Log Data Model

Status: Experimental

This is a data model and semantic conventions that allow to represent logs from various sources: application log files, machine generated events, system logs, etc. Existing log formats can be unambiguously mapped to this data model. Reverse mapping from this data model is also possible to the extent that the target log format has equivalent capabilities.

The purpose of the data model is to have a common understanding of what a log record is, what data needs to be recorded, transferred, stored and interpreted by a logging system.

This proposal defines a data model for Standalone Logs.

Design Notes


The Data Model was designed to satisfy the following requirements:

  • It should be possible to unambiguously map existing log formats to this Data Model. Translating log data from an arbitrary log format to this Data Model and back should ideally result in identical data.

  • Mappings of other log formats to this Data Model should be semantically meaningful. The Data Model must preserve the semantics of particular elements of existing log formats.

  • Translating log data from an arbitrary log format A to this Data Model and then translating from the Data Model to another log format B ideally must result in a meaningful translation of log data that is no worse than a reasonable direct translation from log format A to log format B.

  • It should be possible to efficiently represent the Data Model in concrete implementations that require the data to be stored or transmitted. We primarily care about 2 aspects of efficiency: CPU usage for serialization/deserialization and space requirements in serialized form. This is an indirect requirement that is affected by the specific representation of the Data Model rather than the Data Model itself, but is still useful to keep in mind.

The Data Model aims to successfully represent 3 sorts of logs and events:

  • System Formats. These are logs and events generated by the operating system and over which we have no control - we cannot change the format or affect what information is included (unless the data is generated by an application which we can modify). An example of system format is Syslog.

  • Third-party Applications. These are generated by third-party applications. We may have certain control over what information is included, e.g. customize the format. An example is Apache log file.

  • First-party Applications. These are applications that we develop and we have some control over how the logs and events are generated and what information we include in the logs. We can likely modify the source code of the application if needed.

Definitions Used in this Document

In this document we refer to types any and map<string, any>, defined as follows.

Type any

Value of type any can be one of the following:

  • A scalar value: number, string or boolean,

  • A byte array,

  • An array (a list) of any values,

  • A map<string, any>.

Type map<string, any>

Value of type map<string, any> is a map of string keys to any values. The keys in the map are unique (duplicate keys are not allowed). The representation of the map is language-dependent.

Arbitrary deep nesting of values for arrays and maps is allowed (essentially allows to represent an equivalent of a JSON object).

Field Kinds

This Data Model defines a logical model for a log record (irrespective of the physical format and encoding of the record). Each record contains 2 kinds of fields:

  • Named top-level fields of specific type and meaning.

  • Fields stored as map<string, any>, which can contain arbitrary values of different types. The keys and values for well-known fields follow semantic conventions for key names and possible values that allow all parties that work with the field to have the same interpretation of the data. See references to semantic conventions for Resource and Attributes fields and examples in Appendix A.

The reasons for having these 2 kinds of fields are:

  • Ability to efficiently represent named top-level fields, which are almost always present (e.g. when using encodings like Protocol Buffers where fields are enumerated but not named on the wire).

  • Ability to enforce types of named fields, which is very useful for compiled languages with type checks.

  • Flexibility to represent less frequent data as map<string, any>. This includes well-known data that has standardized semantics as well as arbitrary custom data that the application may want to include in the logs.

When designing this data model we followed the following reasoning to make a decision about when to use a top-level named field:

  • The field needs to be either mandatory for all records or be frequently present in well-known log and event formats (such as Timestamp) or is expected to be often present in log records in upcoming logging systems (such as TraceId).

  • The field’s semantics must be the same for all known log and event formats and can be mapped directly and unambiguously to this data model.

Both of the above conditions were required to give the field a place in the top-level structure of the record.

Log and Event Record Definition

Appendix A contains many examples that show how existing log formats map to the fields defined below. If there are questions about the meaning of the field reviewing the examples may be helpful.

Here is the list of fields in a log record:

Field Name Description
Timestamp Time when the event occurred.
TraceId Request trace id.
SpanId Request span id.
TraceFlags W3C trace flag.
SeverityText The severity text (also known as log level).
SeverityNumber Numerical value of the severity.
Name Short event identifier.
Body The body of the log record.
Resource Describes the source of the log.
Attributes Additional information about the event.

Below is the detailed description of each field.

Field: Timestamp

Type: Timestamp, uint64 nanoseconds since Unix epoch.

Description: Time when the event occurred measured by the origin clock. This field is optional, it may be missing if the timestamp is unknown.

Trace Context Fields

Field: TraceId

Type: byte sequence.

Description: Request trace id as defined in W3C Trace Context. Can be set for logs that are part of request processing and have an assigned trace id. This field is optional.

Field: SpanId

Type: byte sequence.

Description: Span id. Can be set for logs that are part of a particular processing span. If SpanId is present TraceId SHOULD be also present. This field is optional.

Field: TraceFlags

Type: byte.

Description: Trace flag as defined in W3C Trace Context specification. At the time of writing the specification defines one flag - the SAMPLED flag. This field is optional.

Severity Fields

Field: SeverityText

Type: string.

Description: severity text (also known as log level). This is the original string representation of the severity as it is known at the source. If this field is missing and SeverityNumber is present then the short name that corresponds to the SeverityNumber may be used as a substitution. This field is optional.

Field: SeverityNumber

Type: number.

Description: numerical value of the severity, normalized to values described in this document. This field is optional.

SeverityNumber is an integer number. Smaller numerical values correspond to less severe events (such as debug events), larger numerical values correspond to more severe events (such as errors and critical events). The following table defines the meaning of SeverityNumber value:

SeverityNumber range Range name Meaning
1-4 TRACE A fine-grained debugging event. Typically disabled in default configurations.
5-8 DEBUG A debugging event.
9-12 INFO An informational event. Indicates that an event happened.
13-16 WARN A warning event. Not an error but is likely more important than an informational event.
17-20 ERROR An error event. Something went wrong.
21-24 FATAL A fatal error such as application or system crash.

Smaller numerical values in each range represent less important (less severe) events. Larger numerical values in each range represent more important (more severe) events. For example SeverityNumber=17 describes an error that is less critical than an error with SeverityNumber=20.

Mapping of SeverityNumber

Mappings from existing logging systems and formats (or source format for short) must define how severity (or log level) of that particular format corresponds to SeverityNumber of this data model based on the meaning given for each range in the above table.

If the source format has more than one severity that matches a single range in this table then the severities of the source format must be assigned numerical values from that range according to how severe (important) the source severity is.

For example if the source format defines “Error” and “Critical” as error events and “Critical” is a more important and more severe situation then we can choose the following SeverityNumber values for the mapping: “Error”->17, “Critical”->18.

If the source format has only a single severity that matches the meaning of the range then it is recommended to assign that severity the smallest value of the range.

For example if the source format has an “Informational” log level and no other log levels with similar meaning then it is recommended to use SeverityNumber=9 for “Informational”.

Source formats that do not define a concept of severity or log level MAY omit SeverityNumber and SeverityText fields. Backend and UI may represent log records with missing severity information distinctly or may interpret log records with missing SeverityNumber and SeverityText fields as if the SeverityNumber was set equal to INFO (numeric value of 9).

Reverse Mapping

When performing a reverse mapping from SeverityNumber to a specific format and the SeverityNumber has no corresponding mapping entry for that format then it is recommended to choose the target severity that is in the same severity range and is closest numerically.

For example Zap has only one severity in the INFO range, called “Info”. When doing reverse mapping all SeverityNumber values in INFO range (numeric 9-12) will be mapped to Zap’s “Info” level.

Error Semantics

If SeverityNumber is present and has a value of ERROR (numeric 17) or higher then it is an indication that the log record represents an erroneous situation. It is up to the reader of this value to make a decision on how to use this fact (e.g. UIs may display such errors in a different color or have a feature to find all erroneous log records).

If the log record represents an erroneous event and the source format does not define a severity or log level concept then it is recommended to set SeverityNumber to ERROR (numeric 17) during the mapping process. If the log record represents a non-erroneous event the SeverityNumber field may be omitted or may be set to any numeric value less than ERROR (numeric 17). The recommended value in this case is INFO (numeric 9). See Appendix B for more mapping examples.

Displaying Severity

The following table defines the recommended short name for each SeverityNumber value. The short name can be used for example for representing the SeverityNumber in the UI:

SeverityNumber Short Name
10 INFO2
11 INFO3
12 INFO4
14 WARN2
15 WARN3
16 WARN4

When an individual log record is displayed it is recommended to show both SeverityText and SeverityNumber values. A recommended combined string in this case begins with the short name followed by SeverityText in parenthesis.

For example “Informational” Syslog record will be displayed as INFO (Informational). When for a particular log record the SeverityNumber is defined but the SeverityText is missing it is recommended to only show the short name, e.g. INFO.

When drop down lists (or other UI elements that are intended to represent the possible set of values) are used for representing the severity it is preferable to display the short name in such UI elements.

For example a dropdown list of severities that allows filtering log records by severities is likely to be more usable if it contains the short names of SeverityNumber (and thus has a limited upper bound of elements) compared to a dropdown list, which lists all distinct SeverityText values that are known to the system (which can be a large number of elements, often differing only in capitalization or abbreviated, e.g. “Info” vs “Information”).

Comparing Severity

In the contexts where severity participates in less-than / greater-than comparisons SeverityNumber field should be used. SeverityNumber can be compared to another SeverityNumber or to numbers in the 1..24 range (or to the corresponding short names).

Field: Name

Type: string.

Description: Short event identifier that does not contain varying parts. Name describes what happened (e.g. “ProcessStarted”). Recommended to be no longer than 50 characters. Not guaranteed to be unique in any way. Typically used for filtering and grouping purposes in backends. This field is optional.

Field: Body

Type: any.

Description: A value containing the body of the log record (see the description of any type above). Can be for example a human-readable string message (including multi-line) describing the event in a free form or it can be a structured data composed of arrays and maps of other values. First-party Applications SHOULD use a string message. However, a structured body may be necessary to preserve the semantics of some existing log formats. Can vary for each occurrence of the event coming from the same source. This field is optional.

Field: Resource

Type: map<string, any>.

Description: Describes the source of the log, aka resource. Multiple occurrences of events coming from the same event source can happen across time and they all have the same value of Resource. Can contain for example information about the application that emits the record or about the infrastructure where the application runs. Data formats that represent this data model may be designed in a manner that allows the Resource field to be recorded only once per batch of log records that come from the same source. SHOULD follow OpenTelemetry semantic conventions for Resources. This field is optional.

Field: Attributes

Type: map<string, any>.

Description: Additional information about the specific event occurrence. Unlike the Resource field, which is fixed for a particular source, Attributes can vary for each occurrence of the event coming from the same source. Can contain information about the request context (other than TraceId/SpanId). SHOULD follow OpenTelemetry semantic conventions for Log Attributes or semantic conventions for Span Attributes. This field is optional.

Errors and Exceptions

Additional information about errors and/or exceptions that are associated with a log record MAY be included in the structured data in the Attributes section of the record. If included, they MUST follow the OpenTelemetry semantic conventions for exception-related attributes.

Example Log Records

Below are examples that show one possible representation of log records in JSON. These are just examples to help understand the data model. Don’t treat the examples as the way to represent this data model in JSON.

This document does not define the actual encoding and format of the log record representation. Format definitions will be done in separate OTEPs (e.g. the log records may be represented as msgpack, JSON, Protocol Buffer messages, etc).

Example 1

  "Timestamp": "1586960586000000000",
  "Attributes": {
    "http.status_code": 500,
    "http.url": "http://example.com",
    "my.custom.application.tag": "hello",
  "Resource": {
    "service.name": "donut_shop",
    "service.version": "2.0.0",
    "k8s.pod.uid": "1138528c-c36e-11e9-a1a7-42010a800198",
  "TraceId": "f4dbb3edd765f620", // this is a byte sequence
                                 // (hex-encoded in JSON)
  "SpanId": "43222c2d51a7abe3",
  "SeverityText": "INFO",
  "SeverityNumber": 9,
  "Body": "20200415T072306-0700 INFO I like donuts"

Example 2

  "Timestamp": "1586960586000000000",
  "Body": {
    "i": "am",
    "an": "event",
    "of": {
      "some": "complexity"

Example 3

   "Timestamp": "1586960586000000000",
      "http.user_agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.149 Safari/537.36",

Appendix A. Example Mappings

This section contains examples of mapping of other events and logs formats to this data model.

RFC5424 Syslog

Property Type Description Maps to Unified Model Field
TIMESTAMP Timestamp Time when an event occurred measured by the origin clock. Timestamp
SEVERITY enum Defines the importance of the event. Example: `Debug` Severity
FACILITY enum Describes where the event originated. A predefined list of Unix processes. Part of event source identity. Example: `mail system` Attributes["syslog.facility"]
VERSION number Meta: protocol version, orthogonal to the event. Attributes["syslog.version"]
HOSTNAME string Describes the location where the event originated. Possible values are FQDN, IP address, etc. Resource["host.hostname"]
APP-NAME string User-defined app name. Part of event source identity. Resource["service.name"]
PROCID string Not well defined. May be used as a meta field for protocol operation purposes or may be part of event source identity. Attributes["syslog.procid"]
MSGID string Defines the type of the event. Part of event source identity. Example: "TCPIN" Name
STRUCTURED-DATA array of maps of string to string A variety of use cases depending on the SDID: Can describe event source identity Can include data that describes particular occurrence of the event. Can be meta-information, e.g. quality of timestamp value. SDID origin.swVersion map to Resource["service.version"]

SDID origin.ip map to attribute[net.host.ip"]

Rest of SDIDs -> Attributes[“syslog.*"]

MSG string Free-form text message about the event. Typically human readable. Body

Windows Event Log

Property Type Description Maps to Unified Model Field
TimeCreated Timestamp The time stamp that identifies when the event was logged. Timestamp
Level enum Contains the severity level of the event. Severity
Computer string The name of the computer on which the event occurred. Resource["host.hostname"]
EventID uint The identifier that the provider used to identify the event. Name
Message string The message string. Body
Rest of the fields. any All other fields in the event. Attributes["winlog.*"]

SignalFx Events

Field Type Description Maps to Unified Model Field
Timestamp Timestamp Time when the event occurred measured by the origin clock. Timestamp
EventType string Short machine understandable string describing the event type. SignalFx specific concept. Non-namespaced. Example: k8s Event Reason field. Name
Category enum Describes where the event originated and why. SignalFx specific concept. Example: AGENT. Attributes["com.splunk.signalfx.event_category"]
Dimensions map<string, string> Helps to define the identity of the event source together with EventType and Category. Multiple occurrences of events coming from the same event source can happen across time and they all have the value of Dimensions. Resource
Properties map<string, any> Additional information about the specific event occurrence. Unlike Dimensions which are fixed for a particular event source, Properties can have different values for each occurrence of the event coming from the same event source. Attributes

Splunk HEC

We apply this mapping from HEC to the unified model:

Field Type Description Maps to Unified Model Field
time numeric, string The event time in epoch time format, in seconds. Timestamp
host string The host value to assign to the event data. This is typically the host name of the client that you are sending data from. Resource["host.name"]
source string The source value to assign to the event data. For example, if you are sending data from an app you are developing, you could set this key to the name of the app. Resource["com.splunk.source"]
sourcetype string The sourcetype value to assign to the event data. Resource["com.splunk.sourcetype"]
event any The JSON representation of the raw body of the event. It can be a string, number, string array, number array, JSON object, or a JSON array. Body
fields map<string, any> Specifies a JSON object that contains explicit custom fields. Attributes
index string The name of the index by which the event data is to be indexed. The index you specify here must be within the list of allowed indexes if the token has the indexes parameter set. Attributes["com.splunk.index"]

When mapping from the unified model to HEC, we apply this additional mapping:

Unified model element Type Description Maps to HEC
SeverityText string The severity of the event as a human-readable string. fields['otel.log.severity.text']
SeverityNumber string The severity of the event as a number. fields['otel.log.severity.number']
Name string Short event identifier that does not contain varying parts. fields['otel.log.name']
TraceId string Request trace id. fields['trace_id']
SpanId string Request span id. fields['span_id']
TraceFlags string W3C trace flags. fields['trace_flags']


Field Type Description Maps to Unified Model Field
Instant Timestamp Time when an event occurred measured by the origin clock. Timestamp
Level enum Log level. Severity
Message string Human readable message. Body
All other fields any Structured data. Attributes


Field Type Description Maps to Unified Model Field
ts Timestamp Time when an event occurred measured by the origin clock. Timestamp
level enum Logging level. Severity
caller string Calling function's filename and line number. Attributes, key=TBD
msg string Human readable message. Body
All other fields any Structured data. Attributes

Apache HTTP Server access log

Field Type Description Maps to Unified Model Field
%t Timestamp Time when an event occurred measured by the origin clock. Timestamp
%a string Client IP Attributes["net.peer.ip"]
%A string Server IP Attributes["net.host.ip"]
%h string Remote hostname. Attributes["net.peer.name"]
%m string The request method. Attributes["http.method"]
%v,%p,%U,%q string Multiple fields that can be composed into URL. Attributes["http.url"]
%>s string Response status. Attributes["http.status_code"]
All other fields any Structured data. Attributes, key=TBD

CloudTrail Log Event

Field Type Description Maps to Unified Model Field
eventTime string The date and time the request was made, in coordinated universal time (UTC). Timestamp
eventSource string The service that the request was made to. This name is typically a short form of the service name without spaces plus .amazonaws.com. Resource["service.name"]?
awsRegion string The AWS region that the request was made to, such as us-east-2. Resource["cloud.region"]
sourceIPAddress string The IP address that the request was made from. Resource["net.peer.ip"] or Resource["net.host.ip"]? TBD
errorCode string The AWS service error if the request returns an error. Name
errorMessage string If the request returns an error, the description of the error. Body
All other fields * Attributes["cloudtrail.*"]

Google Cloud Logging

Field Type Description Maps to Unified Model Field
timestamp string The time the event described by the log entry occurred. Timestamp
resource MonitoredResource The monitored resource that produced this log entry. Resource
log_name string The URL-encoded LOG_ID suffix of the log_name field identifies which log stream this entry belongs to. Name
json_payload google.protobuf.Struct The log entry payload, represented as a structure that is expressed as a JSON object. Body
proto_payload google.protobuf.Any The log entry payload, represented as a protocol buffer. Body
text_payload string The log entry payload, represented as a Unicode string (UTF-8). Body
severity LogSeverity The severity of the log entry. Severity
trace string The trace associated with the log entry, if any. TraceId
span_id string The span ID within the trace associated with the log entry. SpanId
labels map<string,string> A set of user-defined (key, value) data that provides additional information about the log entry. Attributes
http_request HttpRequest The HTTP request associated with the log entry, if any. Attributes[“google.httpRequest”]
All other fields Attributes[“google.*"]

Elastic Common Schema

Field Type Description Maps to Unified Model Field
@timestamp datetime Time the event was recorded Timestamp
message string Any type of message Body
labels key/value Arbitrary labels related to the event Attributes[*]
tags array of string List of values related to the event ?
trace.id string Trace ID TraceId
span.id* string Span ID SpanId
agent.ephemeral_id string Ephemeral ID created by agent **Resource
agent.id string Unique identifier of this agent **Resource
agent.name string Name given to the agent Resource["telemetry.sdk.name"]
agent.type string Type of agent Resource["telemetry.sdk.language"]
agent.version string Version of agent Resource["telemetry.sdk.version"]
source.ip, client.ip string The IP address that the request was made from. Attributes["net.peer.ip"] or Attributes["net.host.ip"]
cloud.account.id string ID of the account in the given cloud Resource["cloud.account.id"]
cloud.availability_zone string Availability zone in which this host is running. Resource["cloud.zone"]
cloud.instance.id string Instance ID of the host machine. **Resource
cloud.instance.name string Instance name of the host machine. **Resource
cloud.machine.type string Machine type of the host machine. **Resource
cloud.provider string Name of the cloud provider. Example values are aws, azure, gcp, or digitalocean. Resource["cloud.provider"]
cloud.region string Region in which this host is running. Resource["cloud.region"]
cloud.image.id* string Resource["host.image.name"]
container.id string Unique container id Resource["container.id"]
container.image.name string Name of the image the container was built on. Resource["container.image.name"]
container.image.tag Array of string Container image tags. **Resource
container.labels key/value Image labels. Attributes[*]
container.name string Container name. Resource["container.name"]
container.runtime string Runtime managing this container. Example: "docker" **Resource
destination.address string Destination address for the event Attributes["destination.address"]
error.code string Error code describing the error. Attributes["error.code"]
error.id string Unique identifier for the error. Attributes["error.id"]
error.message string Error message. Attributes["error.message"]
error.stack_trace string The stack trace of this error in plain text. Attributes["error.stack_trace]
host.architecture string Operating system architecture **Resource
host.domain string Name of the domain of which the host is a member.

For example, on Windows this could be the host’s Active Directory domain or NetBIOS domain name. For Linux this could be the domain of the host’s LDAP provider.

host.hostname string Hostname of the host.

It normally contains what the hostname command returns on the host machine.

host.id string Unique host id. Resource["host.id"]
host.ip Array of string Host IP Resource["host.ip"]
host.mac array of string MAC addresses of the host Resource["host.mac"]
host.name string Name of the host.

It may contain what hostname returns on Unix systems, the fully qualified, or a name specified by the user.

host.type string Type of host. Resource["host.type"]
host.uptime string Seconds the host has been up. ?
service.ephemeral_id string Ephemeral identifier of this service **Resource
service.id string Unique identifier of the running service. If the service is comprised of many nodes, the service.id should be the same for all nodes. **Resource
service.name string Name of the service data is collected from. Resource["service.name"]
service.node.name string Specific node serving that service Resource["service.instance.id"]
service.state string Current state of the service. Attributes["service.state"]
service.type string The type of the service data is collected from. **Resource
service.version string Version of the service the data was collected from. Resource["service.version"]

* Not yet formalized into ECS.

** A resource that doesn’t exist in the OpenTelemetry resource semantic convention.

This is a selection of the most relevant fields. See for the full reference for an exhaustive list.

Appendix B: SeverityNumber example mappings

Syslog WinEvtLog Log4j Zap java.util.logging SeverityNumber
Debug Verbose DEBUG Debug FINER DEBUG
Informational Information INFO Info INFO INFO
Notice INFO2
Warning Warning WARN Warn WARNING WARN
Critical Critical Dpanic ERROR2
Alert Panic ERROR3
Emergency FATAL Fatal FATAL