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Optimize SIG package deployment for upgrade or rollback
SIG package deployment takes upto 10 minutes or so in a 50+ SIGs and 1000+ nodes cluster. Refactoring SIG deployment such that package distribution and enablement are independently managed. This will allow scheduling new SIG package distribution a...
SIG configuration update currently does full SIG deployment which includes Spark package as well. That on a large cluster with many SIGs can run into hours of deployment. This RFE is requesting to optimize SIG deployment process for Spark configur...
Agnostic/Generic Instance Groups and Resource Scheduler
We are in need of agnostic/generic instance groups and an agnostic/genericresource scheduler.*) agnostic/genericresource schedulerThere is a common need for our data scientists to schedule a "pure" non-Spark TensorFlow Python application to run....
Using EGO Audit Logs To Monitor Log On And Log Off Events At Web GUI and All REST APIs
The EGO Event Audits summarized in Table 1. EGO Event Logging Details of this URL https://www.ibm.com/docs/en/spectrum-conductor/2.4.1?topic=auditing-ego-event-audits define the EGO events that must be audited. The same URL defines the expected a...
Dask support on Conductor based on OpenCE conda packages for Power
Conductor 2.5.0 brings Dask to light. In order to use Dask, one needs to create a conda environment for it. Currently release of Conductor builds that conda environment leveraging WML-CE 1.7.0, a project which was sunset in 2020. It should be lev...
Add slot demand as part of the spark application metric pushed out to elastic search
We would like to have slot demand included as part of the spark application metric that are currently pushed out to elastic search which would help us identify the slot demand vs provisioned for the spark job submitted by the users.
Requesting support for application level performance metrics for Dask jobs to be loaded into ELK. Currently, we get these metrics for spark jobs and would like to get this type of information for Dask jobs as well in 2.5.
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