Ankit Sinha

Weather Provider Service

I spearheaded the development of a cutting-edge Weather Provider Service aimed at delivering accurate and real-time weather information to users. Leveraging Next.js, MySQL, Docker, and Kubernetes in Azure, this service revolutionised weather forecasting by intelligently selecting the most reliable weather data provider based on geographical coordinates and machine learning algorithms.

Tech Stack :
Weather Provider Service

Key Features and Technologies:

  • Next.js Framework: Developed using Next.js, a powerful React framework, to create a highly responsive and dynamic weather provider platform.
  • Microservice Architecture: Implemented as a microservice to ensure modularity, scalability, and ease of maintenance.
  • MySQL Database: Utilised MySQL for efficient data storage, retrieval, and management of weather data and user information.
  • Docker and Kubernetes Deployment: Deployed the application using Docker containers orchestrated by Kubernetes in the Azure cloud environment, ensuring high availability and scalability.
  • Integration of Weather APIs: Integrated multiple weather APIs including OpenWeather, Apple Weather, DarkSky, AccuWeather, etc., to aggregate weather data and ensure redundancy and reliability.
  • Machine Learning Model: Developed a machine learning model to determine the most accurate weather data provider for a given geographical location, enhancing the service's accuracy and reliability.
  • Authentication and Authorization: Implemented robust authentication mechanisms to ensure secure access to the weather data APIs, safeguarding sensitive information and preventing unauthorized access.
  • Caching and Rate Limiting: Implemented caching mechanisms to improve performance and reduce latency, while also implementing rate limiting to prevent abuse and ensure fair usage of the service.

Achievements and Impact:

  • Successfully developed and deployed a highly utilized weather provider microservice, catering to the needs of a diverse user base.
  • Optimized weather forecasting accuracy by dynamically selecting the best weather data provider based on geographical coordinates and machine learning algorithms.
  • Enhanced user experience through real-time and reliable weather information, contributing to increased user engagement and satisfaction.
  • Demonstrated strong technical leadership and project management skills in overseeing the entire development lifecycle and ensuring the successful delivery of the Weather Provider Service.