AWS GCC Infra For A Government Education Authority

About the client

A Singapore-based government education department responsible for formulating and implementing policies, structures, and curricula related to education in the country. It oversees the management and development of government-funded schools, the Institute of Technical Education, polytechnics, and universities.
Industry:
Education, Public Sector
Location:
Singapore

Challenge

Customer has a tender requirement for the provision, development, delivery, installation, testing, and commissioning of a Grammar Error Detection and Correction engine(s) for an AI-enabled Automated Marking System for English Language Writing. The solution needs to meet the operational standards and requirements of an automated marking system while also ensuring resilience against potential disruptions.

Solution

Consulting on GCC Standards: The proposed solution includes providing consulting services on GCC (Government Commercial Cloud) standards. This ensures that the cloud infrastructure setup adheres to the specific security and compliance standards mandated by the government but also aligns with resilience best practices.

Secure AWS Setup: A secure cloud infrastructure will be built on AWS (Amazon Web Services) based on GCC standards. This involves implementing robust security measures, such as access controls, encryption, and network segregation, to protect data and ensure compliance while also fortifying the system against security threats that may compromise resilience.

Environment Segregation: The proposed solution segregates the environments into UAT (User Acceptance Testing), SIT (System Integration Testing), and Production. Each environment follows the AIAS (Automated Marking System) standards and includes various tiers, such as Web, Application, Database, IT, GUT (Grammar Error Detection and Correction engine), and Management Tier.

High Availability Production Environment: The production environment will be designed for high availability across two availability zones. This setup ensures redundancy and fault tolerance, minimizing the risk of downtime and ensuring continuous operation of the AI-enabled Automated Marking System, even in the event of infrastructure failures or outages.

Compliance with GCC Standards: The solution ensures compliance with GCC standards, providing the necessary security and regulatory controls required by the government for data protection and privacy. These compliance measures not only protect the system from potential breaches but also contribute to its overall resilience against cyber threats.

Secure Cloud Infrastructure: The AWS setup will be designed and implemented with robust security measures to safeguard sensitive data and ensure the integrity of the AI-enabled Automated Marking System.

Environment Segregation: By segregating the environments into UAT, SIT, and Production, the solution enables comprehensive testing and deployment processes, ensuring smooth transitions and minimizing disruptions.

High Availability and Fault Tolerance: The production environment’s high availability across two availability zones enhances the system’s resilience and minimizes the risk of downtime or service interruptions. A secure cloud infrastructure is fundamental to building resilience and maintaining the system’s availability and performance.

Compliance with AIAS Standards: The proposed solution aligns with the standards and requirements of the Automated Marking System for English Language Writing, including the specific tiers and components defined in the AIAS guidelines.

Success Metrics

The solution offers customer a secure, compliant, and reliable cloud infrastructure for their AI-enabled Automated Marking System. By aligning with GCC standards, ensuring environment segregation, implementing high availability production environments, and securing the cloud infrastructure, the solution is designed to withstand potential disruptions and maintain continuous operations, even during challenging circumstances.

Tags: Amazon Web Services (AWS) Cloud Infrastructure Education