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Case Studies

Discover how we help our clients achieve their goals.

Case study 01

High-Load Telemetry System

Full System Rebuild & Architecture Overhaul

We rebuilt a high-load telemetry platform from the ground up to handle massive traffic, reduce infrastructure costs, and ensure reliable operation at scale.

BeforePrevious System
AfterRebuilt System
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traffic

~10 MB/s

peak load

Incoming Traffic

code

~600 ms

average

API Response Time

Db

~640 USD

per month

Infrastructure Cost

network

Baseline

limited capacity

Throughput

AfterRebuilt System
speed

Up to 60 MB/s

stable under load

up

6×

increase

code

1–100 ms

average (no network delay)

down

~5–6×

faster

db

~96 USD

per month

down

~85%

reduction

network

6× Higher

than previous system

down

6×

increase

darts

Result

A scalable telemetry platform capable of handling 6× higher throughput, up to 60 MB/s traffic, 
while reducing infrastructure costs by over 85% and maintaining 100% uptime during deployments.

ARCHITECTURE CHANGES

code
Full Technology Rebuild
PHP-based platform completely redesigned and rebuilt in C#.
processor
In-Memory Processing
Operational workloads moved from the database into high-performance in-memory structures.
db
Database Role Simplification
Database used only for historical data, analytics, and backups.
branches
Zero-Downtime Deployment Layer
Proxy subsystem introduced to buffer telemetry traffic during service restarts.
recovery
Automatic State Recovery
Application state restored automatically after deployment within 36 seconds.
cloud
Infrastructure Optimization
Architecture redesigned to maximize throughput while reducing infrastructure costs.
darts

Result

A scalable telemetry platform capable of handling 6× higher throughput, up to 60 MB/s traffic, 
while reducing infrastructure costs by over 85% and maintaining 100% uptime during deployments.

Case study 02

High-Load MySQL Optimization

Performance Optimization & Cost Efficiency

We migrated a high-load MySQL database to Amazon Aurora, redesigned the architecture, and optimized the system for performance, scalability, and cost-efficiency.

BeforeMySQL on AWS (RDS)
AfterAmazon Aurora
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traffic

Baseline

Query Performance

(Critical Operations)

clock

20 hours

Migration Time

gears

8 times

Maintenance Window

money

Baseline

Infrastructure Cost

(per month)

AfterAmazon Aurora
speed

5–10× faster

down

5–10×

improvement

clock

1h 40m

down

>12×

faster

gears

2 times

down

75%

reduction

money

~ 1 000 USD lower

down

1k USD

savings

darts

Result

A modern, optimized database solution with faster performance, lower infrastructure costs, and significantly reduced maintenance effort. The system is now scalable, reliable, and ready to grow with the business.

ARCHITECTURE CHANGES & OPTIMIZATIONs

processor
Reduced Resource Usage
Lowered CPU and memory consumption through query tuning and configuration.
search
Query & Index Optimization
Rewrote critical queries, added proper
indexes, and redesigned data access patterns.
scalability
Vertical Scalability
Adjusted instance types and storage strategy for better performance and efficiency.
migration
Efficient Migration Strategy
Developed a custom migration process to minimize downtime and ensure data integrity.
money
Cost Optimization
Reduced AWS monthly costs by 1k USD while improving overall performance.
protection
High Availability Setup
Configured Aurora for multi-AZ high availability to eliminate downtime risks.
darts

Result

A modern, optimized database solution with faster performance, lower infrastructure costs, and significantly reduced maintenance effort. The system is now scalable, reliable, and ready to grow with the business.