JOHN nguembu

Software Architect · M2 Research in Software Engineering · Yaoundé 🇨🇲

🔬 Research Focus

🎯 Conception d'une approche prédictive d'analyse d'impact des changements dans les architectures microservices évolutives

Design of a Predictive Change Impact Analysis Approach for Evolving Microservice Architectures

Master 2 Research — Software Engineering Université de Yaoundé I · Faculté des Sciences Directeur : Pr OLLÉ OLLÉ Daniel Claude Delort

Designing a predictive framework to anticipate the ripple effects of architectural changes in evolving microservice ecosystems — combining static analysis, runtime observability, and machine learning to reduce regression risk and support informed refactoring decisions.

👋 About Me

name:        Jaures NGUEMBU (aka John)
role:        Software Architect & Fullstack Engineer
focus:       Distributed Systems · Microservices · DDD · Event-Driven
research:    M2 — Predictive Change Impact Analysis (PCIA/PCIS)
institution: Université de Yaoundé I — Faculté des Sciences
supervisor:  Pr OLLÉ OLLÉ Daniel Claude Delort
location:    Yaoundé, Cameroon 🇨🇲
philosophy:  Clean code · Automated tests · Observable systems
open_to:     Research collaborations · Open Source · Architecture consulting

I design resilient, observable, and evolvable distributed systems — bridging the gap between academic rigor (Master 2 Research) and industrial-grade delivery.

My current research tackles a fundamental question in modern software engineering:

How can we predict — before deployment — the ripple effects of a change across a microservice ecosystem?

🧰 Tech Stack

🏗️ Architecture & Distributed Systems

🖥️ Backend

🎨 Frontend

🗄️ Databases & Persistence

🧪 Testing & Quality

🔬 Research & Observability

🛠️ Tools

🚀 Featured Project — NJILA

📦 NJILA — Event-Driven Microservices Platform

A distributed booking & fleet management platform designed as a showcase of microservice architecture principles.

Architectural highlights:

✅ Database per Service — true bounded-context decoupling
✅ Asynchronous messaging via RabbitMQ
✅ Horizontal scalability with stateless service instances
✅ Polyglot persistence — PostgreSQL + MongoDB + Redis
✅ Observability-first — tracing, metrics, structured logs
✅ CI/CD pipeline with automated testing (Pytest, Vitest)

📊 GitHub Analytics

🏆 Statistiques principales

🔥 Série de contributions

📈 Graphe d'activité

🏅 Trophées

🏆 Achievements

🐍 Animation Snake

📋 Badges de secours

_Communauté

_{Étoiles reçues}

_{Dernier commit}

_{Chercheur M2}

💡 Astuce : Si un widget ne s'affiche pas, ouvre-le dans un nouvel onglet — les services GitHub mettent parfois 5-10 secondes à générer l'image la première fois.

🔬 Research & Academic Work

🎓 Master 2 Research — Université de Yaoundé I

Thesis topic (FR):

Conception d'une approche prédictive d'analyse d'impact des changements dans les architectures microservices évolutives

Thesis topic (EN):

Design of a Predictive Change Impact Analysis Approach for Evolving Microservice Architectures

Supervisor: Pr OLLÉ OLLÉ Daniel Claude Delort Institution: Faculté des Sciences · Département d'Informatique Center: CRFD-STG (Centre de Recherche et de Formation Doctorale) Academic Year: 2026 – 2027

Research questions:

RQ1 — Which factors are most relevant for impact prediction?
RQ2 — Does evolution history improve accuracy over static dependencies alone?
RQ3 — Under which conditions is the approach most effective?

Hypotheses:

H1 — Dependencies + history > static dependencies alone
H2 — Co-evolution improves detection of indirectly affected components
H3 — Change characteristics improve propagation prediction accuracy

Methodology:

📐 Static analysis of service contracts (OpenAPI, Protobuf)
🔭 Runtime tracing with OpenTelemetry
🤖 Predictive modeling (decision tree, random forest)
🧪 Empirical validation via temporal simulation

📚 Research Interests

🏗️ Distributed Systems & Microservices
🔮 Predictive Software Engineering
🔄 Change Impact Analysis (PCIA)
📡 Eventual Consistency & Saga Patterns
🧭 Domain-Driven Design (DDD)
🔍 Observability & Distributed Tracing
☁️ Cloud-Native Architecture
🧪 Chaos Engineering & Resilience

💡 Current Focus

🔭 Building

NJILA — Microservices showcase platform
PCIA Framework — Change impact prediction tooling
Observability stack — OpenTelemetry + Grafana + Jaeger reference setup

📚 Learning & Researching

Chaos Engineering & resilience patterns
Machine Learning for code/dependency analysis
Production-grade Kubernetes (operators, autoscaling, service mesh)
Writing my Master's thesis on predictive change impact analysis

🤝 Open to Collaborate On

🏗️ Architecture

Microservices &
Distributed Systems

🔬 Research

Academic papers &
Empirical studies

🧪 Quality

Test Automation &
QA Strategy

💻 Open Source

Java · Python ·
TypeScript ecosystems

📫 Let's Connect

💬 Open to research collaborations, architecture consulting, and open-source contributions.

🧠 Beyond the Code

🎧 Lo-fi & jazz fuel my deep-work sessions
📚 Technical books are part of my daily routine
🧪 I treat testing with the same excitement as feature coding
🌍 I believe Open Source is the fastest path to innovation

🏛️ I think in bounded contexts, even in real life
📐 Architecture diagrams are my favorite kind of art
🔍 I love debugging distributed systems — yes, really
✍️ I write research notes to think more clearly

Thanks for stopping by — feel free to explore my work and reach out if you want to build something meaningful together. 🚀