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Trimaran: Load-aware scheduling plugins

Trimaran is a collection of load-aware scheduler plugins described in Trimaran: Real Load Aware Scheduling.

Currently, the collection consists of the following plugins.

  • TargetLoadPacking: Implements a packing policy up to a configured CPU utilization, then switches to a spreading policy among the hot nodes. (Supports CPU resource.)
  • LoadVariationRiskBalancing: Equalizes the risk, defined as a combined measure of average utilization and variation in utilization, among nodes. (Supports CPU and memory resources.)

The Trimaran plugins utilize a load-watcher to access resource utilization data via metrics providers. Currently, the load-watcher supports three metrics providers: Kubernetes Metrics Server, Prometheus Server, and SignalFx.

There are two modes for a Trimaran plugin to use the load-watcher: as a service or as a library.

load-watcher as a service

In this mode, the Trimaran plugin uses a deployed load-watcher service in the cluster as depicted in the figure below. A watcherAddress configuration parameter is required to define the load-watcher service endpoint. For example,

watcherAddress: http://xxxx.svc.cluster.local:2020

Instructions on how to build and deploy the load-watcher can be found here. The load-watcher service may also be deployed in the same scheduler pod, following the tutorial here.

load-watcher as a service

load-watcher as a library

In this mode, the Trimaran plugin embeds the load-watcher as a library, which in turn accesses the configured metrics provider. In this case, we have three configuration parameters: metricProvider.type, metricProvider.address and metricProvider.token.

load-watcher as a library

The configuration parameters should be set as follows.

  • metricProvider.type: the type of the metrics provider
    • KubernetesMetricsServer (default)
    • Prometheus
    • SignalFx
  • metricProvider.address: the address of the metrics provider endpoint, if needed. For the Kubernetes Metrics Server, this parameter may be ignored. For the Prometheus Server, an example setting is
    • http://prometheus-k8s.monitoring.svc.cluster.local:9090
  • metricProvider.token: set only if an authentication token is needed to access the metrics provider.

The selection of the load-watcher mode is based on the existence of a watcherAddress parameter. If it is set, then the load-watcher is in the 'as a service' mode, otherwise it is in the 'as a library' mode.

In addition to the above configuration parameters, the Trimaran plugin may have its own specific parameters.

Following is an example scheduler configuration.

apiVersion: kubescheduler.config.k8s.io/v1beta2
kind: KubeSchedulerConfiguration
leaderElection:
  leaderElect: false
profiles:
- schedulerName: trimaran
  plugins:
    score:
      enabled:
       - name: LoadVariationRiskBalancing
  pluginConfig:
  - name: LoadVariationRiskBalancing
    args:
      metricProvider:
        type: Prometheus
        address: http://prometheus-k8s.monitoring.svc.cluster.local:9090
      safeVarianceMargin: 1
      safeVarianceSensitivity: 2

Configure Prometheus Metric Provider under different environments

  1. Invalid self-signed SSL connection error for the Prometheus metric queries The Prometheus metric queries may have invalid self-signed SSL connection error when the cluster environment disables the skipInsecureVerify option for HTTPs. In this case, you can configure insecureSkipVerify: true for metricProvider to skip the SSL verification.
 args:
   metricProvider:
     type: Prometheus
     address: http://prometheus-k8s.monitoring.svc.cluster.local:9090
     insecureSkipVerify: true
  1. OpenShift Prometheus authentication without tokens. The OpenShift clusters disallow non-verified clients to access its Prometheus metrics. To run the Trimaran plugin on OpenShift, you need to set an environment variable ENABLE_OPENSHIFT_AUTH=true for your trimaran scheduler deployment when run load-watcher as a library.

A note on multiple plugins

The Trimaran plugins have different, potentially conflicting, objectives. Thus, it is recommended not to enable them concurrently. As such, they are designed to each have its own load-watcher.