Seldon Core Resource quota exceeded

What is Seldon Core Resource quota exceeded

Understanding Seldon Core

Seldon Core is an open-source platform designed to deploy machine learning models on Kubernetes. It provides a robust infrastructure for scaling and managing models in production environments, leveraging Kubernetes' capabilities for orchestration and resource management.

Identifying the Symptom: Resource Quota Exceeded

When deploying a model using Seldon Core, you might encounter an error indicating that the resource quota has been exceeded. This typically manifests as a failure to deploy the model, with logs or error messages pointing to resource constraints.

Common Error Messages

"Error: resource quota exceeded" "Failed to schedule pod: Insufficient resources"

Exploring the Issue: Resource Quota Limits

The "Resource quota exceeded" error occurs when the deployment requests more resources than are available within the namespace's quota. Kubernetes namespaces can have resource quotas set to limit the amount of CPU, memory, and other resources that can be consumed by the pods within them.

Understanding Resource Quotas

Resource quotas are defined in Kubernetes to ensure fair resource distribution and prevent any single deployment from monopolizing resources. They are specified in YAML files and applied to namespaces.

Steps to Resolve the Resource Quota Exceeded Issue

To resolve this issue, you can either adjust the resource requests and limits of your deployment or increase the namespace's resource quota.

Adjusting Resource Requests and Limits

Edit your deployment YAML file to reduce the resource requests and limits. For example: resources: requests: memory: "512Mi" cpu: "500m" limits: memory: "1Gi" cpu: "1" Apply the changes using the command: kubectl apply -f your-deployment.yaml

Increasing Namespace Resource Quota

Check the current resource quota with: kubectl get resourcequota --namespace=your-namespace Edit the resource quota YAML file to increase the limits. For example: apiVersion: v1kind: ResourceQuotametadata: name: example-quotaspec: hard: requests.cpu: "2" requests.memory: "4Gi" limits.cpu: "4" limits.memory: "8Gi" Apply the updated quota with: kubectl apply -f your-quota.yaml

Further Reading and Resources

For more information on managing resources in Kubernetes, consider the following resources:

Kubernetes Resource Quotas Seldon Core Documentation