Yomna Bouallegue - DevOps Engineer

Overview

EdTech backend engineer (senior) focused on building robust API integrations and data-sync pipelines for an LMS. The strongest proven skill is resilient Moodle integration and mirrored-sync design, evidenced by MoodleApiService.php and the idempotent SyncMoodleCourseData job. Public code does not show large-scale service mesh/cluster orchestration manifests or comprehensive production observability/alerting configuration.

Phone

Timeline

Full-Stack Developer & DevOps Intern · Junior

Edora LMS · Internship

Jul 2026 to Aug 2026 1 Month Tunis In office

Built a Laravel backend and a React/TypeScript SPA that extends Moodle, implementing native Moodle authentication via token-based web services and scheduled synchronization of course data into PostgreSQL. Deployed a multi-service stack on a self-managed k3s Kubernetes cluster in Azure, using Traefik with TLS and multiple public subdomains. Implemented Jenkins CI/CD to deploy to Kubernetes on main branch pushes, and set up Prometheus/Grafana monitoring plus automated database backup jobs. Delivered role-based dashboards for admin, teacher, and student users.

Laravel

PHP

PostgreSQL

Redis

React.js

TypeScript

Docker

Nginx

Chart.js

Kubernetes

Jenkins

Prometheus

Grafana

WebSockets

Traefik

MariaDB

Azure

Full-Stack Developer & DevOps Intern · Junior

Teck Catalyze · Internship

Jul 2025 to Aug 2025 1 Month Tunis In office

Co-developed a sports and nutrition coaching platform for multiple roles (client, coach, nutritionist, admin), covering design through deployment within a 6-week period. Built a React Native mobile application with fitness tracking, personalized programs, BMI/BMR calculation, geolocation features, and a marketplace, along with admin dashboards in React. Deployed the Node.js/Express backend with a REST API and JWT authentication behind Nginx on an Azure VM using Docker.

React Native

React.js

Node JS

Express

Docker

Nginx

Azure

Figma

Postman

ESPRIT

Bachelor's Degree · Cloud Computing

2023 Ariana, Tunisia

Projects

MedAssist IA

Jan 2025 to Jan 2026 1 Year

Built a machine-learning workflow to compare multiple algorithms on several medical datasets for early disease detection tasks. Evaluated models using metrics such as accuracy, precision, recall, F1-score, and AUC to select suitable approaches. Deployed a Flask-based prediction interface intended for physician use.

TFAKADNI

Jan 2025 to Jan 2026 1 Year

Designed and deployed a cloud-native private environment on OpenStack with a 7-node setup, configuring core services for networking, compute, images, volumes, and object storage. Automated provisioning of a Kubernetes cluster (control plane plus worker nodes) using OpenStack orchestration, Helm-ready components, and an Ingress setup. Implemented self-healing monitoring with Prometheus, Grafana, and Alertmanager and contributed to an application layer using Angular, Spring Boot, and MySQL with JWT-based security.

Brush & Bargain

Jan 2024 to Jan 2025 1 Year

Developed a cross-platform mobile application for buying, selling, and exhibiting artworks with features like event listings, reservations, and complaint handling. Implemented the app using Firebase as the backend service and focused on delivering end-to-end user flows for marketplace interactions.

ChronoSerena

Jan 2024 to Jan 2025 1 Year

Created a distributed medical management platform for chronic patients using a desktop JavaFX client and a web Symfony backend. Implemented core data organization patterns and RESTful API communication for patient workflows. Used a MySQL database to persist application data and support the system’s overall MVC structure.

AgroDesk

Jan 2023 to Jan 2024 1 Year

Built a desktop agricultural management application using C++ with an object-oriented design and Qt UI components. Integrated an Arduino module to support automated feed scheduling. Connected the system to a database layer for managing farm operational data.

Technical skills

Languages

11

PHP

Java

C++

SQL

JavaScript

Python

TypeScript

C#

Node JS

Go

C

PHP

4

Symfony

Eloquent

Laravel

Composer

AI/ML

6

NumPy

Pandas

XGBoost

Machine Learning

Scikit-learn

LightGBM

DevOps

16

Azure

Docker

Rest API

AWS

Nginx

Kubernetes

GitHub

Grafana

Git

Ansible

K3s

Prometheus

CI/CD

Helm

Ubuntu

Jenkins

Frontend

3

React.js

Angular

Chart.js

Databases

4

PostgreSQL

MySQL

Redis

MariaDB

Other

19

Flask

Spring Boot

Qt

Express

Firebase

React Native

.NET

Figma

Postman

AI/ML

DevOps

cert-manager

Debian

OpenStack

Traefik

WebSockets

Alertmanager

ingress-nginx

MVC

Senior Backend Developer Confidence: High API Engineer

EdTech backend engineer (senior) focused on building robust API integrations and data-sync pipelines for an LMS. The strongest proven skill is resilient Moodle integration and mirrored-sync design, evidenced by MoodleApiService.php and the idempotent SyncMoodleCourseData job. Public code does not show large-scale service mesh/cluster orchestration manifests or comprehensive production observability/alerting configuration.

API Design

6/10

How well APIs are designed

Clear, consistent REST API patterns with input validation and idempotent behaviours, but no explicit versioning or enterprise-grade API governance visible.

Evidence

yum19/Edora/backend/app/Http/Controllers/Api/CourseActivityController.php: store/update/destroy methods with validation, idempotency and error contract responses yum19/Edora/backend/app/Http/Controllers/Api/ClassChatController.php: message endpoints with validation and idempotent reaction/delete behaviour yum19/Edora/backend/app/Services/MoodleApiService.php: fetch() maps Moodle error payloads to typed exceptions and consistent runtime errors

Data Layer & Database

7/10

Working with databases

Strong relational data layer with an explicit migration history, schema evolution, N+1 guards and several hand-tuned grouped queries and indexes.

Evidence

yum19/Edora/backend/database/migrations/: multiple timestamped migrations including add_performance_indexes and trigram index migration (2026_08_18_120000_add_performance_indexes_to_grades_and_completions.php, 2026_08_18_120100_add_trigram_indexes_for_search.php) yum19/Edora/backend/app/Services/AnalyticsService.php: uses eager loading (with) to avoid N+1 and groups queries for peer averages and reports yum19/Edora/backend/app/Jobs/SyncMoodleCourseData.php: uses updateOrCreate for idempotent upserts and grouped selectRaw for completed counts

Scalability & Performance

7/10

Handling load and speed

Thoughtful scalability choices: response caching with per-token keys, queue-based decoupling for syncs, timeouts on HTTP calls and deliberate batching to avoid O(n) queries.

Evidence

yum19/Edora/backend/app/Services/MoodleApiService.php: Cache::remember per-token cache key and Http::timeout usage yum19/Edora/backend/app/Jobs/SyncMoodleCourseData.php: job queued, $tries and $timeout properties and cache tag flush after sync yum19/Edora/backend/app/Services/AnalyticsService.php: completionReport() reduces query load by grouped counts instead of per-item queries

System Architecture

6/10

Overall system structure

Clear separation of controllers, services and jobs, with deliberate decisions about service-account vs per-user tokens and a mirrored local model for fast reads; not a multi-service distributed architecture though.

Evidence

yum19/Edora/backend/app/Services/MoodleApiService.php: single client encapsulating Moodle HTTP concerns and token resolution yum19/Edora/backend/app/Jobs/SyncMoodleCourseData.php: central scheduled job that populates local mirror tables to decouple runtime reads from the LMS yum19/Edora/backend/app/Http/Controllers/Api/CourseActivityController.php: uses SyncMoodleCourseData::dispatch() to keep student-facing mirror in sync

Security & Auth

7/10

Protecting data and access

Good authentication and boundary hygiene: token lifecycle handling, input validation, file upload restrictions and explicit handling of token-expiry errors; full threat-hardened practices (e.g. refresh/revocation UI flows, dependency audits) are not fully visible.

Evidence

yum19/Edora/backend/app/Services/MoodleApiService.php: token resolution, Crypt::decryptString for session tokens and MoodleTokenExpiredException thrown on specific error codes yum19/Edora/backend/app/Http/Middleware/EnsureMoodleToken.php: presence of middleware (authorization boundary) referenced in bootstrap yum19/Edora/backend/app/Http/Controllers/Api/CourseActivityController.php: request validation rules and file upload size/type limits

Reliability & Observability

6/10

Stability and monitoring

Reliable practices present: job retries/timeouts, exception logging, cleanup on partial failure and logging; explicit backoff strategies, circuit breakers and metrics/alerting are not visible in code.

Evidence

yum19/Edora/backend/app/Jobs/SyncMoodleCourseData.php: public int $tries and public int $timeout, and use of report()/Log::info for observability yum19/Edora/backend/app/Services/MoodleApiService.php: Http::timeout and structured Log::error on Moodle API error payloads yum19/Edora/backend/app/Http/Controllers/Api/CourseActivityController.php: cleanup path that deletes created Moodle activity if later steps fail

Expertise

Microservices & API Architecture· Senior

Messaging & Real-time· Senior

Databases & Vector Storage· Senior

Industries

Education· Senior

Technologies

Go

Java

PHP· since 2026 · Senior

C#

Node JS· since 2025

Rest API

.NET· since 2026

Flask· since 2025

Express· since 2025

Laravel· since 2026

Symfony· since 2024

Spring Boot

Composer

Eloquent

Recommendations

Extend the sync job to support horizontal scaling (partitioning work by course ranges or sharding) and add explicit exponential backoff for transient Moodle failures.
Add end-to-end production observability: instrument key paths with metrics, latency histograms, SLOs and alert rules, and export traces for the sync and API calls.
Implement a robust token refresh/revocation lifecycle and a transparent admin endpoint to inspect token health and recent failures.
Harden long-running external interactions with circuit-breaker patterns, and add backoff-configurable retries for critical Http calls in MoodleApiService.

Repositories

The developer's experience in this domain has been verified based on AI analysis of the following repositories:

yum19 Edora Angular

Intern AI/ML Engineer Confidence: Low Generalist

A cloud-focused generalist at an entry level with strengths in cloud deployments and DevOps practices. The strongest proven area is cloud and DevOps tooling as evidenced by repository text mentioning production Kubernetes deployments, private OpenStack clouds and Azure-hosted mobile deployments. There is no human-authored code or ML artifacts available to evaluate model engineering, data pipelines, experiments or deployment implementations.

Model Architecture & Training

How well models are designed and trained

Not evidenced in public code

Data Pipeline & Feature Engineering

How data is prepared for models

Not evidenced in public code

Experimentation & Evaluation

How results are measured and tested

Not evidenced in public code

MLOps & Deployment

How models are shipped to production

Not evidenced in public code

Computational Efficiency

How efficiently computing resources are used

Not evidenced in public code

Research Depth & Innovation

Depth of research and new ideas

Not evidenced in public code

Expertise

Medical AI & Healthcare· Intern

Industries

Education· Junior

Health Care· Intern

Software· Intern

Technologies

AI/ML

DevOps

Python· since 2026 · Junior

SQL

C++

MySQL

PostgreSQL· since 2026

Redis· since 2026

Ansible

Helm

XGBoost· since 2025

Traefik· since 2026

cert-manager

Debian

K3s

Prometheus· since 2026

WebSockets· since 2026

Scikit-learn· since 2026

LightGBM

Azure· since 2025

CI/CD

Jenkins· since 2026

Pandas· since 2025

NumPy· since 2025

Git

MariaDB· since 2026

AWS

Docker· since 2025

Kubernetes· since 2026

Ubuntu

Nginx· since 2025

Grafana· since 2026

Qt

ingress-nginx

OpenStack· since 2026

Alertmanager

GitHub

Machine Learning· since 2025

Recommendations

Develop production-grade Kubernetes deployments, CI/CD pipelines and IaC for cloud-native services.
Build small end-to-end prototypes that include human-authored infra-as-code, deployment manifests and monitoring to demonstrate ownership.
Contribute human-authored MLOps or ML prototype code (data ingestion, training loop, evaluation scripts) to show model engineering capability.

Repositories

The developer's experience in this domain has been verified based on AI analysis of the following repositories:

yum19

Intern Data Scientist Confidence: Low Generalist

Cloud computing engineering student with early practical experience, focused on cloud infrastructure and deployments; the main strength is cloud and deployment work evidenced in the repository README (yum19/yum19/README.md). The strongest proven skill is cloud deployment and infrastructure experience as described in yum19/yum19/README.md. There is no human-authored code, data pipelines, notebooks, tests or production code available here to evaluate engineering depth, data science practice or system design.

Statistical Rigor

Correct use of statistics

Not evidenced in public code

Data Wrangling & Cleaning

Preparing and cleaning data

Not evidenced in public code

Exploratory Analysis & Visualization

Exploring and visualizing data

Not evidenced in public code

Predictive Modeling

Building models that predict

Not evidenced in public code

Business Insight & Impact

Turning analysis into business value

Not evidenced in public code

Reproducibility & Notebook Hygiene

Clean, repeatable analysis

Not evidenced in public code

Industries

Education· Junior

Artificial Intelligence· Intern

Health Care· Intern

Recommendations

Develop small, well-tested ETL pipelines that include unit tests and train/test separation to build demonstrable data-engineering experience.
Implement a reproducible notebook-to-module workflow with pinned environment files and a simple CI pipeline to demonstrate reproducibility and engineering hygiene.
Build and document a cloud-deployed microservice (containerized, IaC, CI/CD) that integrates a simple data ingestion and monitoring pipeline to show end-to-end ownership.
Create one focused data-science notebook that includes hypothesis framing, assumption checks and honest write-up of negative results to show analytical judgment.

Repositories

The developer's experience in this domain has been verified based on AI analysis of the following repositories:

yum19

Job preferences

Work permits: Tunisia