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Production data in test environments

Last updated : Mar 29, 2022
Not on the current edition
This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar Understand more
Mar 2022
Hold ?

We continue to perceive production data in test environments as an area for concern. Firstly, many examples of this have resulted in reputational damage, for example, where an incorrect alert has been sent from a test system to an entire client population. Secondly, the level of security, specifically around protection of private data, tends to be less for test systems. There is little point in having elaborate controls around access to production data if that data is copied to a test database that can be accessed by every developer and QA. Although you can obfuscate the data, this tends to be applied only to specific fields, for example, credit card numbers. Finally, copying production data to test systems can break privacy laws, for example, where test systems are hosted or accessed from a different country or region. This last scenario is especially problematic with complex cloud deployments. Fake data is a safer approach, and tools exist to help in its creation. We do recognize there are reasons for specific elements of production data to be copied, for example, in the reproduction of bugs or for training of specific ML models. Here our advice is to proceed with caution.

Oct 2021
Hold ?

We continue to perceive production data in test environments as an area for concern. Firstly, many examples of this have resulted in reputational damage, for example, where an incorrect alert has been sent from a test system to an entire client population. Secondly, the level of security, specifically around protection of private data, tends to be less for test systems. There is little point in having elaborate controls around access to production data if that data is copied to a test database that can be accessed by every developer and QA. Although you can obfuscate the data, this tends to be applied only to specific fields, for example, credit card numbers. Finally, copying production data to test systems can break privacy laws, for example, where test systems are hosted or accessed from a different country or region. This last scenario is especially problematic with complex cloud deployments. Fake data is a safer approach, and tools exist to help in its creation. We do recognize there are reasons for specific elements of production data to be copied, for example, in the reproduction of bugs or for training of specific ML models. Here our advice is to proceed with caution.

Veröffentlicht : Oct 27, 2021

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