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Jobtypes and Applications / Multiple Instances of aerender on the same worker
« Last post by johndavidwright on December 12, 2017, 09:19:51 PM »
Is it possible for a worker to run multiple instances of aerender? Say my worker has 44 slots. If I give my job the reservation host.processors=4 and set it to have 11 instances, would that worker be able to pickup all 11 instances and run 11 instances of aerender?
SimpleCmds / Adding support for AfterEffects CC 2018
« Last post by jburk on October 18, 2017, 10:13:58 PM »
We've added support today for AfterEffects CC 2018, and for those customers running Qube 6.10, you don't have to wait for us to release a new version in order to take advantage of this.

To get access to submitting jobs for CC 2018, install the attached module into the AfterEffects (ArtistView) or aerender (WranglerView) directory located in either application's File->Open AppUI Dir, then restart AV or WV.

This will only be possible in Qube 6.10, earlier versions will not support this ae_versions module.
SimpleCmds / Re: set environment variables with simpleCMD
« Last post by wingart on August 25, 2017, 10:25:58 PM »
thanks, i will give that a try.
SimpleCmds / Re: set environment variables with simpleCMD
« Last post by jburk on August 24, 2017, 08:12:15 PM »
You can do this in the existing preSubmit() function in

Code: [Select]
def preSubmit(cmd, job):
    # Handle renderer-specific callbacks
    if cmd.package['-renderer'] == 'mi':
        return preSubmit_mi(cmd, job)
    elif cmd.package['-renderer'] == 'turtlebake':
        return preSubmit_turtlebake(cmd, job)
    job['env'] = {
        'foo': 'bar',
        'foobar': 'bat'

SimpleCmds / set environment variables with simpleCMD
« Last post by wingart on August 23, 2017, 10:25:04 PM »
I need to set a few environment variables to load up vray before rendering like so:

SET VRAY_PATH=\\server\vray\35203_maya2016
SET VRAY_FOR_MAYA2017_MAIN_x64=%VRAY_PATH%\maya_vray
SET VRAY_FOR_MAYA2017_PLUGINS_x64=%VRAY_PATH%\maya_vray\vrayplugins
SET VRAY_OSL_PATH_MAYA2017_x64=%VRAY_PATH%\vray\opensl
SET VRAY_RENDER_DESC_PATH=%VRAY_PATH%\maya_root\bin\rendererDesc

How do I hardcode it inside['key1']='value1'['key2']='value2'

This is a supervisor-only patch release of 6.9-2 and 6.10-0 that includes the following key fixes.

  • Supervisor patches to help cut down on the number of threads, and reduce chances of repeated worker rejections on some farms due to race-conditions/timing issues.
  • A bug in the startHost() dispatch routine causing the supervisor NOT to always dispatch jobs to workers when they became available.

And this fix which applies to 6.10-0 only:

  • Job instances can become unkill-able with QB_PREEMPT_MODE_FAIL internal status

The releases are labeled as 6.9-2b and 6.10-0a.

NOTE regarding dependencies on Linux: Installation of this updated supervisor package on a linux system requires the use of rpm with the --nodeps argument; the yum utility does not support disabling the dependency checks during installation, only removal.
Announcements / Maintenance/Patch release 6.9-2a of Qube! available
« Last post by jburk on July 10, 2017, 11:29:31 PM »
We have released a patched version of Qube!, labeled 6.9-2a, that contain various fixes. 

This is a recommended release for all customers running Qube v6.9-1 or earlier; customers already running v6.9-2 need only upgrade if they are impacted by any issues addressed by this release.

The Qube! Installer should automatically pick up this new version when the 6.9-2 manifest is chosen from the public repository, or if a local copy of the 6.9-2a manifest is chosen on a host which can access the internet.

Notable fixes and changes are:

Code: [Select]
@CHANGE: background helper thread improvements
* limit the number of workers that are potentially recontacted by the background helper routine to 50 per iteration.
* background thread exits and refreshes after running for approximately 1 hour, as opposed to 24 hours

@CHANGE: job queries requesting for subjob and/or work details now must explicitly provide job IDs.
Both qbjobinfo() C++ and qb.jobinfo() Python APIs now reject such submissions and return an error.
For example, the Python call "qb.jobinfo(subjobs=True)" will raise a runtime exception.
It must be now called like "qb.jobinfo(subjobs=True, id=12345)" or "qb.jobinfo(subjobs=True, id=[1234,5678])"

@FIX: shortened the timeout for "qbreportwork" when it reports a "failed" work that has migrate_on_frame_retry from 600 seconds to 20.
This was causing long 10-minute pauses on the job instance when a frame
fails after exhausting all of its retry counts.

Please review the release notes to see if you are experiencing an issue that may be resolved by this release

Announcements / Qube! 6.10 released
« Last post by jburk on July 06, 2017, 12:30:13 AM »
Today, we have released Qube! 6.10.

To download this latest version, you can visit our website:

To see what platforms or packages are supported in this release, you can visit this page:

What's New in Qube! 6.10-0
  • Online Performance Reports - Accessible through the metered licensing website, we introduce Online Performance Reporting which are by-the-minute reports that provide users with actionable data on how their Supervisors are doing at any given time. With an initial focus on operations and stability, the graphs will reveal site stress, distribution rates and other data points that help wranglers reallocate and troubleshoot. For 6.10-0, online performance reporting is only available for Linux platforms. Support for OS X and Windows will be added in the future.
  • Online License Keys - Perpetual license keys created for Qube! 6.10 and after will now be downloaded via the metered licensing website. Additional information on license history and total worker numbers is also available, with more management features planned for the future.
  • Microsoft Azure Beta Integration - During the beta release of this feature in Qube! 6.10-0, users will have command line access to Microsoft Azure, allowing them to start and stop cloud nodes from within Qube!. Plans for Azure node management through ArtistView are underway.
  • Clarisse Renderer Support - Clarisse renders can now be dispatched from within Qube! via command line, in app, and load once job submissions.
  • Updated Shotgun Integration - The integrated Shotgun user interface has undergone several minor improvements:
    • Qube! Images to Movie submission will pull in specific data from Shotgun
    • the movie upload script has been updated, fixing a major bug that prevented automated movie uploading to the professional project management tool
  • Partner Licensing Daemon – This helper Daemon will be the foundation for future cloud service provider integrations.
  • C4D Take System – Available only in ArtistView, Qube! now supports submission for the Cinema 4D Take System.
  • EXR Support in Modo – Create one job submission per EXR layer from Modo.
  • Deferred Table Creation – Added as an option in a previous version of Qube!, this optimization for submitting a large number of jobs simultaneously will be on by default starting with 6.10-0.
  • Job Modification – Modifications made to jobs will now run multi-threaded as opposed to running single threaded as they did in previous versions of Qube!, and additional verbosity will be available in logs for jobs that were modified.
  • Linux Platform Support – Added support for CentOS 7.3.
With this version of Qube!, we will no longer be supporting the XSI and MTOR job types.
As part of an ongoing effort to allow IT organizations to consume only the exact amount of public cloud computing resources they need, Google this week announced it has removed the memory caps attached to any virtual machine. In addition, Google claims it has become the first public cloud provider to make the latest generation of Intel Xeon processors, codenamed Skylake, generally available via the Google Cloud Platform (GCP).

Paul Nash, group product manager for GCP, says Google is taking pains to enable IT organizations to consume the virtual machines without requiring them to commit to specific sizes on even an hourly amount of time that ultimately winds up forcing them to pay for unused resources.

A Skylake instance of an Intel processor can now be configured with up to 455GB of RAM. Rather than setting specific memory limits, Nash says IT organizations can now determine how much memory they want to allocate to a virtual CPU instance. That approach is intended to be especially appealing to IT organizations aiming to deploy, for example, in-memory computing databases on a public cloud.

“We’re starting to see more deployments of applications such as SAP HANA databases or analytics applications by enterprise customers,” says Nash.

At the same time, via a new Minimum CPU Platform feature, Google is now allowing IT organizations to select a specific CPU platform for VMs in any given zone. GCP will always schedule a virtual machine to run on that class of CPU family or better.

It’s clear that Google is now spending a lot more time and energy courting enterprise customers. While public clouds have been around for 10 years, most enterprise IT organizations are just now making public clouds a standard deployment option for their applications. That doesn’t mean everything will be moving into a public cloud. But it does mean that before making any substantial commitments, many enterprise IT organizations are likely to be very particular about the terms and conditions offered by a public cloud service provider.
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