Qlik Sense Server: Recent Architecture Changes?

[Anonymous]

Hello,

I am wondering if there have been recent changes (last 9 months) to how Qlik Sense Server can be deployed to take advantage of multiple smaller machines on Amazon Web Services?  My company evaluated using Qlik about 10 months ago in AWS, but the memory usage and processing requirements were overwhelming given that our goal was to embed applications inside our own portal for customers.

Recently though I have heard from fellow BI professionals in my network that they are deploying Qlik Sense Server in AWS on thinner machines that make scaling cost very effective. I've spent the last week or so trying to track down materials related to deploying Qlik Sense Server in AWS and any recent changes Qlik may have made to change memory requirements in that kind of deployment, but thus far I haven't found anything that seems like a big change.

I would love any pointers to materials for deploying in AWS and specifically anything that discusses recent architecture requirement changes.  Stories from folks who have successfully done this would also be really helpful as would any referrals to partners that assisted.

Thanks Everyone!

P.S. If this is the wrong place to ask architecture questions, my apologies - just point me to the right location.

[#2]

How much data / How many users?

However nothing has changed. Perhaps the dynamics of your use case are unique?

[Anonymous]

Hi Mike,

Thanks for your response.  We're looking at roughly 7,800 customers accessing our portal with a peak concurrency around 200 (median would be about 80).  On the data side, our minimum requirement is ingesting data from our Redshift cluster which was at 80 Gigs 10 months ago and is now closer to 90.  The data growth for that source is pretty steady at about 1 GB every month.  We have other sources we're tinkering with as a value-add that could be much bigger, but that's still at the whiteboard stage.

Thanks again for any input you might have here.

[#4]

Are you an OEM customer of Qlik? The OEM team should be able to give you some support on this.

Data Model optimization is always a factor in performance and also where you build calculations and functions within the Script vs the UI.

Check out the posts below. Maybe there are a few things in there that may help

Best Practices in Data Modeling.pdf

Best Practices for Data Modelling

[Anonymous]

Thanks Mike.  The OEM angle may be the missing piece here. I'm not sure we got that far the first time around.

Appreciate the links to the docs as well.

[Michael_Tarallo]

Hi Jason in addition to the excellent information that Michael has provided I think one of our colleagues msi‌ might be able to add to this discussion. Marcus - is there additional information you can provide for Jason in regards to his request above?

Thanks all

Please mark the appropriate replies as CORRECT / HELPFUL so our team and other members know that your question(s) has been answered to your satisfaction.

Regards,

Mike Tarallo

Qlik