We did initially encounter some scalability issues. When we first started bringing it in at the end of 2016 and the beginning of 2017, its memory requirements were pretty substantial, and some of our developers - the machines that they were working on at the time - were running into memory issues. It would run very slowly or they would have to restart or it would hang. But since we've upgraded our developer machines, at end-of service - our routine process - and they've gotten additional memory on their machines, we haven't had that problem anymore.

Scalability is not a problem. I've been doing some testing with files that I have access. I can scale it, bring up all my datasets that I need to look at. It works just fine. I can add new filters, whatever I need.

With how we have configured Eclipse, it takes a couple of minutes to initialize, but once it is up, the performance is very good.

I haven't had any scalability issues. As it is on the desktop, scalability is not relevant. 

We haven't encountered any issues with scalability.

Again, it's had a low-utilization rate. We haven't really had any stress test of it.

I have had no issues with scalability.

In terms of scalability, I really haven't dealt with it at that level. It's pretty much been one-for-one types of situations, either batch jobs calling one program or intercepting one program in CICS.