Data Protection - High Performance Computing Lens

Data Protection

Before architecting any system, you must establish foundational security practices. For example, data classification provides a way to categorize organizational data based on levels of sensitivity, and encryption protects data by rendering it unintelligible to unauthorized access. These tools and techniques are important because they support objectives such as preventing data loss or complying with regulatory obligations.

HPCSEC 3: How does your architecture address data requirements for storage availability and durability through the lifecycle of your results?

In addition to the level of sensitivity and regulatory obligations, HPC data can also be categorized according to when and how the data will next be used. Final results are often retained while intermediate results, which can be recreated if necessary, may not need to be retained. Careful evaluation and categorization of data allows for programmatic data migration of important data to more resilient storage solutions, such as Amazon S3 and Amazon EFS.

An understanding of data longevity combined with programmatic handling of the data offers the minimum exposure and maximum protection for a Well-Architected infrastructure.