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Scrape Configs

Promtail is an agent which reads log files and sends streams of log data to the centralised Loki instances along with a set of labels. For example if you are running Promtail in Kubernetes then each container in a single pod will usually yield a single log stream with a set of labels based on that particular pod Kubernetes labels. You can also run Promtail outside Kubernetes, but you would then need to customise the scrape_configs for your particular use case.

The way how Promtail finds out the log locations and extracts the set of labels is by using the scrape_configs section in the Promtail yaml configuration. The syntax is the same what Prometheus uses.

The scrape_configs contains one or more entries which are all executed for each container in each new pod running in the instance. If more than one entry matches your logs you will get duplicates as the logs are sent in more than one stream, likely with a slightly different labels. Everything is based on different labels. The term "label" here is used in more than one different way and they can be easily confused.

  • Labels starting with __ (two underscores) are internal labels. They are not stored to the loki index and are invisible after Promtail. They "magically" appear from different sources.
  • Labels starting with __meta_kubernetes_pod_label_* are "meta labels" which are generated based on your kubernetes pod labels. Example: If your kubernetes pod has a label "name" set to "foobar" then the scrape_configs section will have a label __meta_kubernetes_pod_label_name with value set to "foobar".
  • There are other __meta_kubernetes_* labels based on the Kubernetes metadata, such as the namespace the pod is running (__meta_kubernetes_namespace) or the name of the container inside the pod (__meta_kubernetes_pod_container_name)
  • The label __path__ is a special label which Promtail will read to find out where the log files are to be read in.
  • The label filename is added for every file found in __path__ to ensure uniqueness of the streams. It contains the absolute path of the file being tailed.

The most important part of each entry is the relabel_configs which are a list of operations which creates, renames, modifies or alters labels. A single scrape_config can also reject logs by doing an action: drop if a label value matches a specified regex, which means that this particular scrape_config will not forward logs from a particular log source, but another scrape_config might.

Many of the scrape_configs read labels from __meta_kubernetes_* meta-labels, assign them to intermediate labels such as __service__ based on a few different logic, possibly drop the processing if the __service__ was empty and finally set visible labels (such as "job") based on the __service__ label.

In general, all of the default Promtail scrape_configs do the following:

  • They read pod logs from under /var/log/pods/$1/*.log.
  • They set "namespace" label directly from the __meta_kubernetes_namespace.
  • They expect to see your pod name in the "name" label
  • They set a "job" label which is roughly "your namespace/your job name"

Idioms and examples on different relabel_configs:

  • Drop the processing if a label is empty:
  - action: drop
    regex: ^$
    - __service__
  • Drop the processing if any of these labels contains a value:
  - action: drop
    regex: .+
    separator: ''
    - __meta_kubernetes_pod_label_name
    - __meta_kubernetes_pod_label_app
  • Rename a metadata label into another so that it will be visible in the final log stream:
  - action: replace
    - __meta_kubernetes_namespace
    target_label: namespace
  • Convert all of the Kubernetes pod labels into visible labels:
  - action: labelmap
    regex: __meta_kubernetes_pod_label_(.+)

Additional reading:

Entry parser


Each job can be configured with a pipeline_stages to parse and mutate your log entry. This allows you to add more labels, correct the timestamp or entirely rewrite the log line sent to Loki.

Rewriting labels by parsing the log entry should be done with caution, this could increase the cardinality of streams created by Promtail.

Aside from mutating the log entry, pipeline stages can also generate metrics which could be useful in situation where you can't instrument an application.

See Processing Log Lines for a detailed pipeline description


The original design doc for labels. Post implementation we have strayed quit a bit from the config examples, though the pipeline idea was maintained.

See the pipeline label docs for more info on creating labels from log content.


Metrics can also be extracted from log line content as a set of Prometheus metrics. Metrics are exposed on the path /metrics in promtail. By default a log size histogram (log_entries_bytes_bucket) per stream is computed. This means you don't need to create metrics to count status code or log level, simply parse the log entry and add them to the labels. All custom metrics are prefixed with promtail_custom_.

There are three Prometheus metric types available.

Counter and Gauge record metrics for each line parsed by adding the value. While Histograms observe sampled values by buckets.

See the pipeline metric docs for more info on creating metrics from log content.

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