The Next Frontier: Data Automation for DevOps Test Data Management


We are excited to share that Delphix has been included as a sample vendor for DevOps Test Data Management (TDM) in four Gartner Hype Cycle 2021 reports for Agile and DevOps, Application Security, Data Security and software engineering respectively.

“Each year, Gartner creates more than 90 hype cycles in various areas to keep up with technology maturity and future potential. The five phases of the hype cycle are the Tech Trigger, the Peak of Exaggerated Expectations, the Trough of Disillusionment, the Slope of Enlightenment, and the Plateau of Productivity.5

This year, DevOps Test Data Management emerged as a practice that can be used to improve the efficiency of an agile organization while complying with privacy regulations and protecting against a growing number of ransomware attacks accompanied by breaches. of data.

Gartner defines DevOps test data management as:

The process of providing DevOps teams with data to assess application performance, functionality, and security. This typically includes copying production data, anonymizing or masking, and virtualizing. In some use cases, specialized techniques, such as synthetic data generation, are appropriate. Given potential compliance and privacy concerns, the process more frequently involves members of the application and data security teams.. “1

The rate at which companies can bring new products and services to market determines their ability to differentiate themselves from their competitors and maintain market share. As businesses seek to accelerate innovation, they need a robust and comprehensive test data management (TDM) strategy that supports an agile application infrastructure. Once viewed as a back office function, TDM is now an essential business enabler for agility, security and profitability.

Many large IT organizations have found economies of scale by centralizing the management of test data, often through the use of tools that subset, hide, and synthesize test data. However, these methods lead to a considerable slowing down of the delays or a serious degradation of the quality of the final code.

For DevOps teams struggling to run millions of CI / CD runs per month, it would be impossible to support using a legacy model. That’s why we’ve designed a solution that makes data as automated, flexible, and scalable as other parts of DevOps, such as network, storage, code, and compute. The automation of test data is the last piece of the automation puzzle.

For development and IT teams to effectively deliver the right test data, 4 main areas must be addressed:

  1. Data dissemination: Reduced test data provisioning time
  2. Data quality: Fulfill the requirements for high fidelity test data
  3. Data security and compliance: Minimize security and compliance risks without compromising agility
  4. Infrastructure costs: Reduce the costs of storing and archiving test data

The table below examines these criteria for the most common types of test data.

An API-based platform like Delphix that enables lightweight, compliant data sharing between teams, testing, and other IT processes can have a transformative effect on software development. For more information on Hype Cycle reports, see the full reports (subscription required) on

Learn how to meet modern test data management requirements with the Delphix DevOps Data Platform.

1 Gartner, “Hype Cycle for Agile and DevOps”, George Spafford, Joachim Herschmann, July 2021
2 Gartner, “Application Security Hype Cycle, 2021,” Joerg Fritsch, July 12, 2021
3 Gartner, “Data Security Hype Cycle, 2021,” Brian Lowans, July 27, 2021
4 Gartner, “Software Engineering Hype Cycle, 2021,” Abhishek Singh, Mark O’Neill, July 27, 2021
5 Gartner IT Glossary, “Hype Cycle,” October 8, 2021 (
GARTNER and HYPE CYCLE are a registered trademark and service mark of Gartner, Inc. and / or its subsidiaries in the United States and internationally, and are used here with permission. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner makes no warranty, express or implied, with respect to this research, including any warranty of merchantability or fitness for a particular purpose.

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