, identified bottlenecks in backend processing, data bus, and SQL queries, and proposed splitting into microservices.
Microservice Transition & MVP
Developed MVP of the redesigned architecture, stress-tested microservices, validated load distribution, and ensured fault isolation.
Performance Optimization
Optimized SQL queries, moved operation history to a separate screen, and improved mobile app loading times.
Documentation & Future Integration
Prepared full technical documentation, UML diagrams, and recommendations for integrating microservices with Spring Cloud for future development.
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01
Microservices Architecture
The monolithic backend was split into multiple independent microservices, each responsible for a specific function. This design improved scalability, allowed parallel processing, and localized failures, so that problems in one service do not affect the others.
Key capabilities:
- Independent scaling of services
- Fault isolation to prevent cascading failures
- Easier maintenance and upgrades without downtime
02
Cloud-based Infrastructure
The new architecture utilized cloud-hosted microservices to optimize resource allocation and improve load distribution. The setup also enabled flexible scaling during peak times and minimized single points of failure in the backend system.
Key capabilities:
- Efficient resource allocation
- High availability and uptime
- Legislation and compliance adherence
03
Optimized SQL and Data Handling
SQL queries and data processing were optimized to eliminate unnecessary requests and reduce post-processing time. This resulted in faster responses from the backend, improved mobile app load times, and more efficient utilization of server resources.
Key capabilities:
- Faster data retrieval and processing
- Reduced database load
- Improved response time for mobile and web apps
04
Separate Operation History
The operations history feature was moved to a dedicated screen in the mobile app, which allowed the main interface to load faster. Users could access their full transaction history without affecting the performance of other functionalities.
Key capabilities:
- Reduced mobile app loading times
- Better user interface responsiveness
- Improved overall UX
Results & business impact
System Stability
Microservices isolated failures, preventing entire system downtime.
Scalability
New architecture allows horizontal scaling of services under peak load.
Operational Efficiency
Optimized SQL and data handling improved backend throughput by 40-60%.
Future-ready Architecture
Full documentation and Spring Cloud readiness enable further platform development.
