Google Cloud Storage Input Plugin

Basic configuration to read JSON logs every minute from my-logs-bucket. For example, Stackdriver logs.

input {
  google_cloud_storage {
    interval => 60
    bucket_id => "my-logs-bucket"
    json_key_file => "/home/user/key.json"
    file_matches => ".*json"
    codec => "json_lines"
  }
}
output { stdout { codec => rubydebug } }

If your pipeline might insert the same file multiple times you can use the line_id metadata key as a deterministic id.

The ID has the format: gs://<bucket_id>/<object_id>:<line_num>@<generation>. line_num represents the nth event deserialized from the file starting at 1. generation is a unique id Cloud Storage generates for the object. When an object is overwritten it gets a new generation.

input {
  google_cloud_storage {
    bucket_id => "batch-jobs-output"
  }
}

output {
  elasticsearch {
    document_id => "%{[@metadata][gcs][line_id]}"
  }
}

Extract data from Cloud Storage, transform it with Logstash and load it into BigQuery.

input {
  google_cloud_storage {
    interval => 60
    bucket_id => "batch-jobs-output"
    file_matches => "purchases.*.csv"
    json_key_file => "/home/user/key.json"
    codec => "plain"
  }
}

filter {
  csv {
    columns => ["transaction", "sku", "price"]
    convert => {
      "transaction" => "integer"
      "price" => "float"
    }
  }
}

output {
  google_bigquery {
    project_id => "my-project"
    dataset => "logs"
    csv_schema => "transaction:INTEGER,sku:INTEGER,price:FLOAT"
    json_key_file => "/path/to/key.json"
    error_directory => "/tmp/bigquery-errors"
    ignore_unknown_values => true
  }
}

The bucket containing your log files.

The path to the key to authenticate your user to the bucket. This service user should have the storage.objects.update permission so it can create metadata on the object preventing it from being scanned multiple times.

The number of seconds between looking for new files in your bucket.

A regex pattern to filter files. Only files with names matching this will be considered. All files match by default.

Any files matching this regex are excluded from processing. No files are excluded by default.

This key will be set on the objects after they’ve been processed by the plugin. That way you can stop the plugin and not upload files again or prevent them from being uploaded by setting the field manually.

If set, the plugin will store the list of processed files locally. This allows you to create a service account for the plugin that does not have write permissions. However, the data will not be shared across multiple running instances of Logstash.

Should the log file be deleted after its contents have been updated?

If set to true, files ending in .gz are decompressed before they’re parsed by the codec. The file will be skipped if it has the suffix, but can’t be opened as a gzip, e.g. if it has a bad magic number.

Add a field to an event

The codec used for input data. Input codecs are a convenient method for decoding your data before it enters the input, without needing a separate filter in your Logstash pipeline.

Disable or enable metric logging for this specific plugin instance by default we record all the metrics we can, but you can disable metrics collection for a specific plugin.

Add a unique ID to the plugin configuration. If no ID is specified, Logstash will generate one. It is strongly recommended to set this ID in your configuration. This is particularly useful when you have two or more plugins of the same type, for example, if you have 2 google_cloud_storage inputs. Adding a named ID in this case will help in monitoring Logstash when using the monitoring APIs.

input {
  google_cloud_storage {
    id => "my_plugin_id"
  }
}

Add any number of arbitrary tags to your event.

This can help with processing later.

Add a type field to all events handled by this input.

Types are used mainly for filter activation.

The type is stored as part of the event itself, so you can also use the type to search for it in Kibana.

If you try to set a type on an event that already has one (for example when you send an event from a shipper to an indexer) then a new input will not override the existing type. A type set at the shipper stays with that event for its life even when sent to another Logstash server.