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CATALOGUED PROJECT

SYSTEM / EVIDENCE / SOURCE

Selestino

Recipe recommendation website for personalized Peruvian dish suggestions, backed by Python, PostgreSQL, containerized deployment, and automated testing.

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EVIDENCE LEDGER

Verifiable project claims before narrative.

01
README: architecture, delivery, and testing

Documents recommendation features, PostgreSQL, Docker, Kubernetes, Google Cloud, Jenkins CI/CD, pytest, and Selenium-based browser testing.

CASE STUDY

From problem to working system.

01 / PROBLEM

Turn user input into personalized Peruvian dish recommendations while keeping the application testable and deployable.

02 / APPROACH

Built a Python and PostgreSQL web application and paired it with container orchestration, cloud infrastructure, continuous delivery, and automated testing.

03 / IMPLEMENTATION

The decisions that turned the approach into a working system.

  1. Django recipe service with models, views, serializers, templates, migrations, and supporting application logic.

  2. Docker packaging plus Kubernetes deployment, service, ingress, autoscaling, configuration, and secret manifests.

  3. Jenkins CI/CD workflow with pytest coverage and Selenium-oriented functional testing.

REPOSITORY DOCUMENTATION

README

Full repository documentation is available on demand for deeper technical inspection.

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