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  • 1.  Customization of pods cpu in MAS

    Posted Mon August 18, 2025 07:38 AM

    Hello Maximo folks,

    Wanted to check if anybody has customized the cpu resource and limits of pods required for MAS. By default, all pods created in installation process considers the alot of additional buffer which at present we see is not required. Because of that our pods are not able to schedule. Although the cpu utlization is very less but still we get insufficient cpu error message in pod as other pods have requested alot of additional buffer.

    If anybody has customized these CPU resource and limit settings, please share your inputs/suggestions or any links we can refer.



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    Poonam Aswani
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  • 2.  RE: Customization of pods cpu in MAS

    Posted Mon August 18, 2025 01:57 PM

    Hi Poonam,

    I experimented with pod templates during our initial R&D for the upgrade but didn't achieve much success. Each improvement really just seemed to create additional complications. Here is some documentation on the custom workloads and pod templates for the CRDs that deploy core and manage services if you'd like to review it. Ultimately, I believe we resolved our issues by just adding more compute resources.



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    Brett Coleman
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  • 3.  RE: Customization of pods cpu in MAS

    Posted Tue August 19, 2025 07:57 AM

    Consider to use Maximo-CPI to collect and review resource usage. In the Resource Optimization Tab, it provides suggested values for adjusting pod resource requests. 



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    Brian Zhu
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  • 4.  RE: Customization of pods cpu in MAS

    Posted Wed August 20, 2025 11:32 AM

    Hi Poonam Aswani,

    We recently customized the CPU resources and limits for the UI pods for one of our clients. These limits can be updated at the deployment level(UI) or via the installed MAS Operator within the Manage project workspace.

    Once the changes are applied, the pods automatically restart to reflect the updated resource configurations, and everything worked as expected



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    Siva Kumar
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  • 5.  RE: Customization of pods cpu in MAS

    Posted Thu August 21, 2025 08:37 AM

    Hi Siva,

    Thanks for providing your inputs. It sounded positive as you have tried some of them. Although not sure what all changes you made in deployment of ui. Would you please share some more details on this? Also, any particular reason of only UI deployment file changed?



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    Poonam Aswani
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  • 6.  RE: Customization of pods cpu in MAS

    Posted Mon August 25, 2025 10:49 AM

    Hi Siva,

    We are also having similar challenge. Is there calculation for the values to be set for resources request and limit? or say, we increase by 30%  or 50% of existing values....also, we update both limits and requests in resources to same values?



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    Prashant Kulkarni
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  • 7.  RE: Customization of pods cpu in MAS

    Posted Tue September 02, 2025 09:41 AM

    Hi Poonam

    To identify the resource request and limit usage values for each pod, use the following command:

    oc describe nodes
    This will display detailed information about each node, including the pods scheduled on them and their respective resource requests and limits.
    For Manage and Core components in the IBM Maximo Application Suite, you can reduce the resource requests and limits by modifying the Custom Resource Definition (CRD) associated with the ManageWorkspace instance or the Suite instance. Specifically:
    - Navigate to the CRD for ManageWorkspace or Suite.
    - Navigate to instances tab
    - Edit the resource specifications under the relevant component sections (e.g., manage, core, etc.).
    - Adjust the resources. Requests and resources.limits values for CPU and memory as needed.
     
    Example snippet from a CRD:
    spec:
      components:
        manage:
          resources:
            requests:
              cpu: "500m"
              memory: "1Gi"
            limits:
              cpu: "1"
              memory: "2Gi"
    Start by slightly reducing the resource requests and limits. Save the CRD. Then test the system and observe its performance over time. If everything remains stable, try reducing the values further. This iterative approach will help you determine optimal settings that prevent resource-related issues caused by overly high requests or limits.


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    Ramakrishnudu Kayala
    Maximo Technical Architect
    Accenture
    Pune
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