Dev Streams with Jetstream & Data Masking
Recently I have become inundated with requests from all over the country to talk to people about leveraging their Delphix installations to remove the constraints in their SDLC and DevOps initiatives. I really don't know the last time I got to speak about something I am this this passionate about.
One of the commonly recurring themes I hear is how the data masking process is a huge hurdle. That hurdle takes all shapes and forms: Using synthetic data or subsetting because the data masking process takes too long; Using synthetic data because data masking is too complicated; Using home grown scripts that worked at one point back in time; or, very commonly, "We know we should, but we don't."
I enjoy the enthusiastic discussion with my customers about addressing these pain points. In the end, we come down to the critical remedy: Developers and Testers need self-service tools to be able to get the data they need, when they need it, where they need it; and that data needs to be masked. Some time ago, I put this little video demonstration together highlighting three or four "day in the life of a developer" scenarios to help my customers visualize what happens when your application teams are no longer hindered by yesterday's problems. I thought I would share this with everyone. I re-recorded the audio as the quality wasn't great, so there are a couple of places where I am just a second ahead of the demonstration.
I hope this helps!