Kubernetes Descheduler: Balancing workloads automatically

2 min readDec 11, 2023

Kubernetes offers various built-in tools for managing node workloads, like NodeSelector, PodAffinity, and Anti-PodAffinity. However, these rules only apply when scheduling new pods. Once a pod is running, it doesn’t adapt to changes in the cluster. This can lead to uneven workload distribution and inefficient resource usage.

The Descheduler solves this problem by providing an automated system for runtime rescheduling. It analyzes your cluster and redistributes pods based on your specified policies. This can improve performance, resource utilization, and overall cluster health.

Understanding the Need for Descheduler

While Kubernetes provides tools like NodeSelector, NodeAffinity, and Pod Topology Spread Constraints to influence pod placement, these options only apply during initial scheduling. After deployment, changes in node utilization or node labels require manual intervention to adjust pod distribution.

Descheduler addresses this gap by automating pod redeployment based on defined policies. This eliminates the need for manual intervention and ensures continuous workload optimization.

Installation and Usage

Descheduler can be deployed using various methods, including Job, CronJob, or Deployment. The Deployment option provides high availability (HA) using the leader election mechanism. This ensures that only one Descheduler instance is making decisions at a time.

Descheduler also offers metrics for Prometheus, allowing you to monitor its performance and identify potential issues.

Here’s an example of deploying Descheduler with Helm and HA enabled:

$ helm repo add descheduler https://kubernetes-sigs.github.io/descheduler/
$ helm upgrade --install descheduler --namespace kube-system descheduler/descheduler --version=0.28.0 -f values.yaml

Values in the values.yaml file can be customized, like the number of replicas and leader election settings.

Descheduler Architecture and Configuration

Descheduler operates on a policy-driven architecture. Policies consist of Evictors and Strategies.

  • Evictors: Define which pods are eligible for redeployment based on criteria such as pod status, labels, or annotations.
  • Strategies: Determine under what circumstances pods should be redeployed. Different strategies address specific needs, such as removing duplicate pods, balancing workloads across nodes, or evicting pods based on restart count.

Descheduler offers flexible configuration options:

  • Deployment options: Choose between Job, CronJob, or Deployment methods depending on your needs.
  • HA architecture: The Deployment option utilizes a Leader Election mechanism for high availability.
  • Metrics collection: Descheduler provides Prometheus metrics for monitoring and debugging purposes.

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