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A Satellite View of Your Cloud Data Footprint

In the world of increasing data privacy and security regulations, such as GDPR and CCPA, enterprises must start with a data mapping visualization framework and build search capabilities for objects/records across time and space dimensions of its data footprint. Oftentimes, it is complex and cost prohibitive to do this retroactively on legacy systems. The good news is that cloud engineering teams can opportunistically do this as their organizations start to modernize their information systems in the cloud. Specifically related to data compliance and security, cloud engineering teams are now able to provide the visibility Data Protection Officers (DPOs) and Chief Information Security Officers (CISOs) require.

Data privacy and security readiness for an enterprise is a lot like what creditworthiness is for a consumer. Past good behavior rewards the future, past recklessness could question the very existence of the business itself. A consumer can protect their creditworthiness in three simple steps.

  1. Understand the current state of creditworthiness by collecting credit reports across all credit bureaus
  2. Take immediate corrective actions for things that can be addressed right away. As an example, close all revolving accounts that are not in use
  3. Make it a habit to do 1 and 2 regularly OR use a credit monitoring system from a reputable vendor for ongoing monitoring, notifications, and corrections

The same concept applies to data privacy and security readiness for organizations migrating to the cloud or already operating in the cloud

  1. Generate a data visualization map across all cloud accounts, regions, and services – we call this the satellite-like view of data footprint across clouds. This helps to identify problem areas.
  2. Zoom into the problem areas (say, an account, region, or service) and perform corrective actions. For example, identify orphaned snapshots from years ago still lingering in a cloud account creating data privacy liability and incurring storage costs.
  3. Continue to do 1 and 2 on an ongoing basis OR wouldn’t it be great to have a service from a reputable vendor doing that for you?

We previously blogged about being “zoomers” and spending hundreds of hours with CloudOps engineers and learning about their top 5 confessions. The last two of those 5 confessions got a lot of attention from DPOs and CISOs.

For example, the most difficult scenario for any cloud engineering team, and the DPOs and CISOs they support, is not having visibility into the unknown world of their cloud data footprint. They might be non-compliant by accident because they were unaware of some area in the organization that is collecting and maintaining information protected under GDPR/CCPA. A satellite-like visibility across the entire cloud footprint is a critical necessity. That is the starting point from where they can zoom into problem areas and take corrective actions. What if there was an automated service that did this continuously?

And there is a bonus to having satellite-like visibility with zoom-in capability. Cost optimization! Ever since the passage of GDPR, and later with the arrival of CCPA, organizations had been outrightly weighing the cost of retrofitting complex mapping and discovery tools. Or, if they are unable to retrofit, they pay fines when cited for a violation. While this is not a long-term strategy, the nascent and evolving nature of such regulations prompted them to punt such projects down the line. With the arrival of a satellite view, and its ability to deliver actionable insights by zooming in, cost reduction is an added benefit: the icing on the cake.

So how can you achieve satellite-like visibility with zoom-in capability? Stay tuned, on May 27th we’re launching something huge! Can’t wait? Contact us and we would be more than happy to help you discover your true cloud data footprint and what you can do to mitigate risk and reduce costs.

Abdul Rasheed

by Abdul Rasheed

Sr. Director of Product Management

Nic Hernandez

by Nic Hernandez

Cloud SE