
This PR Adds notes and example on logging for Ray/K8s. Implements an API Reference paging pointing to the configuration guide and the RayCluster CR definition. Takes managed K8s services out of the tabbed structure, to make that page look less sad. Adds a comparison of the KubeRay operator and legacy K8s operator Adds an architecture diagram for the autoscaling sections Fixes some other minor items Adds some info about networking to the configuration guide, removes the previously planned networking page Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>
5.8 KiB
(kuberay-logging)=
Logging
This page provides tips on how to collect logs from Ray clusters running on Kubernetes.
:::{tip}
Skip to {ref}the deployment instructions<kuberay-logging-tldr>
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 {ref}example<kuberay-fluentbit>
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
.
(kuberay-fluentbit)=
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.
:language: yaml
:start-after: Fluent Bit ConfigMap
:end-before: ---
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 theRefresh_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.
:language: yaml
:start-after: Log and config volumes
Mount the Ray log directory
Add the following volume mount to the Ray container's configuration.
:language: yaml
:start-after: Share logs with Fluent Bit
:end-before: Fluent Bit sidecar
Add the Fluent Bit sidecar
Finally, add the Fluent Bit sidecar container to each Ray pod config in your RayCluster CR.
:language: yaml
:start-after: Fluent Bit sidecar
:end-before: Log and config volumes
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.
:language: yaml
Deploying a RayCluster with logging CR.
(kuberay-logging-tldr)= Now, we will see how to deploy the configuration described above.
Deploy the KubeRay Operator if you haven't yet.
Refer to the {ref}Getting Started guide<kuberay-operator-deploy>
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