Introduction

Grapes is a solution that automates the provisioning of non-production environments with datasets.

Grapes operates on the principle that production data is the best dataset for executing realistic and comprehensive test scenarios.

However, using production data can pose significant constraints, especially in the following areas:

• Confidentiality: Some data must remain confidential. This includes personal data, as well as health and financial information.

• Volume: Some databases are too large to be used in their current state on a test or development environment. The physical (or virtual) sizing of servers in non-production environments is generally smaller than that of production, making it sometimes impossible to properly execute applications using these databases.

• Consistency: With the development of microservices architectures and the increasing typology of databases (Relational, Document, Key-Value, etc.), it becomes more difficult to create consistent datasets between multiple services or databases.

• Complexity: The usual procedure of backup/restore of databases can be complex either due to access reasons or due to the very nature of certain databases that do not offer this type of service.

Grapes addresses all of these constraints with the following features:

• Support for multiple types of databases.
• Automatic detection of personal and sensitive data.
• Over 12 data anonymization functions.
• Intelligent data sampling.
• Cascade data filtering.