Logging¶

This page provides tips on how to collect logs from Ray clusters running on Kubernetes.

Tip

Skip to the deployment instructions for a sample configuration showing how to extract logs from a Ray pod.

The Ray log directory¶

Each Ray pod runs several component processes, such as the Raylet, object manager, dashboard agent, etc. These components log to files in the directory /tmp/ray/session_latest/logs in the pod’s file system. Extracting and persisting these logs requires some setup.

Log processing tools¶

There are a number of log processing tools available within the Kubernetes ecosystem. This page will shows how to extract Ray logs using Fluent Bit. Other popular tools include Fluentd, Filebeat, and Promtail.

Log collection strategies¶

We mention two strategies for collecting logs written to a pod’s filesystem, sidecar containers and daemonsets. You can read more about these logging patterns in the Kubernetes documentation.

Sidecar containers¶

We will provide an example of the sidecar strategy in this guide. You can process logs by configuring a log-processing sidecar for each Ray pod. Ray containers should be configured to share the /tmp/ray directory with the logging sidecar via a volume mount.

You can configure the sidecar to do either of the following:

  • Stream Ray logs to the sidecar’s stdout.

  • Export logs to an external service.

Daemonset¶

Alternatively, it is possible to collect logs at the Kubernetes node level. To do this, one deploys a log-processing daemonset onto the Kubernetes cluster’s nodes. With this strategy, it is key to mount the Ray container’s /tmp/ray directory to the relevant hostPath.

Setting up logging sidecars with Fluent Bit.¶

In this section, we give an example of how to set up log-emitting Fluent Bit sidecars for Ray pods.

See the full config for a single-pod RayCluster with a logging sidecar here. We now discuss this configuration and show how to deploy it.

Configure log processing¶

The first step is to create a ConfigMap with configuration for Fluent Bit.

Here is a minimal ConfigMap which tells a Fluent Bit sidecar to

  • Tail Ray logs.

  • Output the logs to the container’s stdout.

apiVersion: v1
kind: ConfigMap
metadata:
  name: fluentbit-config
data:
  fluent-bit.conf: |
    [INPUT]
        Name tail
        Path /tmp/ray/session_latest/logs/*
        Tag ray
        Path_Key true
        Refresh_Interval 5
    [OUTPUT]
        Name stdout
        Match *

A few notes on the above config:

  • In addition to streaming logs to stdout, you can use an [OUTPUT] clause to export logs to any storage backend supported by Fluent Bit.

  • The Path_Key true line above ensures that file names are included in the log records emitted by Fluent Bit.

  • The Refresh_Interval 5 line asks Fluent Bit to refresh the list of files in the log directory once per 5 seconds, rather than the default 60. The reason is that the directory /tmp/ray/session_latest/logs/ does not exist initially (Ray must create it first). Setting the Refresh_Interval low allows us to see logs in the Fluent Bit container’s stoud sooner.

Add logging sidecars to your RayCluster CR.¶

Add log and config volumes.¶

For each pod template in our RayCluster CR, we need to add two volumes: One volume for Ray’s logs and another volume to store Fluent Bit configuration from the ConfigMap applied above.

        volumes:
        - name: ray-logs
          emptyDir: {}
        - name: fluentbit-config
          configMap:
            name: fluentbit-config

Mount the Ray log directory¶

Add the following volume mount to the Ray container’s configuration.

          volumeMounts:
          - mountPath: /tmp/ray
            name: ray-logs

Add the Fluent Bit sidecar¶

Finally, add the Fluent Bit sidecar container to each Ray pod config in your RayCluster CR.

        - name: fluentbit
          image: fluent/fluent-bit:1.9.6
          # These resource requests for Fluent Bit should be sufficient in production.
          resources:
            requests:
              cpu: 100m
              memory: 128Mi
            limits:
              cpu: 100m
              memory: 128Mi
          volumeMounts:
          - mountPath: /tmp/ray
            name: ray-logs
          - mountPath: /fluent-bit/etc/fluent-bit.conf
            subPath: fluent-bit.conf
            name: fluentbit-config

Mounting the ray-logs volume gives the sidecar container access to Ray’s logs. The fluentbit-config volume gives the sidecar access to logging configuration.

Putting everything together¶

Putting all of the above elements together, we have the following yaml configuration for a single-pod RayCluster will a log-processing sidecar.

# Fluent Bit ConfigMap
apiVersion: v1
kind: ConfigMap
metadata:
  name: fluentbit-config
data:
  fluent-bit.conf: |
    [INPUT]
        Name tail
        Path /tmp/ray/session_latest/logs/*
        Tag ray
        Path_Key true
        Refresh_Interval 5
    [OUTPUT]
        Name stdout
        Match *
---
# RayCluster CR with a FluentBit sidecar
apiVersion: ray.io/v1alpha1
kind: RayCluster
metadata:
  labels:
    controller-tools.k8s.io: "1.0"
  name: raycluster-complete-logs
spec:
  rayVersion: '2.0.0'
  headGroupSpec:
    serviceType: ClusterIP
    rayStartParams:
      dashboard-host: '0.0.0.0'
      block: 'true'
    template:
      spec:
        containers:
        - name: ray-head
          image: rayproject/ray:2.0.0
          lifecycle:
            preStop:
              exec:
                command: ["/bin/sh","-c","ray stop"]
          # This config is meant for demonstration purposes only.
          # Use larger Ray containers in production!
          resources:
            limits:
              cpu: "1"
              memory: "1G"
            requests:
              cpu: "1"
              memory: "1G"
          # Share logs with Fluent Bit
          volumeMounts:
          - mountPath: /tmp/ray
            name: ray-logs
        # Fluent Bit sidecar
        - name: fluentbit
          image: fluent/fluent-bit:1.9.6
          # These resource requests for Fluent Bit should be sufficient in production.
          resources:
            requests:
              cpu: 100m
              memory: 128Mi
            limits:
              cpu: 100m
              memory: 128Mi
          volumeMounts:
          - mountPath: /tmp/ray
            name: ray-logs
          - mountPath: /fluent-bit/etc/fluent-bit.conf
            subPath: fluent-bit.conf
            name: fluentbit-config
        # Log and config volumes
        volumes:
        - name: ray-logs
          emptyDir: {}
        - name: fluentbit-config
          configMap:
            name: fluentbit-config

Deploying a RayCluster with logging CR.¶

Now, we will see how to deploy the configuration described above.

Deploy the KubeRay Operator if you haven’t yet. Refer to the Getting Started guide for instructions on this step.

Now, run the following commands to deploy the Fluent Bit ConfigMap and a single-pod RayCluster with a Fluent Bit sidecar.

# Starting from the parent of cloned Ray master.
pushd ray/doc/source/cluster/cluster_under_construction/ray-clusters-on-kubernetes/configs/
kubectl apply -f ray-cluster.log.yaml
popd

Determine the Ray pod’s name with

kubectl get pod | grep raycluster-complete-logs

Examine the FluentBit sidecar’s STDOUT to see logs for Ray’s component processes.

# Substitute the name of your Ray pod.
kubectl logs raycluster-complete-logs-head-xxxxx -c fluentbit