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Parsing log data

Log parsing is the process of translating unstructured log data into attributes (key:value pairs) based on rules you define. You can use these attributes in your NRQL queries to facet or filter logs in useful ways.

New Relic parses log data automatically according to certain parsing rules. In this doc, you'll learn how logs parsing works, and how to create your own custom parsing rules.

You can also create, query, and manage your log parsing rules by using NerdGraph, our GraphQL API. A helpful tool for this is our Nerdgraph API explorer. For more information, see our NerdGraph tutorial for parsing.

Here's a 5-minute video about log parsing:

Parsing example

A good example is a default NGINX access log containing unstructured text. It's useful for searching but not much else. Here's an example of a typical line: - - [10/May/1997:08:05:32 +0000] "GET /downloads/product_1 HTTP/1.1" 304 0 "-" "Debian APT-HTTP/1.3 (0.8.16~exp12ubuntu10.21)"

In an unparsed format, you would need to do a full text search to answer most questions. After parsing, the log is organized into attributes, like response code and request URL:

"remote_addr": "",
"time": "1586514731",
"method": "GET",
"path": "/downloads/product_1",
"version": "HTTP/1.1",
"response": "304",
"bytesSent": 0,
"user_agent": "Debian APT-HTTP/1.3 (0.8.16~exp12ubuntu10.21)"

Parsing makes it easier to create custom queries that facet on those values. This helps you understand the distribution of response codes per request URL and quickly find problematic pages.

How log parsing works

Here's an overview of how New Relic implements parsing of logs:

Log parsing

How it works


  • Parsing is applied to a specific selected field. By default, the message field is used. However, any field/attribute can be chosen, even one that doesn't currently exist in your data.
  • Each parsing rule is created by using a NRQL WHERE clause that determines which logs the rule will attempt to parse.
  • To simplify the matching process, we recommend adding a logtype attribute to your logs. However, you are not limited to using logtype; one or more attributes can be used as matching criteria in the NRQL WHERE clause.


  • Parsing will only be applied once to each log message. If multiple parsing rules match the log, only the first that succeeds will be applied.
  • Parsing rules are unordered. If more than one parsing rules matches a log, one is chosen at random. Be sure to build your parsing rules so that they do not match the same logs.
  • Parsing takes place during log ingestion, before data is written to NRDB. Once data has been written to storage, it can no longer be parsed.
  • Parsing occurs in the pipeline before data enrichments take place. Be careful when defining the matching criteria for a parsing rule. If the criteria is based on an attribute that doesn't exist until after parsing or enrichment take place, that data won't be present in the logs when matching occurs. As a result, no parsing will happen.


  • Rules can be written in Grok, regex, or a mixture of the two. Grok is a collection of patterns that abstract away complicated regular expressions.

Parse attributes using Grok

Parsing patterns are specified using Grok, an industry standard for parsing log messages. Any incoming log with a logtype field will be checked against our built-in parsing rules, and if possible, the associated Grok pattern is applied to the log.

Grok is a superset of regular expressions that adds built-in named patterns to be used in place of literal complex regular expressions. For instance, instead of having to remember that an integer can be matched with the regular expression (?:[+-]?(?:[0-9]+)), you can just write %{INT} to use the Grok pattern INT, which represents the same regular expression.

Grok patterns have the syntax:



  • PATTERN_NAME is one of the supported Grok patterns. The pattern name is just a user-friendly name representing a regular expression. They are exactly equal to the corresponding regular expression.
  • OPTIONAL_EXTRACTED_ATTRIBUTE_NAME, if provided, is the name of the attribute that will be added to your log message with the value matched by the pattern name. It's equivalent to using a named capture group using regular expressions. If this is not provided, then the parsing rule will just match a region of your string, but not extract an attribute with its value.
  • OPTIONAL_TYPE specifies the type of attribute value to extract. If omitted, values are extracted as strings. For instance, to extract the value 123 from "File Size: 123" as a number into attribute file_size, use value: %{INT:file_size:int}.
  • OPTIONAL_PARAMETER specifies an optional parameter for certain types. Currently only the datetime type takes a parameter, see below for details.

You can also use a mix of regular expressions and Grok pattern names in your matching string.

Click this link for a list of supported Grok patterns, and here for a list of supported Grok types.

Note that variable names must be explicitly set and be lowercase like %{URI:uri}. Expressions such as %{URI} or %{URI:URI} would not work.

Organizing by logtype

New Relic's log ingestion pipeline can parse data by matching a log event to a rule that describes how the log should be parsed. There are two ways log events can be parsed:

Rules are a combination of matching logic and parsing logic. Matching is done by defining a query match on an attribute of the logs. Rules aren't applied retroactively. Logs collected before a rule is created aren't parsed by that rule.

The simplest way to organize your logs and how they're parsed is to include the logtype field in your log event. This tells New Relic what built-in rule to apply to the logs.


Once a parsing rule is active, data parsed by the rule is permanently changed. This can't be reverted.


Parsing is computationally expensive, which introduces risk. Parsing is done for custom rules defined in an account and for matching patterns to a log. A large number of patterns or poorly defined custom rules will consume a huge amount of memory and CPU resources while also taking a very long time to complete.

In order to prevent problems, we apply two parsing limits: per-message-per-rule and per-account.




The per-message-per-rule limit prevents the time spent parsing any single message from being greater than 100 ms. If that limit is reached, the system will cease attempting to parse the log message with that rule.

The ingestion pipeline will attempt to run any other applicable on that message, and the message will still be passed through the ingestion pipeline and stored in NRDB. The log message will be in its original, unparsed format.


The per-account limit exists to prevent accounts from using more than their fair share of resources. The limit considers the total time spent processing all log messages for an account per-minute.


To easily check if your rate limits have been reached, go to your system Limits page in the New Relic UI.

Built-in parsing rules

Common log formats have well-established parsing rules already created for them. To get the benefit of built-in parsing rules, add the logtype attribute when forwarding logs. Set the value to something listed in the following table, and the rules for that type of log will be applied automatically.

List of built-in rules

The following logtype attribute values map to a predefined parsing rule. For example, to query the Application Load Balancer:

  • From the New Relic UI, use the format logtype:"alb".
  • From NerdGraph, use the format logtype = 'alb'.

To learn what fields are parsed for each rule, see our documentation about built-in parsing rules.


Log source

Example matching query


Apache access logs



Apache error logs



Application load balancer logs



Cassandra logs



CloudFront (standard web logs)



CloudFront (real-time web logs)



Elastic Load Balancer logs



HAProxy logs



KTranslate container health logs



Linux cron



Linux messages



Microsoft IIS server logs - W3C format



MongoDB logs



Monit logs



MySQL error logs



NGINX access logs



NGINX error logs



Postgresql logs



Rabbitmq logs



Redis logs



Route 53 logs



Syslogs with RFC5424 format


Add the logtype attribute

When aggregating logs, it's important to provide metadata that makes it easy to organize, search, and parse those logs. One simple way of doing this is to add the attribute logtype to the log messages when they're shipped. Built-in parsing rules are applied by default to certain logtype values.


The fields logType, logtype, and LOGTYPE are all supported for built-in rules. For ease of searching, we recommend that you align on a single syntax in your organization.

Here are some examples of how to add logtype to logs sent by some of our supported shipping methods.

Create and view custom parsing rules

Many logs are formatted or structured in a unique way. In order to parse them, custom logic must be built and applied.

From the left nav in the logs UI, select Parsing, then create your own custom parsing rule with a valid NRQL WHERE clause and Grok pattern.

To create and manage your own, custom parsing rules:

  1. Go to one.newrelic.com > All capabilities > Logs.
  2. From Manage data on the left nav of the logs UI, click Parsing, then click Create parsing rule.
  3. Enter a name for the new parsing rule.
  4. Select an existing field to parse (default = message), or enter a new field name.
  5. Enter a valid NRQL WHERE clause to match the logs you want to parse.
  6. Select a matching log if one exists, or click on the Paste log tab to paste in a sample log. Note that if you copy text from the logs UI or the query builder to paste into the parsing UI, ensure that it's the Unformatted version.
  7. Enter the parsing rule and validate it's working by viewing the results in the Output section. To learn about Grok and custom parsing rules, read our blog post about how to parse logs with Grok patterns.
  8. Enable and save the custom parsing rule.

To view existing parsing rules:

  1. Go to one.newrelic.com > All capabilities > Logs.
  2. From Manage data on the left nav of the logs UI, click Parsing.


If parsing isn't working the way you intended, it may be due to:

  • Logic: The parsing rule matching logic doesn't match the logs you want.
  • Timing: If your parsing matching rule targets a value that doesn't exist yet, it will fail. This can occur if the value is added later in the pipeline as part of the enrichment process.
  • Limits: There is a fixed amount of time available every minute to process logs via parsing, patterns, drop filters, etc. If the maximum amount of time has been spent, parsing will be skipped for additional log event records.

To resolve these problems, create or adjust your custom parsing rules.

If you haven't already, create your free New Relic account below to start monitoring your data today.

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