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s3 input

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s3 input

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This functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.

Use the s3 input to retrieve logs from S3 objects that are pointed by messages from specific SQS queues. This input can, for example, be used to receive S3 server access logs to monitor detailed records for the requests that are made to a bucket.

When processing a s3 object which pointed by a sqs message, if half of the set visibility timeout passed and the processing is still ongoing, then the visibility timeout of that sqs message will be reset to make sure the message does not go back to the queue in the middle of the processing. If there are errors happening during the processing of the s3 object, then the process will be stopped and the sqs message will be returned back to the queue.

filebeat.inputs:
- type: s3
  queue_url: https://sqs.ap-southeast-1.amazonaws.com/1234/test-s3-queue
  access_key_id: my-access-key
  secret_access_key: my-secret-access-key

The s3 input supports the following configuration options plus the Common options described later.

`queue_url`

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URL of the AWS SQS queue that messages will be received from. Required.

`visibility_timeout`

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The duration (in seconds) that the received messages are hidden from subsequent retrieve requests after being retrieved by a ReceiveMessage request. This value needs to be a lot bigger than filebeat collection frequency so if it took too long to read the s3 log, this sqs message will not be reprocessed. The default visibility timeout for a message is 300 seconds. The minimum is 0 seconds. The maximum is 12 hours.

`aws credentials`

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In order to make AWS API calls, s3 input requires AWS credentials.Please see AWS credentials options for more details.

AWS Permissions

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Specific AWS permissions are required for IAM user to access SQS and S3:

s3:GetObject
sqs:ReceiveMessage
sqs:ChangeMessageVisibility
sqs:DeleteMessage

S3 and SQS setup

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Enable bucket notification: any new object creation in S3 bucket will also create a notification through SQS. Please see create-sqs-queue-for-notification for more details.

Parallel Processing

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Multiple Filebeat instances can read from the same SQS queues at the same time. To horizontally scale processing when there are large amounts of log data flowing into an S3 bucket, you can run multiple Filebeat instances that read from the same SQS queues at the same time. No additional configuration is required.

Using SQS ensures that each message in the queue is processed only once even when multiple Filebeat instances are running in parallel. To prevent Filebeat from receiving and processing the message more than once, set the visibility timeout.

The visibility timeout begins when SQS returns a message to Filebeat. During this time, Filebeat processes and deletes the message. However, if Filebeat fails before deleting the message and your system doesn’t call the DeleteMessage action for that message before the visibility timeout expires, the message becomes visible to other Filebeat instances, and the message is received again. By default, the visibility timeout is set to 5 minutes for s3 input in Filebeat. 5 minutes is sufficient time for Filebeat to read SQS messages and process related s3 log files.

Common options

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The following configuration options are supported by all inputs.

`enabled`

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Use the enabled option to enable and disable inputs. By default, enabled is set to true.

`tags`

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A list of tags that Filebeat includes in the tags field of each published event. Tags make it easy to select specific events in Kibana or apply conditional filtering in Logstash. These tags will be appended to the list of tags specified in the general configuration.

Example:

filebeat.inputs:
- type: s3
  . . .
  tags: ["json"]

`fields`

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Optional fields that you can specify to add additional information to the output. For example, you might add fields that you can use for filtering log data. Fields can be scalar values, arrays, dictionaries, or any nested combination of these. By default, the fields that you specify here will be grouped under a fields sub-dictionary in the output document. To store the custom fields as top-level fields, set the fields_under_root option to true. If a duplicate field is declared in the general configuration, then its value will be overwritten by the value declared here.

filebeat.inputs:
- type: s3
  . . .
  fields:
    app_id: query_engine_12

`fields_under_root`

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If this option is set to true, the custom fields are stored as top-level fields in the output document instead of being grouped under a fields sub-dictionary. If the custom field names conflict with other field names added by Filebeat, then the custom fields overwrite the other fields.

`processors`

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A list of processors to apply to the input data.

See Filter and enhance the exported data for information about specifying processors in your config.

`pipeline`

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The Ingest Node pipeline ID to set for the events generated by this input.

The pipeline ID can also be configured in the Elasticsearch output, but this option usually results in simpler configuration files. If the pipeline is configured both in the input and output, the option from the input is used.

AWS Credentials Configuration

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To configure AWS credentials, either put the credentials into the Filebeat configuration, or use a shared credentials file, as shown in the following examples.

Supported Formats

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Use AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and/or AWS_SESSION_TOKEN

Users can either put the credentials into metricbeat module configuration or use environment variable AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and/or AWS_SESSION_TOKEN instead.

Use AWS credentials in Filebeat configuration

filebeat.inputs:
- type: s3
  queue_url: https://sqs.us-east-1.amazonaws.com/123/test-queue
  access_key_id: '<access_key_id>'
  secret_access_key: '<secret_access_key>'
  session_token: '<session_token>'

filebeat.inputs:
- type: s3
  queue_url: https://sqs.us-east-1.amazonaws.com/123/test-queue
  access_key_id: '${AWS_ACCESS_KEY_ID:""}'
  secret_access_key: '${AWS_SECRET_ACCESS_KEY:""}'
  session_token: '${AWS_SESSION_TOKEN:""}'

Use shared AWS credentials file

filebeat.inputs:
- type: s3
  queue_url: https://sqs.us-east-1.amazonaws.com/123/test-queue
  credential_profile_name: test-fb

credential_profile_name is optional. If there is no credential_profile_name given, the default profile will be used. In Windows, shared credentials file is at C:\Users\<yourUserName>\.aws\credentials. For Linux, macOS or Unix, the file is located at ~/.aws/credentials. Please see Create Shared Credentials File for more details.

AWS Credentials Types

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There are two different types of AWS credentials can be used: access keys and temporary security credentials.

Access keys

AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are the two parts of access keys. They are long-term credentials for an IAM user or the AWS account root user. Please see AWS Access Keys and Secret Access Keys for more details.

Temporary security credentials

temporary security credentials has a limited lifetime and consists of an access key ID, a secret access key, and a security token which typically returned from GetSessionToken. MFA-enabled IAM users would need to submit an MFA code while calling GetSessionToken. default_region identifies the AWS Region whose servers you want to send your first API request to by default. This is typically the Region closest to you, but it can be any Region. Please see Temporary Security Credentials for more details. sts get-session-token AWS CLI can be used to generate temporary credentials. For example. with MFA-enabled:

aws> sts get-session-token --serial-number arn:aws:iam::1234:mfa/your-email@example.com --token-code 456789 --duration-seconds 129600

Because temporary security credentials are short term, after they expire, the user needs to generate new ones and modify the aws.yml config file with the new credentials. Unless live reloading feature is enabled for Metricbeat, the user needs to manually restart Metricbeat after updating the config file in order to continue collecting Cloudwatch metrics. This will cause data loss if the config file is not updated with new credentials before the old ones expire. For Metricbeat, we recommend users to use access keys in config file to enable aws module making AWS api calls without have to generate new temporary credentials and update the config frequently.

IAM policy is an entity that defines permissions to an object within your AWS environment. Specific permissions needs to be added into the IAM user’s policy to authorize Metricbeat to collect AWS monitoring metrics. Please see documentation under each metricset for required permissions.

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