This documentation contains work-in-progress information for future Elastic Stack and Cloud releases. Use the version selector to view supported release docs. It also contains some Elastic Cloud serverless information. Check out our serverless docs for more details.

› › ›

IP location processor

edit

IP location processor

edit

The ip_location processor adds information about the geographical location of an IPv4 or IPv6 address.

By default, the processor uses the GeoLite2 City, GeoLite2 Country, and GeoLite2 ASN IP geolocation databases from MaxMind, shared under the CC BY-SA 4.0 license. It automatically downloads these databases if your nodes can connect to storage.googleapis.com domain and either:

ingest.geoip.downloader.eager.download is set to true
your cluster has at least one pipeline with a geoip or ip_location processor

Elasticsearch automatically downloads updates for these databases from the Elastic GeoIP endpoint: https://geoip.elastic.co/v1/database. To get download statistics for these updates, use the GeoIP stats API.

If your cluster can’t connect to the Elastic GeoIP endpoint or you want to manage your own updates, see Manage your own IP geolocation database updates.

If you would like to have Elasticsearch download database files directly from Maxmind using your own provided license key, see Create or update IP geolocation database configuration.

If Elasticsearch can’t connect to the endpoint for 30 days all updated databases will become invalid. Elasticsearch will stop enriching documents with ip geolocation data and will add tags: ["_ip_location_expired_database"] field instead.

Using the `ip_location` Processor in a Pipeline

edit

Table 28. ip-location options

Name	Required	Default	Description
`field`	yes	-	The field to get the IP address from for the geographical lookup.
`target_field`	no	ip_location	The field that will hold the geographical information looked up from the database.
`database_file`	no	GeoLite2-City.mmdb	The database filename referring to one of the automatically downloaded GeoLite2 databases (GeoLite2-City.mmdb, GeoLite2-Country.mmdb, or GeoLite2-ASN.mmdb), or the name of a supported database file in the `ingest-geoip` config directory, or the name of a configured database (with the `.mmdb` suffix appended).
`properties`	no	[`continent_name`, `country_iso_code`, `country_name`, `region_iso_code`, `region_name`, `city_name`, `location`] *	Controls what properties are added to the `target_field` based on the ip geolocation lookup.
`ignore_missing`	no	`false`	If `true` and `field` does not exist, the processor quietly exits without modifying the document
`first_only`	no	`true`	If `true` only first found ip geolocation data, will be returned, even if `field` contains array
`download_database_on_pipeline_creation`	no	`true`	If `true` (and if `ingest.geoip.downloader.eager.download` is `false`), the missing database is downloaded when the pipeline is created. Else, the download is triggered by when the pipeline is used as the `default_pipeline` or `final_pipeline` in an index.

*Depends on what is available in database_file:

If a GeoLite2 City or GeoIP2 City database is used, then the following fields may be added under the target_field: ip, country_iso_code, country_name, country_in_european_union, registered_country_iso_code, registered_country_name, registered_country_in_european_union, continent_code, continent_name, region_iso_code, region_name, city_name, postal_code, timezone, location, and accuracy_radius. The fields actually added depend on what has been found and which properties were configured in properties.
If a GeoLite2 Country or GeoIP2 Country database is used, then the following fields may be added under the target_field: ip, country_iso_code, country_name, country_in_european_union, registered_country_iso_code, registered_country_name, registered_country_in_european_union, continent_code, and continent_name. The fields actually added depend on what has been found and which properties were configured in properties.
If the GeoLite2 ASN database is used, then the following fields may be added under the target_field: ip, asn, organization_name and network. The fields actually added depend on what has been found and which properties were configured in properties.
If the GeoIP2 Anonymous IP database is used, then the following fields may be added under the target_field: ip, hosting_provider, tor_exit_node, anonymous_vpn, anonymous, public_proxy, and residential_proxy. The fields actually added depend on what has been found and which properties were configured in properties.
If the GeoIP2 Connection Type database is used, then the following fields may be added under the target_field: ip, and connection_type. The fields actually added depend on what has been found and which properties were configured in properties.
If the GeoIP2 Domain database is used, then the following fields may be added under the target_field: ip, and domain. The fields actually added depend on what has been found and which properties were configured in properties.
If the GeoIP2 ISP database is used, then the following fields may be added under the target_field: ip, asn, organization_name, network, isp, isp_organization_name, mobile_country_code, and mobile_network_code. The fields actually added depend on what has been found and which properties were configured in properties.
If the GeoIP2 Enterprise database is used, then the following fields may be added under the target_field: ip, country_iso_code, country_name, country_in_european_union, registered_country_iso_code, registered_country_name, registered_country_in_european_union, continent_code, continent_name, region_iso_code, region_name, city_name, postal_code, timezone, location, accuracy_radius, country_confidence, city_confidence, postal_confidence, asn, organization_name, network, hosting_provider, tor_exit_node, anonymous_vpn, anonymous, public_proxy, residential_proxy, domain, isp, isp_organization_name, mobile_country_code, mobile_network_code, user_type, and connection_type. The fields actually added depend on what has been found and which properties were configured in properties.

Here is an example that uses the default city database and adds the geographical information to the ip_location field based on the ip field:

resp = client.ingest.put_pipeline(
    id="ip_location",
    description="Add ip geolocation info",
    processors=[
        {
            "ip_location": {
                "field": "ip"
            }
        }
    ],
)
print(resp)

resp1 = client.index(
    index="my-index-000001",
    id="my_id",
    pipeline="ip_location",
    document={
        "ip": "89.160.20.128"
    },
)
print(resp1)

resp2 = client.get(
    index="my-index-000001",
    id="my_id",
)
print(resp2)

const response = await client.ingest.putPipeline({
  id: "ip_location",
  description: "Add ip geolocation info",
  processors: [
    {
      ip_location: {
        field: "ip",
      },
    },
  ],
});
console.log(response);

const response1 = await client.index({
  index: "my-index-000001",
  id: "my_id",
  pipeline: "ip_location",
  document: {
    ip: "89.160.20.128",
  },
});
console.log(response1);

const response2 = await client.get({
  index: "my-index-000001",
  id: "my_id",
});
console.log(response2);

PUT _ingest/pipeline/ip_location
{
  "description" : "Add ip geolocation info",
  "processors" : [
    {
      "ip_location" : {
        "field" : "ip"
      }
    }
  ]
}
PUT my-index-000001/_doc/my_id?pipeline=ip_location
{
  "ip": "89.160.20.128"
}
GET my-index-000001/_doc/my_id

Which returns:

{
  "found": true,
  "_index": "my-index-000001",
  "_id": "my_id",
  "_version": 1,
  "_seq_no": 55,
  "_primary_term": 1,
  "_source": {
    "ip": "89.160.20.128",
    "ip_location": {
      "continent_name": "Europe",
      "country_name": "Sweden",
      "country_iso_code": "SE",
      "city_name" : "Linköping",
      "region_iso_code" : "SE-E",
      "region_name" : "Östergötland County",
      "location": { "lat": 58.4167, "lon": 15.6167 }
    }
  }
}

Here is an example that uses the default country database and adds the geographical information to the geo field based on the ip field. Note that this database is downloaded automatically. So this:

resp = client.ingest.put_pipeline(
    id="ip_location",
    description="Add ip geolocation info",
    processors=[
        {
            "ip_location": {
                "field": "ip",
                "target_field": "geo",
                "database_file": "GeoLite2-Country.mmdb"
            }
        }
    ],
)
print(resp)

resp1 = client.index(
    index="my-index-000001",
    id="my_id",
    pipeline="ip_location",
    document={
        "ip": "89.160.20.128"
    },
)
print(resp1)

resp2 = client.get(
    index="my-index-000001",
    id="my_id",
)
print(resp2)

const response = await client.ingest.putPipeline({
  id: "ip_location",
  description: "Add ip geolocation info",
  processors: [
    {
      ip_location: {
        field: "ip",
        target_field: "geo",
        database_file: "GeoLite2-Country.mmdb",
      },
    },
  ],
});
console.log(response);

const response1 = await client.index({
  index: "my-index-000001",
  id: "my_id",
  pipeline: "ip_location",
  document: {
    ip: "89.160.20.128",
  },
});
console.log(response1);

const response2 = await client.get({
  index: "my-index-000001",
  id: "my_id",
});
console.log(response2);

PUT _ingest/pipeline/ip_location
{
  "description" : "Add ip geolocation info",
  "processors" : [
    {
      "ip_location" : {
        "field" : "ip",
        "target_field" : "geo",
        "database_file" : "GeoLite2-Country.mmdb"
      }
    }
  ]
}
PUT my-index-000001/_doc/my_id?pipeline=ip_location
{
  "ip": "89.160.20.128"
}
GET my-index-000001/_doc/my_id

returns this:

{
  "found": true,
  "_index": "my-index-000001",
  "_id": "my_id",
  "_version": 1,
  "_seq_no": 65,
  "_primary_term": 1,
  "_source": {
    "ip": "89.160.20.128",
    "geo": {
      "continent_name": "Europe",
      "country_name": "Sweden",
      "country_iso_code": "SE"
    }
  }
}

Not all IP addresses find geo information from the database, When this occurs, no target_field is inserted into the document.

Here is an example of what documents will be indexed as when information for "80.231.5.0" cannot be found:

resp = client.ingest.put_pipeline(
    id="ip_location",
    description="Add ip geolocation info",
    processors=[
        {
            "ip_location": {
                "field": "ip"
            }
        }
    ],
)
print(resp)

resp1 = client.index(
    index="my-index-000001",
    id="my_id",
    pipeline="ip_location",
    document={
        "ip": "80.231.5.0"
    },
)
print(resp1)

resp2 = client.get(
    index="my-index-000001",
    id="my_id",
)
print(resp2)

const response = await client.ingest.putPipeline({
  id: "ip_location",
  description: "Add ip geolocation info",
  processors: [
    {
      ip_location: {
        field: "ip",
      },
    },
  ],
});
console.log(response);

const response1 = await client.index({
  index: "my-index-000001",
  id: "my_id",
  pipeline: "ip_location",
  document: {
    ip: "80.231.5.0",
  },
});
console.log(response1);

const response2 = await client.get({
  index: "my-index-000001",
  id: "my_id",
});
console.log(response2);

PUT _ingest/pipeline/ip_location
{
  "description" : "Add ip geolocation info",
  "processors" : [
    {
      "ip_location" : {
        "field" : "ip"
      }
    }
  ]
}

PUT my-index-000001/_doc/my_id?pipeline=ip_location
{
  "ip": "80.231.5.0"
}

GET my-index-000001/_doc/my_id

Which returns:

{
  "_index" : "my-index-000001",
  "_id" : "my_id",
  "_version" : 1,
  "_seq_no" : 71,
  "_primary_term": 1,
  "found" : true,
  "_source" : {
    "ip" : "80.231.5.0"
  }
}

« Inference processor Join processor »

IP location processor

IP location processor

Using the ip_location Processor in a Pipeline

Using the `ip_location` Processor in a Pipeline