description |
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Kubernetes Production Grade Log Processor |
Fluent Bit is a lightweight and extensible Log Processor that comes with full support for Kubernetes:
- Process Kubernetes containers logs from the file system or Systemd/Journald.
- Enrich logs with Kubernetes Metadata.
- Centralize your logs in third party storage services like Elasticsearch, InfluxDB, HTTP, etc.
Before getting started it is important to understand how Fluent Bit will be deployed. Kubernetes manages a cluster of nodes, so our log agent tool will need to run on every node to collect logs from every POD, hence Fluent Bit is deployed as a DaemonSet (a POD that runs on every node of the cluster).
When Fluent Bit runs, it will read, parse and filter the logs of every POD and will enrich each entry with the following information (metadata):
- Pod Name
- Pod ID
- Container Name
- Container ID
- Labels
- Annotations
To obtain this information, a built-in filter plugin called kubernetes talks to the Kubernetes API Server to retrieve relevant information such as the pod_id, labels and annotations, other fields such as pod_name, container_id and container_name are retrieved locally from the log file names. All of this is handled automatically, no intervention is required from a configuration aspect.
Our Kubernetes Filter plugin is fully inspired by the Fluentd Kubernetes Metadata Filter written by Jimmi Dyson.
Fluent Bit should be deployed as a DaemonSet, so it will be available on every node of your Kubernetes cluster.
The recommended way to deploy Fluent Bit is with the official Helm Chart: https://github.com/fluent/helm-charts
If you are using Red Hat OpenShift you will also need to set up security context constraints (SCC) using the relevant option in the helm chart.
Helm is a package manager for Kubernetes and allows you to quickly deploy application packages into your running cluster. Fluent Bit is distributed via a helm chart found in the Fluent Helm Charts repo: https://github.com/fluent/helm-charts.
To add the Fluent Helm Charts repo use the following command
helm repo add fluent https://fluent.github.io/helm-charts
To validate that the repo was added you can run helm search repo fluent
to ensure the charts were added. The default chart can then be installed by running the following
helm upgrade --install fluent-bit fluent/fluent-bit
The default chart values include configuration to read container logs, with Docker parsing, systemd logs apply Kubernetes metadata enrichment and finally output to an Elasticsearch cluster. You can modify the values file included https://github.com/fluent/helm-charts/blob/master/charts/fluent-bit/values.yaml to specify additional outputs, health checks, monitoring endpoints, or other configuration options.
The default configuration of Fluent Bit makes sure of the following:
- Consume all containers logs from the running Node and parse them with either the
docker
orcri
multiline parser. - Persist how far it got into each file it is tailing so if a pod is restarted it picks up from where it left off.
- The Kubernetes filter will enrich the logs with Kubernetes metadata, specifically labels and annotations. The filter only goes to the API Server when it cannot find the cached info, otherwise it uses the cache.
- The default backend in the configuration is Elasticsearch set by the Elasticsearch Output Plugin. It uses the Logstash format to ingest the logs. If you need a different Index and Type, please refer to the plugin option and do your own adjustments.
- There is an option called Retry_Limit set to False, that means if Fluent Bit cannot flush the records to Elasticsearch it will re-try indefinitely until it succeed.
Since v1.5.0, Fluent Bit supports deployment to Windows pods.
When deploying Fluent Bit to Kubernetes, there are three log files that you need to pay attention to.
C:\k\kubelet.err.log
- This is the error log file from kubelet daemon running on host.
- You will need to retain this file for future troubleshooting (to debug deployment failures etc.)
C:\var\log\containers\<pod>_<namespace>_<container>-<docker>.log
- This is the main log file you need to watch. Configure Fluent Bit to follow this file.
- It is actually a symlink to the Docker log file in
C:\ProgramData\
, with some additional metadata on its file name.
C:\ProgramData\Docker\containers\<docker>\<docker>.log
- This is the log file produced by Docker.
- Normally you don't directly read from this file, but you need to make sure that this file is visible from Fluent Bit.
Typically, your deployment yaml contains the following volume configuration.
spec:
containers:
- name: fluent-bit
image: my-repo/fluent-bit:1.8.4
volumeMounts:
- mountPath: C:\k
name: k
- mountPath: C:\var\log
name: varlog
- mountPath: C:\ProgramData
name: progdata
volumes:
- name: k
hostPath:
path: C:\k
- name: varlog
hostPath:
path: C:\var\log
- name: progdata
hostPath:
path: C:\ProgramData
Assuming the basic volume configuration described above, you can apply the following config to start logging. You can visualize this configuration here (Sign-up required)
fluent-bit.conf: |
[SERVICE]
Parsers_File C:\\fluent-bit\\parsers.conf
[INPUT]
Name tail
Tag kube.*
Path C:\\var\\log\\containers\\*.log
Parser docker
DB C:\\fluent-bit\\tail_docker.db
Mem_Buf_Limit 7MB
Refresh_Interval 10
[INPUT]
Name tail
Tag kubelet.err
Path C:\\k\\kubelet.err.log
DB C:\\fluent-bit\\tail_kubelet.db
[FILTER]
Name kubernetes
Match kube.*
Kube_URL https://kubernetes.default.svc.cluster.local:443
[OUTPUT]
Name stdout
Match *
parsers.conf: |
[PARSER]
Name docker
Format json
Time_Key time
Time_Format %Y-%m-%dT%H:%M:%S.%L
Time_Keep On
Windows pods often lack working DNS immediately after boot (#78479). To mitigate this issue, filter_kubernetes
provides a built-in mechanism to wait until the network starts up:
DNS_Retries
- Retries N times until the network start working (6)DNS_Wait_Time
- Lookup interval between network status checks (30)
By default, Fluent Bit waits for 3 minutes (30 seconds x 6 times). If it's not enough for you, tweak the configuration as follows.
[filter]
Name kubernetes
...
DNS_Retries 10
DNS_Wait_Time 30