Hi! I'm Ronnie

I'm a Solutions Architect and a Fullstack Developer.

GitHub / Linkedin

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Established Software Professional

Introduction

A dedicated, agile and passionate, polygot fullstack developer and solutions architect,with 4 years of experience in designing sustainable, cost effective and creative solutions for business.

Gathered indepth knowledge in wide range of technologies working in industrial, commercially scalable as well as niche projects.

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Technical finesse

Well seasoned professional, with experience working in teams as well as in individual capacity.

Experience in programming languages: Python 3.x (Primary), JavaScript ES6+, Node.js (Core, React, Angular and Vue) and Shell scripting with various distributions of Linux/Unix, GNU and Windows OS. Skilled with cloud platforms such as Amazon Web Services and Heroku.

  • Cloud Engineering
  • Fullstack Development
  • Service/Process Automation
  • Application Security

Apart from Designing, Developing and Deploying resilient Software Architecture , others areas of interest includes, Containerization/Dockerization, Data Analytics and Business Intelligence

To view highlights from my GitHub repository

Project Gallery

Here are a few highlights from my GitHub repositories..

Python, Django, Redis, Heroku

From setting up a local development environment and then deploying both staging as well as production environment on Heroku

Implemented storage using Heroku Postgres add-on and New Relic for application performance monitoring.

Implemented a Redis task queue system for handling web requests.



Mozilla and Geckodriver Buildpack, Heroku

buildpack installs Firefox alongwith mozilla/geckodriver the Selenium driver for Firefox) in a Heroku slug. Open Sourced, documents hosted on GitHub.



ElasticSearch, Logstash and Kibana

Using the ELK stack built a solution for monitoring logs within a Big Data ecosystem.

Implemented a trend analyzer using Machine Learning powered with Kibana.

Automated Log Monitoring and Single Metric Anomaly Detector

Using Kibana and the X-Pack machine learning features analyze the input stream of data, model its behavior, and perform analysis based on the detectors you defined in your job. When an event occurs outside of the model, that event is identified as an anomaly.



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