Vulnerability Assessment for Cloud-Based AI Platform - atlantiq AI

The main objective of this project is to conduct a comprehensive vulnerability assessment of atlantiq AI's cloud-based infrastructure and AI systems. Learners will be tasked with identifying potential security weaknesses in our AWS-hosted services, including EC2 instances, S3 buckets, RDS databases, and Lambda functions. They will also assess the security of our AI model deployment pipeline and data processing systems. The expected outcomes include: 1. A detailed vulnerability assessment report highlighting critical, high, medium, and low-risk vulnerabilities in our cloud infrastructure and AI systems. 2. Specific recommendations for enhancing our security posture, with a focus on protecting sensitive AI models and user data. 3. A security architecture overview that aligns with our unique needs as an AI-powered SaaS startup, including recommendations for secure AI model deployment and data handling practices. 4. Proposed implementation strategies for recommended security measures, considering our resource constraints as a startup.

Development of Cloud-Based AI Platform - atlantiq AI

The main objective of this project is to optimize and enhance atlantiq AI's multi-tenant SaaS infrastructure and address database complexities. Learners will be tasked with improving the efficiency, scalability, and reliability of our AWS-hosted services, including EC2 instances, S3 buckets, RDS databases, and Lambda functions. They will also focus on refining our database management practices to ensure optimal performance and data integrity. The expected outcomes include: 1. A comprehensive assessment report identifying key areas for optimization in our cloud infrastructure and database systems. 2. Specific recommendations for enhancing our multi-tenant architecture, focusing on scalability and resource management. 3. An architecture overview that aligns with our unique needs as an AI-powered SaaS startup, including recommendations for efficient database management and data handling practices. 4. Proposed implementation strategies for recommended improvements, considering our resource constraints as a startup.

DevOps & Backend Development for Cloud-Based AI Platform - atlantiq AI

The main objective of this project is to enhance and optimize atlantiq AI's cloud-based infrastructure and backend systems. Learners will be tasked with improving the efficiency, scalability, and reliability of our AWS-hosted services, including EC2 instances, S3 buckets, RDS databases, and Lambda functions. They will also work on refining our CI/CD pipelines and automating various aspects of our DevOps processes. The expected outcomes include: A detailed assessment report highlighting areas for improvement in our cloud infrastructure and backend systems. Specific recommendations for enhancing our DevOps practices, with a focus on automation, scalability, and reliability. An architecture overview that aligns with our unique needs as an AI-powered SaaS startup, including recommendations for efficient resource management and deployment practices. Proposed implementation strategies for recommended improvements, considering our resource constraints as a startup.