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Jesus Honored Contributor.
Honored Contributor.
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Memory requirement for small deployment: 25-30 users

I read for Filr 2.0 the memory requirements are still very high at 12GB recommended.

According to the docs a small deployment supports:
300 - 2,000 concurrent users, depending on the level of user activity.


Now what if you have say 20-30 users, which is possibly down to 1% of what 12Gb supports, can the memory requirements be successfully reduced? Is anyone doing such a thing in production?

--
Gordon
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snielson1 Absent Member.
Absent Member.

Re: Memory requirement for small deployment: 25-30 users

Filr isn't only about the concurrent users.

How many files will you be syncing?
Will you be indexing the content?
How often will you be syncing?
Will users be using the desktop client?
Will users be using the mobile client?

I wouldn't recommend going below 8GB (What I use for my test setup)

Shane Nielson Kind of alright at doing stuff with the computer thing
sveld1 Absent Member.
Absent Member.

Re: Memory requirement for small deployment: 25-30 users

to add to snielson; mind that a single appliance not only runs the Filr Portal and file-access-service (famt), but also the ' search index' and the ' database' which in a large setup run on separate appliances. Officially Novell advice (from docu) is to always use a large setup for production, there is currently no way to go from a small to a large Filr setup.

If you downsize the VM memory mind that you have to tune your JVM setting (Firl admin console at port 9443> Filr Configuration> JVM settings) too; from like 4 to 3 GB case your VM is configured with 8 GB. So, just play with the settings and take into account the memory usage that the OS needs, the Database, famt and the indexer. Have fun!

Best regards, Sebastiaan Veld If you find this post helpful and are logged into the web interface, show your appreciation and click on the star below...
ksiddiqui Absent Member.
Absent Member.

Re: Memory requirement for small deployment: 25-30 users

How many files are initially sync'd in and how many are added on a regular basis moving forward will play a vital role in your planning (and don't consider turning on content indexing if resources are extremely limited).

Realistically speaking, a small all-in-one should only be used in lab/testing/eval instances. It will never be able to meet the needs of a production system. Going from small to large or large clustered deployment will also present challenges down the road.
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Jesus Honored Contributor.
Honored Contributor.

Re: Memory requirement for small deployment: 25-30 users

ksiddiqui;2420656 wrote:
Realistically speaking, a small all-in-one should only be used in lab/testing/eval instances. It will never be able to meet the needs of a production system. Going from small to large or large clustered deployment will also present challenges down the road.


But the docs say a small deployment should be able to support 300 users, so surely 20-30 users should be a breeze, and be a viable option for small organisations.
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Knowledge Partner
Knowledge Partner

Re: Memory requirement for small deployment: 25-30 users

On Tue, 23 Feb 2016 02:36:02 GMT, gordon mzano
<gordon_mzano@no-mx.forums.microfocus.com> wrote:

>
>ksiddiqui;2420656 Wrote:
>> Realistically speaking, a small all-in-one should only be used in
>> lab/testing/eval instances. It will never be able to meet the needs of a
>> production system. Going from small to large or large clustered
>> deployment will also present challenges down the road.

>
>But the docs say a small deployment should be able to support 300 users,
>so surely 20-30 users should be a breeze, and be a viable option for
>small organisations.


It works fine for small organizations. We have 70 users at our
company. I have a small deployment. About half of the employees use
Filr and I have never had a problem with it. The small deployment
option is definitely the way to go for small organizations such as
ours. Just don't skimp on the hardware requirements. I gave mine 12
GB of RAM and 4 virtual sockets (which I believe is the
recommendation). Works great.
Ken
--
Ken
Knowledge Partner

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