Project Overview: This project involved the development of a sophisticated storage feature for CAE, an AI-powered observability and server monitoring solution. The primary objective was to create a tiered storage system that efficiently stores customer data while ensuring cost-effectiveness, compliance with industry regulations, and robust data lifecycle management. Data was stored in three distinct formats—hot, warm, and cold—offering both reduced costs and increased flexibility in data management.

Project Objectives:

1. Tiered Storage: Develop a tiered storage system to optimize the storage of customer data according to its access patterns and lifecycle.

2. Cost Efficiency: Implement cost-effective storage solutions that allow CAE to manage data economically, reducing operational expenses.

3. Compliance: Ensure that data storage practices adhere to industry regulations and data security standards.

4. Data Lifecycle Management: Establish robust data lifecycle management processes, including data retention, archiving, and disposal policies.

Technologies Used:

• Elasticsearch: Utilized for efficient indexing and searching of data.
• AWS S3: Employed for scalable and cost-effective object storage.
• Flask: Used to develop microservices for data management.
• Kubernetes: Orchestrated containerized applications for scalability and deployment.
• Docker: Containerization for portability and efficient resource utilization.

Project Scope:

The project scope encompassed the following key components:

1. Tiered Storage System:

   • Creation of a tiered storage model to classify data into hot, warm, and cold tiers based on usage patterns and access frequency.
   • Integration with Elasticsearch and AWS S3 to manage data across different storage tiers efficiently.

2. Cost-Effective Storage Solutions:

   • Implementation of strategies to optimize storage costs while maintaining data accessibility.
   • Fine-tuning storage configurations to align with CAE's cost management goals.

3. Compliance Measures:

   • Ensuring that data handling practices adhere to industry regulations, data privacy laws, and security standards.
   • Implementing encryption, access controls, and data retention policies as needed.

4. Data Lifecycle Management:

   • Development of comprehensive data lifecycle management processes, including data retention policies, archiving mechanisms, and secure data disposal procedures.

Project Results:

The successful completion of this project yielded the following outcomes:

• A tiered storage system that intelligently manages customer data in hot, warm, and cold storage tiers.
• Improved cost efficiency by reducing storage expenses while preserving data accessibility.
• Enhanced compliance with industry regulations and data security standards.
• Robust data lifecycle management processes to ensure efficient data retention, archiving, and disposal.

Conclusion:

The development of the CAE Tiered Storage Feature empowers CAE to provide customers with a cost-effective, compliant, and efficiently managed data storage solution. Leveraging technologies such as Elasticsearch, AWS S3, Flask, Kubernetes, and Docker, this project contributes to the overall efficiency, scalability, regulatory compliance, and lifecycle management of CAE's observability and server monitoring solution.