Parsing log data

Parsing is the process of splitting unstructured log data into attributes (key/value pairs). You can use these attributes to facet or filter logs in useful ways. This in turn helps you build better charts and alerts.

To get started with parsing, watch the following video tutorial on YouTube (approx. 4-1/2 minutes).

New Relic parses log data according to rules. This document describes how logs parsing works, how to use built-in rules, and how to create custom rules.

You can also create, query, and manage your log parsing rules by using NerdGraph, our GraphQL API, at api.newrelic.com/graphiql. For more information, see our NerdGraph tutorial for parsing.

Parsing example

A good example is a default NGINX access log containing unstructured text. It is useful for searching but not much else. Here's an example of a typical line:

127.180.71.3 - - [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":"93.180.71.3",
  "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:

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 patterns, 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.

You can always use a mix of regular expressions and Grok pattern names in your matching string. For more information, see our list of Grok syntax and supported types.

{
  "message": "54.3.120.2 2048 0"
}

{
  "host_ip": "43.3.120.2",
  "bytes_received": 2048,
  "bytes_sent": 0
}

"%{IP:host_ip} %{INT:bytes_received} %{INT:bytes_sent}"

%{PATTERN_NAME[:OPTIONAL_EXTRACTED_ATTRIBUTE_NAME[:OPTIONAL_TYPE]]}

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:

• Use a built-in rule.
• Define a custom rule.

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 are not applied retroactively. Logs collected before a rule is created are not parsed by that rule.

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

Limits

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.

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.

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 are shipped. Built-in parsing rules are applied by default to certain logtype values.

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

logs:
  - name: file-simple
    file: /path/to/file
    attributes:
      logtype: fileRaw  
  - name: nginx-example
    file: /var/log/nginx.log
    attributes:
      logtype: nginx

<filter containers>
  @type record_transformer
  enable_ruby true
  <record>
    #Add logtype to trigger a built-in parsing rule for nginx access logs
    logtype nginx
    #Set timestamp from the value contained in the field "time"
    timestamp record["time"]
    #Add hostname and tag fields to all records
    hostname "#{Socket.gethostname}"
    tag ${tag}
  </record>
</filter>

[FILTER]
    Name record_modifier
    Match *
    Record logtype nginx
    Record hostname ${HOSTNAME}
    Record service_name Sample-App-Name

filter {
  mutate {
    add_field => {
      "logtype" => "nginx"
      "service_name" => "myservicename"
      "hostname" => "%{host}"
    }
  }
}

POST /log/v1 HTTP/1.1
Host: log-api.newrelic.com
Content-Type: application/json
X-License-Key: YOUR_LICENSE_KEY
Accept: */*
Content-Length: 133
{
  "timestamp": TIMESTAMP_IN_UNIX_EPOCH,
  "message": "User 'xyz' logged in",
  "logtype": "accesslogs",
  "service": "login-service",
  "hostname": "login.example.com"
}

Create 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.

To create and manage your own, custom parsing rules:

1. Go to one.newrelic.com > Logs.
2. From Manage Data on the left nav of the Logs UI, click Parsing, then click Create parsing rule.
3. Enter the parsing rule's name.
4. Choose an attribute and value to match on.
5. Write your Grok pattern and test the rule. To learn about Grok and custom parsing rules, read our blog post about how to parse logs with Grok patterns.
6. Enable and save the custom parsing rule.

To view existing parsing rules:

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

Troubleshooting

If parsing is not working the way you intended, it may be due to:

• Logic: The parsing rule matching logic does not 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.