DevOps Project – Polis Center

AIM:

The DevOps project aims to streamline the process of making data files readily available for the development teams to work on. DevOps, short for Development and Operations, is a collaborative approach that integrates development, testing, deployment, and operations processes to improve efficiency and reduce the time it takes to deliver software solutions.

OBJECTIVE:

The primary objective of the project is to enhance the efficiency and effectiveness of data file management for development purposes. This involves ensuring that development teams have seamless access to the required data files without encountering delays or inefficiencies.

SCOPE:

The project involves setting up centralized data repositories or pipelines where data files are stored and managed. Automation tools and techniques are employed to automate tasks such as data file updates, synchronization, and access control. Additionally, integration with development tools and platforms is established to seamlessly integrate data files into the development workflow.

KEY FINDINGS:

1. Improved Accessibility: Implementing centralized repositories and automation tools significantly improved the accessibility of data files for development teams. With data files readily available and easily accessible, developers experienced fewer delays and obstacles in obtaining the necessary resources for their tasks.

2. Enhanced Efficiency: Automation of tasks such as data file updates, synchronization, and access control led to notable improvements in efficiency. Manual effort previously required for repetitive tasks was reduced, allowing development teams to focus more on productive work and accelerating the development process.

3. Increased Collaboration: The implementation of DevOps practices fostered better collaboration between development teams, operations, and other stakeholders involved in data file management. Improved communication channels and standardized procedures facilitated smoother coordination and knowledge sharing across teams.

4. Consistency and Reliability: By establishing standardized procedures and automation mechanisms, the project ensured greater consistency and reliability in data file management. Version control systems and automated testing helped maintain the integrity of data files throughout the development lifecycle, reducing the risk of errors and inconsistencies.

5. Scalability: The DevOps solution demonstrated scalability by effectively accommodating the evolving needs of development teams and project requirements. As the project and data requirements grew, the infrastructure and processes could scale seamlessly to meet the increased demand without significant disruption.

WORKFLOW:

Data Acquisition: JSON files containing the data to be converted are obtained from various sources such as APIs, databases, or file systems.

Parsing JSON: The JSON files are parsed to extract the relevant data fields and structures. This step involves reading the JSON files and converting them into a format that can be easily manipulated and processed.

Data Transformation: The extracted data may be transformed to prepare it for conversion to XLSX format. This could include data cleaning, normalization, or restructuring to ensure consistency and compatibility with the target format.

Conversion to XLSX: Once the data is prepared, it is converted to XLSX format. This conversion can be performed using libraries or tools capable of generating Excel-compatible files from structured data.

File Generation: The converted data is written to an XLSX file, creating a spreadsheet containing the transformed data. This file may include multiple sheets, depending on the complexity of the data and the desired organization.