Kubeturbo resource limits

By default, Kubeturbo deploys without limits or requests. If you prefer to set limits or requests, the amount of resources required for Kubeturbo is related to the number of workloads and pods that it manages. A workload is defined as a unique workload controller, such as deployment foo and statefulset bar.

After you deploy Kubeturbo, you can view the number of workloads in the Turbonomic supply chain. Set the scope to a single container platform cluster and then view the Workload Controller entity.

Note:

Kubeturbo discovers, collects, and processes metrics for container platform resources every one minute and then sends the data to Turbonomic for analysis every 10 minutes. Since data is collected every one minute, Kubeturbo holds the data in memory consistently.

Use the following table as a guide for setting memory limits:

Number of pods	Number of workload controllers	Recommended memory limit (Gi)
5,000	2,500	4
5,000	5,000	4
10,000	5,000	6
10,000	10,000	6.5
20,000	10,000	9.2
20,000	20,000	12
30,000	15,000	13
30,000	30,000	16

Points to consider:

To avoid CPU throttling, do not set a CPU limit.
If needed, memory requests can be set to 1 GB.
If needed, CPU requests can be set to 1 core (1000 millicores).
If Kubeturbo memory usage is very high and consistently growing over time, set a limit that is lower than the node memory capacity to limit the memory usage. Refer to the preceding table for guidance.
To configure Kubeturbo container spec limits and requests, see the next sections.

YAML configuration: Kubeturbo container spec limit and request

Edit the deployment.

kubectl edit deployment kubeturbo -n turbo

In the containers section, find and update the resources: {} section as shown in the following example:
```
resources:
  limits:
    memory: 16Gi
  requests:
    memory: 1Gi
```
If the section does not exist, create it as described.
Save the changes.

The kubeturbo pod restarts with the changes applied automatically.
Verify the changes.
```
kubectl get pods -n turbo -o custom-columns='NAME:.metadata.name,MEMORY_REQ:spec.containers[].resources.requests.memory,MEM_LIM:spec.containers[].resources.limits.memory'
```
The output should be similar to the following example. This output confirms that the memory limit and request was set correctly for kubeturbo.

NAME MEMORY_REQ MEM_LIM

kubeturbo-6cbfc74b68-dfvtk 1Gi 16Gi

Operator configuration: Kubeturbo container spec limit and request

Edit the deployment.

kubectl edit kubeturbo kubeturbo-release -n turbo

In the spec section, find and update the resources: {} section as shown in the following example.
```
resources:
  limits:
    memory: 16Gi
  requests:
    memory: 1Gi
```
If the section does not exist, create it as described.
Save the changes.

The kubeturbo-release pod restarts with the changes applied automatically.
Verify the changes.
```
kubectl get pods -n turbo -o custom-columns='NAME:.metadata.name,MEMORY_REQ:spec.containers[].resources.requests.memory,MEM_LIM:spec.containers[].resources.limits.memory'
```
Verify that the output is similar to the following example. This output confirms that the memory limit and request was set correctly for kubeturbo-release.

NAME MEMORY_REQ MEM_LIM

kubeturbo-release-6cbfc74b68-dfvtk 1Gi 16Gi