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Status Future consideration
Workspace IBM Turbonomic ARM
Created by Guest
Created on Nov 18, 2022

Ability to report Namespace quota and suggest quota values based on formula

My customer's challenge is that their OpenShift clusters are full in Request while actual resource consumption is very low. There are thousands of namespaces with request quotas in their environment. They would like to have Turbonomic identify the most optimal namespace quota size without human intervention and make the change, in addition to what we already can do with workload spec.

Idea priority High
  • Admin
    Eva Tuczai
    Mar 14, 2023

    Our approach will be to provide a Namespace usage report in the new (v2) reporting framework, with a projection of quota size based on a formula. Because of the multiple factors stated in the comments above, this is not conducive to market analysis. Will deliver a prototype report by end of year.

  • Admin
    Eva Tuczai
    Dec 19, 2022

    The challenge here is that our rightsizing optimization algorithm is not what is really wanted. Quotas are not related to any physical capacity, and are usually leveraged for allocation only based capacity planning. Since quotas have no relationship to utilization, the use of quotas forces app owners to set resource specs (limits/requests as applicable) on every workload that is deployed in order to comply with the quota, the real challenge is optimizing the workload sizes within the namespace/project, and modifying the quota is only meaningful if the workload within the quota is optimized FIRST. Consider these scenarios wrt quotas, and the answer may be a spreadsheet, not an optimization algorithm:

    1. NS with quota and no workload. Usage is 0. Resize to what? If someone is using quotas for allocation based capacity planning, then is this capacity being "held" for an app owner until they are ready? What is the definition of ready? How long do you hold onto this "capacity"?

    2. NS with quota, and workload sizes have "filled up" this quota. Usage is 100%. Should I resize up? What if this quota is full because the app owner deployed oversized workloads, and Turbo has a bunch of resize down actions? In this scenario, we have 2 problems:

      1. Resizing up just because the quota is 100% makes no sense unless there is more workload coming, which is usually a capacity planning task.

      2. In this scenario, to get the quota optimization the workload must first resize down, not give more quota

    3. NS with quota, and some workload deployed. Usage is x%. What to resize to? How far back in history do you need to go to accommodate horizontal scaling of workloads?

      1. How long do I keep that "peak"? And should I resize down to the max or leave "headroom" which really makes no sense.

      2. In this scenario, with horizontally scalable workload could be oversized, so every replica is contributing to a bloated quota requirement.

    4. NS with CPU Limit Quota, and workloads need to resize up for CPU Throttling.

      1. Want to understand if Platform owners would really allow the quota resize up, and let a cluster to be more overcommitted on CPU Limit knowing that it was needed to mitigate Throttling and that TURBO would manage resources based on UTILIZATION?

      2. What would they need to do to convince themselves that the Quota should go up, and so should the overcommit ratio (CPU Limit Quota : Physical CPU capacity)? Or would they convince themselves that they need more nodes - which is waste.

    5. For those that use quotas for allocation-only based capacity planning in disguise, the next ask may be to reflect Quota:Cluster Overcommit: sum up all the Quotas and maintain a ratio of quota:physical cluster resources (of some low number like 2:1) so that quotas do not overcommit. Since quotas drive a behavior to oversize workloads, I do not want to propagate inefficient cluster capacity planning through an allocation only model. The real problem is rightsizing the Workloads withing the Namespace, and then assigning a reasonable quota.

    Wanted to share some thoughts and challenges I see when the real problem is the need to optimize the size of the workload running in the namespace, and manage cluster capacity to a combination of allocation (to accommodate requests) and actual utilization (that will optimize both limits and requests)