Fluent Bit Kubernetes Filter allows to enrich your log files with Kubernetes metadata.

When Fluent Bit is deployed in Kubernetes as a DaemonSet and configured to read the log files from the containers (using tail or systemd input plugins), this filter aims to perform the following operations:

  • Analyze the Tag and extract the following metadata:

    • Pod Name

    • Namespace

    • Container Name

    • Container ID

  • Query Kubernetes API Server to obtain extra metadata for the POD in question:

    • Pod ID

    • Labels

    • Annotations

The data is cached locally in memory and appended to each record.

Configuration Parameters

The plugin supports the following configuration parameters:

Processing the 'log' value

Kubernetes Filter aims to provide several ways to process the data contained in the log key. The following explanation of the workflow assumes that your original Docker parser defined in parsers.conf is as follows:

    Name         docker
    Format       json
    Time_Key     time
    Time_Format  %Y-%m-%dT%H:%M:%S.%L
    Time_Keep    On

Since Fluent Bit v1.2 we are not suggesting the use of decoders (Decode_Field_As) if you are using Elasticsearch database in the output to avoid data type conflicts.

To perform processing of the log key, it's mandatory to enable the Merge_Log configuration property in this filter, then the following processing order will be done:

  • If a Pod suggest a parser, the filter will use that parser to process the content of log.

  • If the option Merge_Parser was set and the Pod did not suggest a parser, process the log content using the suggested parser in the configuration.

  • If no Pod was suggested and no Merge_Parser is set, try to handle the content as JSON.

If log value processing fails, the value is untouched. The order above is not chained, meaning it's exclusive and the filter will try only one of the options above, not all of them.

Kubernetes Annotations

A flexible feature of Fluent Bit Kubernetes filter is that allow Kubernetes Pods to suggest certain behaviors for the log processor pipeline when processing the records. At the moment it support:

  • Suggest a pre-defined parser

  • Request to exclude logs

The following annotations are available:

Annotation Examples in Pod definition

Suggest a parser

The following Pod definition runs a Pod that emits Apache logs to the standard output, in the Annotations it suggest that the data should be processed using the pre-defined parser called apache:

apiVersion: v1
kind: Pod
  name: apache-logs
    app: apache-logs
    fluentbit.io/parser: apache
  - name: apache
    image: edsiper/apache_logs

Request to exclude logs

There are certain situations where the user would like to request that the log processor simply skip the logs from the Pod in question:

apiVersion: v1
kind: Pod
  name: apache-logs
    app: apache-logs
    fluentbit.io/exclude: "true"
  - name: apache
    image: edsiper/apache_logs

Note that the annotation value is boolean which can take a true or false and must be quoted.

Workflow of Tail + Kubernetes Filter

Kubernetes Filter depends on either Tail or Systemd input plugins to process and enrich records with Kubernetes metadata. Here we will explain the workflow of Tail and how it configuration is correlated with Kubernetes filter. Consider the following configuration example (just for demo purposes, not production):

    Name    tail
    Tag     kube.*
    Path    /var/log/containers/*.log
    Parser  docker

    Name             kubernetes
    Match            kube.*
    Kube_URL         https://kubernetes.default.svc:443
    Kube_CA_File     /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
    Kube_Token_File  /var/run/secrets/kubernetes.io/serviceaccount/token
    Kube_Tag_Prefix  kube.var.log.containers.
    Merge_Log        On
    Merge_Log_Key    log_processed

In the input section, the Tail plugin will monitor all files ending in .log in path /var/log/containers/. For every file it will read every line and apply the docker parser. Then the records are emitted to the next step with an expanded tag.

Tail support Tags expansion, which means that if a tag have a star character (*), it will replace the value with the absolute path of the monitored file, so if you file name and path is:


then the Tag for every record of that file becomes:


note that slashes are replaced with dots.

When Kubernetes Filter runs, it will try to match all records that starts with kube. (note the ending dot), so records from the file mentioned above will hit the matching rule and the filter will try to enrich the records

Kubernetes Filter do not care from where the logs comes from, but it cares about the absolute name of the monitored file, because that information contains the pod name and namespace name that are used to retrieve associated metadata to the running Pod from the Kubernetes Master/API Server.

If you have large pod specifications (can be caused by large numbers of environment variables, etc.), be sure to increase the Buffer_Size parameter of the kubernetes filter. If object sizes exceed this buffer, some metadata will fail to be injected to the logs.

If the configuration property Kube_Tag_Prefix was configured (available on Fluent Bit >= 1.1.x), it will use that value to remove the prefix that was appended to the Tag in the previous Input section. Note that the configuration property defaults to _kube._var.logs.containers. , so the previous Tag content will be transformed from:




the transformation above do not modify the original Tag, just creates a new representation for the filter to perform metadata lookup.

that new value is used by the filter to lookup the pod name and namespace, for that purpose it uses an internal Regular expression:


If you want to know more details, check the source code of that definition here.

You can see on Rublar.com web site how this operation is performed, check the following demo link:

Custom Regex

Under certain and not common conditions, a user would want to alter that hard-coded regular expression, for that purpose the option Regex_Parser can be used (documented on top).

Final Comments

So at this point the filter is able to gather the values of pod_name and namespace, with that information it will check in the local cache (internal hash table) if some metadata for that key pair exists, if so, it will enrich the record with the metadata value, otherwise it will connect to the Kubernetes Master/API Server and retrieve that information.

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