Datatype converter processors - Amazon CloudWatch Logs
typeConverterdatetimeConverter
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Datatype converter processors

This section contains information about the datatype converter processors that you can use with a log event transformer.

typeConverter

Use the typeConverter processor to convert a value type associated with the specified key to the specified type. It's a casting processor that changes the types of the specified fields. Values can be converted into one of the following datatypes: integer, double, string and boolean.

Field Description Required? Default Limits

entries

 Array of entries. Each item in the array must contain key and type fields.

Yes

Maximum entries: 10

key

 The key with the value that is to be converted to a different type

Yes

Maximum length: 128

Maximum nested key depth: 3

type

 The type to convert to. Valid values are integer, double, string and boolean.

Yes

Example

Take the following example log event:

{
    "name": "value",
    "status": "200"
}

The transformer configuration is this, using typeConverter with parseJSON:

[
    {
        "parseJSON": {}
    },
    {
        "typeConverter": {
            "entries": [
                {
                    "key": "status",
                    "type": "integer"
                }
            ]
        }
    }
]

The transformed log event would be the following.

{
    "name": "value",
    "status": 200
}

datetimeConverter

Use the datetimeConverter processor to convert a datetime string into a format that you specify.

Field Description Required? Default Limits

source

 The key to apply the date conversion to.

Yes

Maximum entries: 10

matchPatterns

 A list of patterns to match against the source field

Yes

Maximum entries: 5

target

 The JSON field to store the result in.

Yes

Maximum length: 128

Maximum nested key depth: 3

targetFormat

 The datetime format to use for the converted data in the target field.

No

yyyy-MM-dd'T'HH:mm:ss.SSS'Z

Maximum length:64

sourceTimezone

The time zone of the source field.

For a list of possible values, see Java Supported Zone Ids and Offsets.

No

UTC

Minimum length:1

targetTimezone

The time zone of the target field.

For a list of possible values, see Java Supported Zone Ids and Offsets.

No

UTC

Minimum length:1

locale

The locale of the source field.

For a list of possible values, see Locale getAvailableLocales() Method in Java with Examples.

Yes

Minimum length:1

Example

Take the following example log event:

{"german_datetime": "Samstag 05. Dezember 1998 11:00:00"}

The transformer configuration is this, using dateTimeConverter with parseJSON:

[
    {
        "parseJSON": {}
    },
    {
        "dateTimeConverter": {
            "source": "german_datetime",
            "target": "target_1",
            "locale": "de",
            "matchPatterns": ["EEEE dd. MMMM yyyy HH:mm:ss"],
            "sourceTimezone": "Europe/Berlin",
            "targetTimezone": "America/New_York",
            "targetFormat": "yyyy-MM-dd'T'HH:mm:ss z"
        }
    }
]

The transformed log event would be the following.

{
    "german_datetime": "Samstag 05. Dezember 1998 11:00:00",
    "target_1": "1998-12-05T17:00:00 MEZ"
}