Services used by Lyftrondata
Below is the documentation detailing the usage of UI, API, Master API, PostgreSQL, and Airflow with their respective ports, along with an explanation of their dependencies and how they work together.
| Container Name | Purpose | Port's |
|---|---|---|
UI | The UI container hosts the frontend interface, allowing users to interact with the application. Its purpose is to provide a visually appealing and intuitive interface, enabling users to access and manipulate data effectively. It facilitates seamless interaction and enhances the user experience. | 3000 |
UI (React) | Frontend interface built with React.js, providing an interactive user experience for accessing and manipulating application data. | |
API | The API container acts as a mediator between the frontend UI and backend services. Its purpose is to handle incoming requests from the UI, execute business logic, and provide responses containing requested data or status information. It facilitates communication and data exchange between frontend and backend components. | 8000 |
Celery | Celery is a distributed task queue system for Python applications. It enables the execution of tasks asynchronously in the background. With Celery, developers can offload time-consuming or resource-intensive tasks to separate workers, improving application responsiveness and scalability. It's commonly used for processing tasks like data processing, email sending, and periodic task scheduling. | 5672 |
Redis | Key-value store used for caching frequently accessed data, improving application performance by reducing database load. | 6379 |
Master API | The Master API container serves as an additional API for specific administrative tasks. Its purpose is to manage privileged operations or configurations not handled by the primary API. It provides additional functionality for system administrators or privileged users to perform administrative tasks efficiently. | 8001 |
PostgreSQL | The PostgreSQL container hosts the relational database management system (RDBMS) used for storing and managing application data. Its purpose is to provide a reliable and efficient storage solution, ensuring data integrity, security, and scalability for the application. It facilitates persistent data storage and retrieval. | 5432 |
Airflow | The Airflow container orchestrates workflows and task scheduling within the application. Its purpose is to automate task execution, monitor progress, and handle dependencies in data pipelines or ETL processes. It facilitates efficient workflow management and streamlines data processing tasks within the application. | 5009, 8080 |
Airflow Scheduler | Core component of Airflow, responsible for scheduling and triggering workflow tasks based on defined DAG configurations. | 8080 |
Airflow Postgres | Metadata database for Airflow, storing workflow configurations, task status, and execution logs. | 5432 |
Airflow DB Init | Initializes and manages the metadata database schema required by Airflow, ensuring proper setup and configuration. |
Overall, these components work together to provide a comprehensive application environment, with each serving a specific purpose and interacting with others to fulfill the application's functionality and requirements.
Info: For lyftrondata installation on the environment follow the document
Last updated