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ECS formatted application logs

Logs formatted in Elastic Common Schema (ECS) don’t require manual parsing, and the configuration can be reused across applications. ECS-formatted logs, when paired with an APM agent, allow you to correlate logs to easily view logs that belong to a particular trace.

You can format your logs in ECS format the following ways:

ECS loggers: plugins for your logging libraries that reformat your logs into ECS format.
APM agent ECS reformatting: Java, Ruby, and Python APM agents automatically reformat application logs to ECS format without a logger.

ECS loggers

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ECS loggers reformat your application logs into ECS-compatible JSON, removing the need for manual parsing. ECS loggers require Filebeat or Elastic Agent configured to monitor and capture application logs. In addition, pairing ECS loggers with your framework’s APM agent allows you to correlate logs to easily view logs that belong to a particular trace.

Get startededit

For more information on adding an ECS logger to your application, refer to the guide for your framework:

APM agent ECS reformatting

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Java, Ruby, and Python APM agents can automatically reformat application logs to ECS format without an ECS logger or the need to modify your application. The APM agent also allows for log correlation so you can easily view logs that belong to a particular trace.

To set up log ECS reformatting:

Enable log ECS reformattingedit

Log ECS reformatting is controlled by the log_ecs_reformatting configuration option, and is disabled by default. Refer to the guide for your framework for information on enabling:

Ingest logsedit

After enabling log ECS reformatting, send your application logs to your project using one of the following shipping tools:

Filebeat: A lightweight data shipper that sends log data to your project.
Elastic Agent: A single agent for logs, metrics, security data, and threat prevention. With Fleet, you can centrally manage Elastic Agent policies and lifecycles directly from your project.

Ingest logs with Filebeatedit

Use Filebeat version 8.11+ for the best experience when ingesting logs with Filebeat.

Follow these steps to ingest application logs with Filebeat.

Step 1: Install Filebeatedit

Install Filebeat on the server you want to monitor by running the commands that align with your system:

Download the Filebeat Windows zip file: https://artifacts.elastic.co/downloads/beats/filebeat/filebeat-8.16.0-windows-x86_64.zip
Extract the contents of the zip file into C:\Program Files.
Rename the filebeat-((version))-windows-x86_64 directory to ((filebeat)).
Open a PowerShell prompt as an Administrator (right-click the PowerShell icon and select Run As Administrator).

From the PowerShell prompt, run the following commands to install Filebeat as a Windows service:

PS > cd 'C:\Program Files{filebeat}'
PS C:\Program Files{filebeat}> .\install-service-filebeat.ps1

If script execution is disabled on your system, you need to set the execution policy for the current session to allow the script to run. For example: PowerShell.exe -ExecutionPolicy UnRestricted -File .\install-service-filebeat.ps1.

Step 2: Connect to your projectedit

Connect to your project using an API key to set up Filebeat. Set the following information in the filebeat.yml file:

output.elasticsearch:
  hosts: ["your-projects-elasticsearch-endpoint"]
  api_key: "id:api_key"

Set the hosts to your project’s Elasticsearch endpoint. Locate your project’s endpoint by clicking the help icon () and selecting Endpoints. Add the Elasticsearch endpoint to your configuration.

From Developer tools, run the following command to create an API key that grants manage permissions for the cluster and the filebeat-* indices using:

POST /_security/api_key
{
  "name": "filebeat_host001",
  "role_descriptors": {
    "filebeat_writer": {
      "cluster": ["manage"],
      "index": [
        {
          "names": ["filebeat-*"],
          "privileges": ["manage"]
        }
      ]
    }
  }
}

Refer to Grant access using API keys for more information.

Step 3: Configure Filebeatedit

Add the following configuration to your filebeat.yaml file to start collecting log data.

Add the following configuration to your filebeat.yaml file to start collecting log data.

filebeat.inputs:
- type: filestream   
  paths: /path/to/logs.json
  parsers:
    - ndjson:
        overwrite_keys: true   
        add_error_key: true   
        expand_keys: true   
  fields:
    service.name: your_service_name   
    service.version: your_service_version   
    service.environment: your_service_environment   

processors:   
  - add_host_metadata: ~
  - add_cloud_metadata: ~
  - add_docker_metadata: ~
  - add_kubernetes_metadata: ~

	Use the filestream input to read lines from active log files.
	Values from the decoded JSON object overwrite the fields that Filebeat normally adds (type, source, offset, etc.) in case of conflicts.
	Filebeat adds an "error.message" and "error.type: json" key in case of JSON unmarshalling errors.
	Filebeat will recursively de-dot keys in the decoded JSON, and expand them into a hierarchical object structure.
	The `service.name` (required), `service.version` (optional) and `service.environment` (optional) of the service you’re collecting logs from, used for Log correlation.
	Processors enhance your data. See processors to learn more.

Make sure your application logs to stdout/stderr.
Follow the Run Filebeat on Kubernetes guide.
Enable hints-based autodiscover (uncomment the corresponding section in filebeat-kubernetes.yaml).

Add these annotations to your pods that log using ECS-compatible JSON. This will make sure the logs are parsed appropriately.

annotations:
co.elastic.logs/json.overwrite_keys: true   
co.elastic.logs/json.add_error_key: true   
co.elastic.logs/json.expand_keys: true

	Values from the decoded JSON object overwrite the fields that Filebeat normally adds (type, source, offset, etc.) in case of conflicts.
	Filebeat adds an "error.message" and "error.type: json" key in case of JSON unmarshalling errors.
	Filebeat will recursively de-dot keys in the decoded JSON, and expand them into a hierarchical object structure.

Make sure your application logs to stdout/stderr.
Follow the Run Filebeat on Docker guide.
Enable hints-based autodiscover.
Add these labels to your containers that log using ECS-compatible JSON. This will make sure the logs are parsed appropriately. In docker-compose.yml:

labels:
  co.elastic.logs/json.overwrite_keys: true   
  co.elastic.logs/json.add_error_key: true   
  co.elastic.logs/json.expand_keys: true

	Values from the decoded JSON object overwrite the fields that Filebeat normally adds (type, source, offset, etc.) in case of conflicts.
	Filebeat adds an "error.message" and "error.type: json" key in case of JSON unmarshalling errors.
	Filebeat will recursively de-dot keys in the decoded JSON, and expand them into a hierarchical object structure.

Step 4: Set up and start Filebeatedit

From the Filebeat installation directory, set the index template by running the command that aligns with your system:

From the Filebeat installation directory, start filebeat by running the command that aligns with your system:

Ingest logs with Elastic Agentedit

Add the custom logs integration to ingest and centrally manage your logs using Elastic Agent and Fleet:

Step 1: Add the custom logs integration to your projectedit

To add the custom logs integration to your project:

In your Elastic Observability Serverless project, go to Project Settings → Integrations.
Type custom in the search bar and select Custom Logs.
Click Install Elastic Agent at the bottom of the page, and follow the instructions for your system to install the Elastic Agent. If you’ve already installed an Elastic Agent, you’ll be taken directly to configuring your integration.
After installing the Elastic Agent, click Save and continue to configure the integration from the Add Custom Logs integration page.
Give your integration a meaningful name and description.
Add the Log file path. For example, /var/log/your-logs.log.
Under Custom log file, click Advanced options.
In the Processors text box, add the following YAML configuration to add processors that enhance your data. See processors to learn more.
```
processors:
  - add_host_metadata: ~
  - add_cloud_metadata: ~
  - add_docker_metadata: ~
  - add_kubernetes_metadata: ~
```

Under Custom configurations, add the following YAML configuration to collect data.

json:
  overwrite_keys: true  
  add_error_key: true  
  expand_keys: true  
  keys_under_root: true  
fields_under_root: true  
fields:
  service.name: your_service_name  
  service.version: your_service_version  
  service.environment: your_service_environment

	Values from the decoded JSON object overwrite the fields that Elastic Agent normally adds (type, source, offset, etc.) in case of conflicts.
	Elastic Agent adds an "error.message" and "error.type: json" key in case of JSON unmarshalling errors.
	Elastic Agent will recursively de-dot keys in the decoded JSON, and expand them into a hierarchical object structure.
	By default, the decoded JSON is placed under a "json" key in the output document. When set to `true`, the keys are copied top level in the output document.
	When set to `true`, custom fields are stored as top-level fields in the output document instead of being grouped under a fields sub-dictionary.
	The `service.name` (required), `service.version` (optional), and `service.environment` (optional) of the service you’re collecting logs from, used for Log correlation.

An agent policy is created that defines the data your Elastic Agent collects. If you’ve previously installed an Elastic Agent on the host you’re collecting logs from, you can select the Existing hosts tab and use an existing agent policy.
Click Save and continue.

View logs

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Use Logs Explorer to search, filter, and visualize your logs. Refer to the filter and aggregate logs documentation for more information.

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