This post is one of a series of previews of companies presenting at Cloud Field Day 3, an invitation-only event in Silicon Valley, taking place 4-6 April 2018.  For more information, see the dedicated CFD3 events page

There’s a very interesting theme to the presenters at CFD3 and that highlights one of the challenges of building a multi-cloud strategy – data management.  Larger enterprises developing software in-house, for example, need to be able to safely generate test/dev environments from production data.  Structured data management (stuff in databases) is where Delphix comes in.


It’s very easy to think about traditional data management in the context of unstructured data.  This is because, generally, unstructured content is the main growth area in the enterprise today..  However, structured data sitting in traditional databases is used to drive transactional systems and still has huge financial value to the enterprise.  As part of a DevOps process, developers regularly need to take copies of production data and both transform and obfuscate it before being used in test/dev environments.


Think of the scale of the problem when dealing with structured data.  Historically, a DBA would have restored a test/dev copy from a backup or dump of production, then built scripts to hide or tokenise personal data.  This is a labour intensive and manual process which doesn’t scale well.

In modern DevOps environments, virtual infrastructure can be built out in minutes using tools like AWS CloudFormation, Ravello or scripting with Ansible, Chef and Puppet.  The hard piece here is getting the data into those environments in an automated and safe way.

The Delphix Data Platform solves the data mobility piece of the puzzle but can be used for much more than DevOps seeding.  Database images can be used for analytics, search, production break/fix troubleshooting or cloud migration.

Swiss Army

As a tool, the Delphix Data Platform is a bit of a Swiss Army penknife.  There are lots of things that it could be used for, most of the time only limited by the imagination of the customer.  This is where the marketing gets interesting.  The use cases for Data Platform are really the selling point, so need to focus on the value and ROI that can be achieved.

The Architect’s View

For me, the interesting part of the discussion with Delphix will be on the practicality of implementing Data Platform into other existing processes.  How much can be automated?  How is the audit trail of data maintained, so businesses can conform to regulations like GDPR?  We’ve already discussed Morpheus Data in these previews of Cloud Field Day.  So an obvious question for our readers is to understand how these platforms might both differ and work together.  Delphix can solve the structured part of the puzzle – what about my unstructured and file data?

Here’s one final point to ponder before we hear from the presenters.  If I have a production environment that is many terabytes of data, how do I successfully test new code against a copy?  Development environments usually store a small subset of data for functional testing, whereas user acceptance (showing my age) might implement a full copy of production to validate scalability concerns.

How do either of these concepts work with many developers, each of whom want their own copy of data?  Delivering multiple, space efficient copies of production images will probably be one of the most useful features of these kinds of platforms, but how many can actually deliver it?

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Written by Chris Evans

With 30+ years in IT, Chris has worked on everything from mainframe to open platforms, Windows and more. During that time, he has focused on storage, developed software and even co-founded a music company in the late 1990s. These days it's all about analysis, advice and consultancy.