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Please use the following category to raise ideas for these offerings for all environments (traditional on-premises, containers, cloud):
Cloud Pak for Multicloud Management
Cloud Pak for Network Automation - including Orchestration and Performance Management
Cloud Pak for Watson AIOps - including Netcool Operations Management portfolio
Edge Application Manager
IBM Observability with Instana
ITM-APM Products - including IBM Tivoli Monitoring v6 and Application Performance Monitoring v8
Workload Automation - including Workload Scheduler
Tivoli System Automation - including Tivoli System Automation Application Manager (SA AM), Tivoli System Automation for Multiplatforms (SA MP)
Custom Template Sensor - executeCommandWithTimeout (may) block if standard input is not redirected from a file
The executeCommandWithTimeout command (may) block if standard input is not redirected from a file. The command we are executing does not as far as I can tell read from standard input, so I don't really understand why this is happening). We redirec...
Application and Event monitoring statefulset operators
The community around the operator pattern and the community framework has gained a lot of traction and has matured quite a bit from its original proposal and delivery. There are increasingly more examples of technologies adopting this pattern (htt...
Operator pattern based deployment lifecycle management for the Application and Event monitoring workload
Refactor the ibm-cloud-appmgmt-prod helm chart to be replaced by a go-sdk operator for controlling the deployment lifecycle, administrative and operation tasks of the IBM Cloud App Management workload.
Note: Not to be confused with using a helm-t...
Vertical scaling of Application and Event monitoring stateful services
A means by which to effectively perform vertical scaling of key stateful services in the `ibm-cloud-appmgmt-prod` chart.
Today, the stateful services include PersistentVolumeClaims in their pod spec, and use helm values to configure the size of t...
Allow for additional inputs into the placement rules. For example: cost of resources within a cluster, network latency of a cluster (ex: edge vs central cloud), networking capacity between locations, cluster hardware capabilities (CPU pinning, GPU...
Enhanced Visibility of Deployed Application Versions.
Update the topology, application, and/or overview screens in MCM to more effectively see what release(s) of applications are deployed to which clusters. These views should be consumable even when there are 100s of clusters and support grouping by ...
When doing an application update (such as from v1.0 to v1.1) for multiple Deployables each deployed in their own cluster, the customer needs more control over how those upgrades are performed. The ability to do a canary deployment (upgrade just on...
When doing an application update (such as from v1.0 to v1.1) for a single Deployable, MCM should support Kubernetes rolling upgrades for each service in the application so that the application can be upgraded with zero downtime. Our understanding ...
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