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Grok debugger

Serverless

Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud.

Availability

  • Generally available

    This functionality is generally available and ready for production usage.

Serverless interfaces and procedures might differ from classic Elastic Stack deployments.

Stack

The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats.

Availability

  • Generally available

    This functionality is generally available and ready for production usage.

Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments.

This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.

You can build and debug grok patterns in the Kibana Grok Debugger before you use them in your data processing pipelines. Grok is a pattern matching syntax that you can use to parse arbitrary text and structure it. Grok is good for parsing syslog, apache, and other webserver logs, mysql logs, and in general, any log format that is written for human consumption.

Grok patterns are supported in Elasticsearch runtime fields, the Elasticsearch grok ingest processor, and the Logstash grok filter. For syntax, see Grokking grok.

The Elastic Stack ships with more than 120 reusable grok patterns. For a complete list of patterns, see Elasticsearch grok patterns and Logstash grok patterns.

Because Elasticsearch and Logstash share the same grok implementation and pattern libraries, any grok pattern that you create in the Grok Debugger will work in both Elasticsearch and Logstash.

This example walks you through using the Grok Debugger. This tool is automatically enabled in Kibana.

Note

If you’re using Elastic Stack security features, you must have the manage_pipeline permission to use the Grok Debugger.

  1. Find the Grok Debugger by navigating to the Developer tools page using the navigation menu or the global search field.

  2. In Sample Data, enter a message that is representative of the data that you want to parse. For example:

    Ruby
    55.3.244.1 GET /index.html 15824 0.043
    
  3. In Grok Pattern, enter the grok pattern that you want to apply to the data.

    To parse the log line in this example, use:

    Ruby
    %{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}
    
  4. Click Simulate.

    You’ll see the simulated event that results from applying the grok pattern.

    Grok Debugger
    Grok Debugger

If the default grok pattern dictionary doesn’t contain the patterns you need, you can define, test, and debug custom patterns using the Grok Debugger.

Custom patterns that you enter in the Grok Debugger are not saved. Custom patterns are only available for the current debugging session and have no side effects.

Follow this example to define a custom pattern.

  1. In Sample Data, enter the following sample message:

    Ruby
    Jan  1 06:25:43 mailserver14 postfix/cleanup[21403]: BEF25A72965: message-id=<20130101142543.5828399CCAF@mailserver14.example.com>
    
  2. Enter this grok pattern:

    Ruby
    %{SYSLOGBASE} %{POSTFIX_QUEUEID:queue_id}: %{MSG:syslog_message}
    

    Notice that the grok pattern references custom patterns called POSTFIX_QUEUEID and MSG.

  3. Expand Custom Patterns and enter pattern definitions for the custom patterns that you want to use in the grok expression. You must specify each pattern definition on its own line.

    For this example, you must specify pattern definitions for POSTFIX_QUEUEID and MSG:

    Ruby
    POSTFIX_QUEUEID [0-9A-F]{10,11}
    MSG message-id=<%{GREEDYDATA}>
    
  4. Click Simulate.

    You’ll see the simulated output event that results from applying the grok pattern that contains the custom pattern:

    Debugging a custom pattern
    Debugging a custom pattern

    If an error occurs, you can continue iterating over the custom pattern until the output matches the event that you expect.