Development of a Scalable Knowledge Management System Using JAMstack and Microservices

The organization faces difficulties in effectively searching, classifying, and managing internal knowledge stored across multiple platforms, including a widely-used communication tool. Growing data volume hampers efficient retrieval, leads to categorization issues, and complicates data ownership and security.

A mid-to-large sized remote organization managing extensive internal knowledge and collaboration, seeking a secure and high-performance knowledge aggregation platform.

• Enable efficient search and retrieval of knowledge data, even as data volume grows exponentially.
• Implement a classification and tagging system to organize knowledge based on technology, domains, and content type.
• Enhance data security and access control with microservices architecture, reducing vulnerabilities.
• Ensure scalability and high performance through serverless and CDN-based deployment, minimizing latency and infrastructure costs.
• Streamline data ingestion from existing communication channels via integration and automation.

• Microservices architecture for secure, modular data processing and retrieval
• Static content generation with a modern frontend framework for fast user experience
• Integration with communication platforms to capture, tag, and classify data in real-time
• Search functionality with customizable filtering and metadata-based organization
• Client-side enhancements for interactive querying and data exploration
• Role-based access control and secure authentication mechanisms
• Automated deployment pipelines leveraging CI/CD tools for on-demand rebuild and scalability

• Communication platform APIs (e.g., chat or messaging tools) for capturing data
• Authentication providers for secure access
• External classification or tagging services (if applicable)

• Scalability to support data growth of exponential nature without performance degradation
• Blazing fast load times with CDN delivery and static content
• High security through microservice isolation and limited attack surface
• Zero downtime deployments with automated CI/CD pipelines
• Cost efficiency via serverless infrastructure and pay-per-use models

The implementation of the knowledge management platform is expected to significantly enhance internal data retrieval efficiency, reduce search time, and improve data classification accuracy. Security enhancements will mitigate vulnerabilities, while performance optimizations will support scalable growth. Overall, the project aims to reduce infrastructure costs and increase user productivity, enabling the organization to handle exponentially growing data volumes effectively.