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Parsing log data

At New Relic, log parsing refers to the process of pulling out attributes (key:value pairs) from your unstructured log data. You can use these attributes to search for and query logs in more practically useful ways, which in turn helps you build better charts and alerts.

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, 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:

Log parsing

How it works

What

  • 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.

When

  • 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 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.

How

  • 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 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.

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

Watch our YouTube video (approx. 6 minutes) to learn how to use a Grok debugger when you create Grok parsing rule patterns:

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 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.

Important

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

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.

Limit

Description

Per-message-per-rule

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.

Per-account

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.

The limit is not a fixed value; it scales up or down proportionally to the volume of data stored daily by the account and the environment size that is subsequently allocated to support that customer.

Tip

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.

logtype

Log source

Example matching query

apache

Apache access logs

logtype:"apache"

apache_error

Apache error logs

logtype:"apache_error"

alb

Application load balancer logs

logtype:"alb"

cassandra

Cassandra logs

logtype:"cassandra"

cloudfront-web

CloudFront (standard web logs)

logtype:"cloudfront-web"

cloudfront-rtl

CloudFront (real-time web logs)

logtype:"cloudfront-rtl"

elb

Elastic Load Balancer logs

logtype:"elb"

haproxy_http

HAProxy logs

logtype:"haproxy_http"

ktranslate-health

KTranslate container health logs

logtype:"ktranslate-health"

linux_cron

Linux cron

logtype:"linux_cron"

linux_messages

Linux messages

logtype:"linux_messages"

iis_w3c

Microsoft IIS server logs - W3C format

logtype:"iis_w3c"

mongodb

MongoDB logs

logtype:"mongodb"

monit

Monit logs

logtype:"monit"

mysql-error

MySQL error logs

logtype:"mysql-error"

nginx

NGINX access logs

logtype:"nginx"

nginx-error

NGINX error logs

logtype:"nginx-error"

postgresql

Postgresql logs

logtype:"postgresql"

rabbitmq

Rabbitmq logs

logtype:"rabbitmq"

redis

Redis logs

logtype:"redis"

route-53

Route 53 logs

logtype:"route-53"

syslog-rfc5424

Syslogs with RFC5424 format

logtype:"syslog-rfc5424"

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.

Tip

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 > 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.
  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 > 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.

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