f850b42474
Automatic merge from submit-queue (batch tested with PRs 60737, 60739, 61080, 60968, 60951). If you want to cherry-pick this change to another branch, please follow the instructions <a href="https://github.com/kubernetes/community/blob/master/contributors/devel/cherry-picks.md">here</a>. Find most recent modified date for fluentd buffers recursively. Fixes #60762 **What this PR does / why we need it**: Due to updates in Fluent v0.14, the buffers directory modified date is no longer updated when files inside the directory are changed. Therefore we must find the most recent modified date recursively to fix liveness probe. **Release note**: ```release-note NONE ``` |
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| fluentd-gcp-image | ||
| podsecuritypolicies | ||
| event-exporter.yaml | ||
| fluentd-gcp-configmap.yaml | ||
| fluentd-gcp-ds-sa.yaml | ||
| fluentd-gcp-ds.yaml | ||
| OWNERS | ||
| README.md | ||
| scaler-deployment.yaml | ||
| scaler-policy.yaml | ||
| scaler-rbac.yaml | ||
Stackdriver Logging Agent
==============
Stackdriver Logging Agent is a DaemonSet which spawns a pod on each node that reads logs, generated by kubelet, container runtime and containers and sends them to the Stackdriver. When logs are exported to the Stackdriver, they can be searched, viewed, and analyzed.
Learn more at: https://kubernetes.io/docs/tasks/debug-application-cluster/logging-stackdriver
Troubleshooting
In Kubernetes clusters in version 1.10.0 or later, fluentd-gcp DaemonSet can be manually scaled. This is useful e.g. when applications running in the cluster are sending a large volume of logs (i.e. over 100kB/s), causing fluentd-gcp to fail with OutOfMemory errors. Conversely, if the applications aren't generating a lot of logs, it may be useful to reduce the amount of resources consumed by fluentd-gcp, making these resources available to other applications. To learn more about Kubernetes resource requests and limits, see the official documentation (CPU, memory). The amount of resources requested by fluentd-gcp on every node in the cluster can be fetched by running following command:
$ kubectl get ds -n kube-system -l k8s-app=fluentd-gcp \
-o custom-columns=NAME:.metadata.name,\
CPU_REQUEST:.spec.template.spec.containers[].resources.requests.cpu,\
MEMORY_REQUEST:.spec.template.spec.containers[].resources.requests.memory,\
MEMORY_LIMIT:.spec.template.spec.containers[].resources.limits.memory
This will display an output similar to the following:
NAME CPU_REQUEST MEMORY_REQUEST MEMORY_LIMIT
fluentd-gcp-v2.0.15 100m 200Mi 300Mi
In order to change those values, a ScalingPolicy needs to be defined. Currently, only base values are supported (no automatic scaling). The ScalingPolicy can be created using kubectl. E.g. to set cpu request to 101m, memory request to 150Mi and memory limit to 400Mi:
$ cat <<EOF | kubectl apply -f -
apiVersion: scalingpolicy.kope.io/v1alpha1
kind: ScalingPolicy
metadata:
name: fluentd-gcp-scaling-policy
namespace: kube-system
spec:
containers:
- name: fluentd-gcp
resources:
requests:
- resource: cpu
base: 101m
- resource: memory
base: 150Mi
limits:
- resource: memory
base: 400Mi
EOF
To remove the override and go back to GKE-provided defaults, it is enough to just remove the ScalingPolicy:
$ kubectl delete -n kube-system scalingpolicies.scalingpolicy.kope.io/fluentd-gcp-scaling-policy