Sep 9, 2026 · 36 min · 9 segments
How do you move a million mainframe data sets from IBM z/OS to the cloud without a multi-year project? VirtualZ Computing Executive Chairman Marc Sokol and CTO Vince Re walk through the PropelZ…
It's also how do I do that at scale in a production environment where, you know, as you said, it might not be one file.
I mean, when we look at some of our competitors' products, they often don't have much thought around this issue of scale and you know, the operational aspects that go into it.
I mean, if you had to think about every data set is, you know, let's say a batch job or a command line input, the idea of doing hundreds of thousands of those is just, you know, just insane.
It's just something that would, take probably months to find all of those files, figure out how to optimize each of them, and then run them that way.
If I ran 100,000 transfers, which ones worked? Which ones maybe didn't work? What needs to be reviewed? What maybe needs just to be resubmitted? I mean, there's a lot of management challenge when you scale something like that.
The reality here is everyone we speak to, one of the very first questions we get is, how long is it going to take? How many resources do I need? How much bandwidth should I allocate? All of that kind of stuff.
So, again, if you try to do one at a time, this is going to be really, really slow, no matter what resources you have.
But if you don't have an automated strategy to kind of scale things or actually the other way too, if you are tight on resources and you want to be able to scale down, you need something there.
You need a sophisticated way of kind of matching what you're trying to do to what resources that you have.
We'd like a single, really simple way to say, how am I doing? How's it going? What's working? What's not working? What do I need to do from there forward? I mean, that's a really important point of it.
And I'll just mention quickly, we talk about this as a scale problem for number of files, but sometimes the same issue comes up when you have, let's say, one incredibly enormous file that you want to move.
Maybe you've got a database table with trillion rows in it or whatever the details are.
It's also how do I do that at scale in a production environment where, you know, as you said, it might not be one file.
I mean, when we look at some of our competitors' products, they often don't have much thought around this issue of scale and you know, the operational aspects that go into it.
I mean, if you had to think about every data set is, you know, let's say a batch job or a command line input, the idea of doing hundreds of thousands of those is just, you know, just insane.
It's just something that would, take probably months to find all of those files, figure out how to optimize each of them, and then run them that way.
If I ran 100,000 transfers, which ones worked? Which ones maybe didn't work? What needs to be reviewed? What maybe needs just to be resubmitted? I mean, there's a lot of management challenge when you scale something like that.
The reality here is everyone we speak to, one of the very first questions we get is, how long is it going to take? How many resources do I need? How much bandwidth should I allocate? All of that kind of stuff.
So, again, if you try to do one at a time, this is going to be really, really slow, no matter what resources you have.
But if you don't have an automated strategy to kind of scale things or actually the other way too, if you are tight on resources and you want to be able to scale down, you need something there.
You need a sophisticated way of kind of matching what you're trying to do to what resources that you have.
We'd like a single, really simple way to say, how am I doing? How's it going? What's working? What's not working? What do I need to do from there forward? I mean, that's a really important point of it.
And I'll just mention quickly, we talk about this as a scale problem for number of files, but sometimes the same issue comes up when you have, let's say, one incredibly enormous file that you want to move.
Maybe you've got a database table with trillion rows in it or whatever the details are.
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