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ActiveMQ

Collect logs and metrics from ActiveMQ instances with Elastic Agent.

What is an Elastic integration?
Version
1.1.0 (View all)
Compatible Kibana version(s)
8.8.0 or higher
Supported Serverless project types

What's this?
Security
Observability
Subscription level
What's this?
Basic
Level of support
What's this?
Elastic

Overview

Apache ActiveMQ is the most popular open-source, multi-protocol, Java-based message broker. It supports industry-standard protocols, facilitating client choices across various languages and platforms, including JavaScript, C, C++, Python, .Net, and more. ActiveMQ enables seamless integration of multi-platform applications through the widely used AMQP protocol and allows efficient message exchange between web applications using STOMP over WebSockets. Additionally, it supports IoT device management via MQTT and provides flexibility to accommodate any messaging use case, supporting both existing JMS infrastructure and beyond.

Use the ActiveMQ integration to:

  • Collect logs related to the audit and ActiveMQ instance and collect metrics related to the broker, queue and topic.
  • Create visualizations to monitor, measure and analyze the usage trend and key data, and derive business insights.
  • Create alerts to reduce the MTTD and also the MTTR by referencing relevant logs when troubleshooting an issue.

Data streams

The ActiveMQ integration collects logs and metrics data.

Logs help you keep a record of events that happen on your machine. The Log data streams collected by ActiveMQ integration are audit and log so that users can keep track of the username, audit threads, messages, name of the caller issuing the logging requests, logging event etc.

Metrics give you insight into the statistics of the ActiveMQ. The Metric data streams collected by the ActiveMQ integration are broker, queue and topic so that the user can monitor and troubleshoot the performance of the ActiveMQ instance.

Data streams:

  • audit: Collects information related to the username, audit threads and messages.
  • broker: Collects information related to the statistics of enqueued and dequeued messages, consumers, producers and memory usage (broker, store, temp).
  • log: Collects information related to the startup and shutdown of the ActiveMQ application server, the deployment of new applications, or the failure of one or more subsystems.
  • queue: Collects information related to the statistics of queue name and size, exchanged messages and number of producers and consumers.
  • topic: Collects information related to the statistics of exchanged messages, consumers, producers and memory usage.

Note:

  • Users can monitor and see the log inside the ingested documents for ActiveMQ in the logs-* index pattern from Discover, and for metrics, the index pattern is metrics-*.

Compatibility

This integration has been tested against ActiveMQ 5.17.1 (independent from the operating system).

Prerequisites

You need Elasticsearch to store and search your data and Kibana to visualize and manage it. You can use our hosted Elasticsearch Service on Elastic Cloud, which is recommended or self-manage the Elastic Stack on your hardware.

Setup

For step-by-step instructions on how to set up an integration, see the Getting Started guide.

Supported Log Formats

Here are the supported log format for the Audit logs and ActiveMQ logs in the ActiveMQ instance,

Audit Logs

%-5p | %m | %t%n

Here is the breakdown of the pattern:

  • %-5p: This part represents the log level left-aligned with a width of 5 characters. The - signifies left alignment.

  • %m: This part represents the log message.

  • %t%n: This part represents the thread name (%t) followed by a newline (%n).

ActiveMQ Logs

%d | %-5p | %m | %c | %t%n%throwable{full}

Here is the breakdown of the pattern:

  • %d: This part represents the date and time of the log event in the ISO8601 format.

  • %-5p: This part represents the log level left-aligned with a width of 5 characters. The - signifies left alignment.

  • %m: This part represents the log message.

  • %c: This part represents the logger category (class name).

  • %t%n: This part represents the thread name (%t) followed by a newline (%n).

  • %throwable{full}: This part represents the full stack trace if an exception is attached to the log entry.

Validation

After the integration is successfully configured, clicking on the Assets tab of the ActiveMQ Integration should display a list of available dashboards. Click on the dashboard available for your configured data stream. It should be populated with the required data.

Troubleshooting

If host.ip is shown conflicted under logs-* data view, then this issue can be solved by reindexing the Audit and Log data stream's indices.

If host.ip is shown conflicted under metrics-* data view, then this issue can be solved by reindexing the Broker, Queue and Topic data stream's indices.

Logs

ActiveMQ Logs

These logs are System logs of ActiveMQ.

An example event for log looks as following:

{
    "@timestamp": "2022-06-24T12:54:26.345Z",
    "activemq": {
        "log": {
            "caller": "org.apache.activemq.broker.BrokerService",
            "thread": "main"
        }
    },
    "agent": {
        "ephemeral_id": "71698f60-6a6f-4b4e-ac2a-20c0b1805cff",
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "name": "docker-fleet-agent",
        "type": "filebeat",
        "version": "8.5.0"
    },
    "data_stream": {
        "dataset": "activemq.log",
        "namespace": "ep",
        "type": "logs"
    },
    "ecs": {
        "version": "8.5.1"
    },
    "elastic_agent": {
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "snapshot": false,
        "version": "8.5.0"
    },
    "event": {
        "agent_id_status": "verified",
        "dataset": "activemq.log",
        "ingested": "2022-12-09T04:19:37Z",
        "kind": "event",
        "module": "activemq",
        "type": [
            "info"
        ]
    },
    "host": {
        "name": "docker-fleet-agent"
    },
    "input": {
        "type": "log"
    },
    "log": {
        "file": {
            "path": "/tmp/service_logs/activemq.log"
        },
        "level": "INFO",
        "offset": 0
    },
    "message": "Using Persistence Adapter: KahaDBPersistenceAdapter[/softwares/apache-activemq-5.17.1/data/kahadb]",
    "tags": [
        "forwarded",
        "activemq-log"
    ]
}

Exported fields

FieldDescriptionType
@timestamp
Event timestamp.
date
activemq.log.caller
Name of the caller issuing the logging request (class or resource).
keyword
activemq.log.thread
Thread that generated the logging event.
keyword
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
error.message
Error message.
match_only_text
error.stack_trace
The stack trace of this error in plain text.
wildcard
error.stack_trace.text
Multi-field of error.stack_trace.
match_only_text
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.original
Raw text message of entire event. Used to demonstrate log integrity or where the full log message (before splitting it up in multiple parts) may be required, e.g. for reindex. This field is not indexed and doc_values are disabled. It cannot be searched, but it can be retrieved from _source. If users wish to override this and index this field, please see Field data types in the Elasticsearch Reference.
keyword
host.ip
Host ip addresses.
ip
input.type
Input type
keyword
log.file.path
Full path to the log file this event came from, including the file name. It should include the drive letter, when appropriate. If the event wasn't read from a log file, do not populate this field.
keyword
log.flags
Log flags
keyword
log.level
Original log level of the log event. If the source of the event provides a log level or textual severity, this is the one that goes in log.level. If your source doesn't specify one, you may put your event transport's severity here (e.g. Syslog severity). Some examples are warn, err, i, informational.
keyword
log.offset
Log offset
long
message
For log events the message field contains the log message, optimized for viewing in a log viewer. For structured logs without an original message field, other fields can be concatenated to form a human-readable summary of the event. If multiple messages exist, they can be combined into one message.
match_only_text
tags
List of keywords used to tag each event.
keyword

Audit Logs

In secured environments, it is required to log every user management action. ActiveMQ implements audit logging, which means that every management action made through JMX or Web Console management interface is logged and available for later inspection.

An example event for audit looks as following:

{
    "@timestamp": "2022-12-09T04:17:31.785Z",
    "activemq": {
        "audit": {
            "thread": "RMI TCP Connection(1)-127.0.0.1"
        }
    },
    "agent": {
        "ephemeral_id": "34b01ecd-6dff-4bc4-b2e2-a7388b1e20b2",
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "name": "docker-fleet-agent",
        "type": "filebeat",
        "version": "8.5.0"
    },
    "data_stream": {
        "dataset": "activemq.audit",
        "namespace": "ep",
        "type": "logs"
    },
    "ecs": {
        "version": "8.5.1"
    },
    "elastic_agent": {
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "snapshot": false,
        "version": "8.5.0"
    },
    "event": {
        "agent_id_status": "verified",
        "dataset": "activemq.audit",
        "ingested": "2022-12-09T04:17:32Z",
        "kind": "event",
        "module": "activemq",
        "type": [
            "info"
        ]
    },
    "host": {
        "name": "docker-fleet-agent"
    },
    "input": {
        "type": "log"
    },
    "log": {
        "file": {
            "path": "/tmp/service_logs/audit.log"
        },
        "level": "INFO",
        "offset": 0
    },
    "message": "called org.apache.activemq.broker.jmx.BrokerView.terminateJVM[0] on localhost at 24-06-2022 13:09:43,996",
    "tags": [
        "forwarded",
        "activemq-audit"
    ],
    "user": {
        "name": "anonymous"
    }
}

Exported fields

FieldDescriptionType
@timestamp
Event timestamp.
date
activemq.audit.thread
Thread that generated the logging event.
keyword
cloud.account.id
The cloud account or organization id used to identify different entities in a multi-tenant environment. Examples: AWS account id, Google Cloud ORG Id, or other unique identifier.
keyword
cloud.availability_zone
Availability zone in which this host is running.
keyword
cloud.image.id
Image ID for the cloud instance.
keyword
cloud.instance.id
Instance ID of the host machine.
keyword
cloud.instance.name
Instance name of the host machine.
keyword
cloud.machine.type
Machine type of the host machine.
keyword
cloud.project.id
Name of the project in Google Cloud.
keyword
cloud.provider
Name of the cloud provider. Example values are aws, azure, gcp, or digitalocean.
keyword
cloud.region
Region in which this host is running.
keyword
container.id
Unique container id.
keyword
container.image.name
Name of the image the container was built on.
keyword
container.labels
Image labels.
object
container.name
Container name.
keyword
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
error.message
Error message.
match_only_text
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.original
Raw text message of entire event. Used to demonstrate log integrity or where the full log message (before splitting it up in multiple parts) may be required, e.g. for reindex. This field is not indexed and doc_values are disabled. It cannot be searched, but it can be retrieved from _source. If users wish to override this and index this field, please see Field data types in the Elasticsearch Reference.
keyword
host.architecture
Operating system architecture.
keyword
host.containerized
If the host is a container.
boolean
host.domain
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.
keyword
host.hostname
Hostname of the host. It normally contains what the hostname command returns on the host machine.
keyword
host.id
Unique host id. As hostname is not always unique, use values that are meaningful in your environment. Example: The current usage of beat.name.
keyword
host.ip
Host ip addresses.
ip
host.mac
Host mac addresses.
keyword
host.name
Name of the host. It can contain what hostname returns on Unix systems, the fully qualified domain name, or a name specified by the user. The sender decides which value to use.
keyword
host.os.build
OS build information.
keyword
host.os.codename
OS codename, if any.
keyword
host.os.family
OS family (such as redhat, debian, freebsd, windows).
keyword
host.os.kernel
Operating system kernel version as a raw string.
keyword
host.os.name
Operating system name, without the version.
keyword
host.os.name.text
Multi-field of host.os.name.
text
host.os.platform
Operating system platform (such centos, ubuntu, windows).
keyword
host.os.version
Operating system version as a raw string.
keyword
host.type
Type of host. For Cloud providers this can be the machine type like t2.medium. If vm, this could be the container, for example, or other information meaningful in your environment.
keyword
input.type
Input type
keyword
log.file.path
Full path to the log file this event came from, including the file name. It should include the drive letter, when appropriate. If the event wasn't read from a log file, do not populate this field.
keyword
log.level
Original log level of the log event. If the source of the event provides a log level or textual severity, this is the one that goes in log.level. If your source doesn't specify one, you may put your event transport's severity here (e.g. Syslog severity). Some examples are warn, err, i, informational.
keyword
log.offset
Log offset
long
message
For log events the message field contains the log message, optimized for viewing in a log viewer. For structured logs without an original message field, other fields can be concatenated to form a human-readable summary of the event. If multiple messages exist, they can be combined into one message.
match_only_text
tags
List of keywords used to tag each event.
keyword
user.name
Short name or login of the user.
keyword
user.name.text
Multi-field of user.name.
match_only_text

Metrics

Broker Metrics

ActiveMQ brokers serve as implementations of the Java Messaging Service (JMS), a Java specification facilitating the seamless exchange of data between applications. Metrics provide insights into statistics such as enqueued and dequeued messages, as well as details on consumers, producers, and memory usage (broker, store, temp).

An example event for broker looks as following:

{
    "@timestamp": "2022-12-09T04:18:21.069Z",
    "activemq": {
        "broker": {
            "connections": {
                "count": 9
            },
            "consumers": {
                "count": 0
            },
            "mbean": "org.apache.activemq:brokerName=localhost,type=Broker",
            "memory": {
                "broker": {
                    "pct": 0
                },
                "store": {
                    "pct": 0
                },
                "temp": {
                    "pct": 0
                }
            },
            "messages": {
                "count": 9,
                "dequeue": {
                    "count": 0
                },
                "enqueue": {
                    "count": 20
                }
            },
            "name": "localhost",
            "producers": {
                "count": 0
            }
        }
    },
    "agent": {
        "ephemeral_id": "04f37e48-28d9-4b56-a226-c480f4a8a5ae",
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "name": "docker-fleet-agent",
        "type": "metricbeat",
        "version": "8.5.0"
    },
    "data_stream": {
        "dataset": "activemq.broker",
        "namespace": "ep",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.5.1"
    },
    "elastic_agent": {
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "snapshot": false,
        "version": "8.5.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": [
            "web"
        ],
        "dataset": "activemq.broker",
        "duration": 22293625,
        "ingested": "2022-12-09T04:18:22Z",
        "kind": "metric",
        "module": "activemq",
        "type": [
            "info"
        ]
    },
    "host": {
        "architecture": "x86_64",
        "containerized": false,
        "hostname": "docker-fleet-agent",
        "id": "66392b0697b84641af8006d87aeb89f1",
        "ip": [
            "172.18.0.7"
        ],
        "mac": [
            "02-42-AC-12-00-07"
        ],
        "name": "docker-fleet-agent",
        "os": {
            "codename": "focal",
            "family": "debian",
            "kernel": "5.15.49-linuxkit",
            "name": "Ubuntu",
            "platform": "ubuntu",
            "type": "linux",
            "version": "20.04.5 LTS (Focal Fossa)"
        }
    },
    "metricset": {
        "name": "broker",
        "period": 10000
    },
    "service": {
        "address": "http://elastic-package-service-activemq-1:8161/api/jolokia/%3FignoreErrors=true\u0026canonicalNaming=false",
        "type": "activemq"
    },
    "tags": [
        "activemq-broker"
    ]
}

Exported fields

FieldDescriptionTypeUnitMetric Type
@timestamp
Event timestamp.
date
activemq.broker.connections.count
Total number of connections.
long
counter
activemq.broker.consumers.count
Number of message consumers.
long
gauge
activemq.broker.mbean
MBean that this event is related to.
keyword
activemq.broker.memory.broker.pct
The percentage of the memory limit used.
float
percent
gauge
activemq.broker.memory.store.pct
Percent of store limit used.
float
percent
gauge
activemq.broker.memory.temp.pct
The percentage of the temp usage limit used.
float
percent
gauge
activemq.broker.messages.count
Number of unacknowledged messages on the broker.
long
gauge
activemq.broker.messages.dequeue.count
Number of messages that have been acknowledged on the broker.
long
gauge
activemq.broker.messages.enqueue.count
Number of messages that have been sent to the destination.
long
gauge
activemq.broker.name
Broker name.
keyword
activemq.broker.producers.count
Number of message producers active on destinations on the broker.
long
gauge
agent.id
Unique identifier of this agent (if one exists). Example: For Beats this would be beat.id.
keyword
cloud.account.id
The cloud account or organization id used to identify different entities in a multi-tenant environment. Examples: AWS account id, Google Cloud ORG Id, or other unique identifier.
keyword
cloud.availability_zone
Availability zone in which this host, resource, or service is located.
keyword
cloud.instance.id
Instance ID of the host machine.
keyword
cloud.provider
Name of the cloud provider. Example values are aws, azure, gcp, or digitalocean.
keyword
cloud.region
Region in which this host, resource, or service is located.
keyword
container.id
Unique container id.
keyword
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
error.message
Error message.
match_only_text
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.duration
Duration of the event in nanoseconds. If event.start and event.end are known this value should be the difference between the end and start time.
long
event.ingested
Timestamp when an event arrived in the central data store. This is different from @timestamp, which is when the event originally occurred. It's also different from event.created, which is meant to capture the first time an agent saw the event. In normal conditions, assuming no tampering, the timestamps should chronologically look like this: @timestamp < event.created < event.ingested.
date
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
host.ip
Host ip addresses.
ip
host.name
Name of the host. It can contain what hostname returns on Unix systems, the fully qualified domain name, or a name specified by the user. The sender decides which value to use.
keyword
service.address
Address where data about this service was collected from. This should be a URI, network address (ipv4:port or [ipv6]:port) or a resource path (sockets).
keyword
service.type
The type of the service data is collected from. The type can be used to group and correlate logs and metrics from one service type. Example: If logs or metrics are collected from Elasticsearch, service.type would be elasticsearch.
keyword
tags
List of keywords used to tag each event.
keyword

Queue Metrics

Queues are FIFO (first-in, first-out) pipelines of messages produced and consumed by brokers and clients. Producers create messages and push them onto these queues. Then, those messages are polled and collected by consumer applications, one message at a time. Metrics show statistics of exchanged messages, consumers, producers and memory usage.

An example event for queue looks as following:

{
    "@timestamp": "2022-12-09T04:20:29.290Z",
    "activemq": {
        "queue": {
            "consumers": {
                "count": 0
            },
            "mbean": "org.apache.activemq:brokerName=localhost,destinationName=TEST,destinationType=Queue,type=Broker",
            "memory": {
                "broker": {
                    "pct": 0
                }
            },
            "messages": {
                "dequeue": {
                    "count": 0
                },
                "dispatch": {
                    "count": 0
                },
                "enqueue": {
                    "count": 8,
                    "time": {
                        "avg": 0,
                        "max": 0,
                        "min": 0
                    }
                },
                "expired": {
                    "count": 0
                },
                "inflight": {
                    "count": 0
                },
                "size": {
                    "avg": 1035
                }
            },
            "name": "TEST",
            "producers": {
                "count": 0
            },
            "size": 8
        }
    },
    "agent": {
        "ephemeral_id": "cf2dc538-c1ce-41e4-8c82-90a77985107b",
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "name": "docker-fleet-agent",
        "type": "metricbeat",
        "version": "8.5.0"
    },
    "data_stream": {
        "dataset": "activemq.queue",
        "namespace": "ep",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.5.1"
    },
    "elastic_agent": {
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "snapshot": false,
        "version": "8.5.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": [
            "web"
        ],
        "dataset": "activemq.queue",
        "duration": 21893167,
        "ingested": "2022-12-09T04:20:30Z",
        "kind": "metric",
        "module": "activemq",
        "type": [
            "info"
        ]
    },
    "host": {
        "architecture": "x86_64",
        "containerized": false,
        "hostname": "docker-fleet-agent",
        "id": "66392b0697b84641af8006d87aeb89f1",
        "ip": [
            "172.18.0.7"
        ],
        "mac": [
            "02-42-AC-12-00-07"
        ],
        "name": "docker-fleet-agent",
        "os": {
            "codename": "focal",
            "family": "debian",
            "kernel": "5.15.49-linuxkit",
            "name": "Ubuntu",
            "platform": "ubuntu",
            "type": "linux",
            "version": "20.04.5 LTS (Focal Fossa)"
        }
    },
    "metricset": {
        "name": "queue",
        "period": 10000
    },
    "service": {
        "address": "http://elastic-package-service-activemq-1:8161/api/jolokia/%3FignoreErrors=true\u0026canonicalNaming=false",
        "type": "activemq"
    },
    "tags": [
        "activemq-queue"
    ]
}

Exported fields

FieldDescriptionTypeUnitMetric Type
@timestamp
Event timestamp.
date
activemq.queue.consumers.count
Number of consumers subscribed to this destination.
long
gauge
activemq.queue.mbean
MBean that this event is related to.
keyword
activemq.queue.memory.broker.pct
Percent of memory limit used.
float
percent
gauge
activemq.queue.messages.dequeue.count
Number of messages that has been acknowledged (and removed) from the destination.
long
gauge
activemq.queue.messages.dispatch.count
Number of messages that has been delivered to consumers, including those not acknowledged.
long
gauge
activemq.queue.messages.enqueue.count
Number of messages that have been sent to the destination.
long
gauge
activemq.queue.messages.enqueue.time.avg
Average time a message was held on this destination.
double
gauge
activemq.queue.messages.enqueue.time.max
The longest time a message was held on this destination.
long
gauge
activemq.queue.messages.enqueue.time.min
The shortest time a message was held on this destination.
long
gauge
activemq.queue.messages.expired.count
Number of messages that have been expired.
long
gauge
activemq.queue.messages.inflight.count
Number of messages that have been dispatched to consumers but not acknowledged by consumers.
long
gauge
activemq.queue.messages.size.avg
Average message size on this destination.
long
gauge
activemq.queue.name
Queue name.
keyword
activemq.queue.producers.count
Number of producers attached to this destination.
long
gauge
activemq.queue.size
Queue size.
long
gauge
agent.id
Unique identifier of this agent (if one exists). Example: For Beats this would be beat.id.
keyword
cloud.account.id
The cloud account or organization id used to identify different entities in a multi-tenant environment. Examples: AWS account id, Google Cloud ORG Id, or other unique identifier.
keyword
cloud.availability_zone
Availability zone in which this host, resource, or service is located.
keyword
cloud.instance.id
Instance ID of the host machine.
keyword
cloud.provider
Name of the cloud provider. Example values are aws, azure, gcp, or digitalocean.
keyword
cloud.region
Region in which this host, resource, or service is located.
keyword
container.id
Unique container id.
keyword
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
error.message
Error message.
match_only_text
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.duration
Duration of the event in nanoseconds. If event.start and event.end are known this value should be the difference between the end and start time.
long
event.ingested
Timestamp when an event arrived in the central data store. This is different from @timestamp, which is when the event originally occurred. It's also different from event.created, which is meant to capture the first time an agent saw the event. In normal conditions, assuming no tampering, the timestamps should chronologically look like this: @timestamp < event.created < event.ingested.
date
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
host.ip
Host ip addresses.
ip
host.name
Name of the host. It can contain what hostname returns on Unix systems, the fully qualified domain name, or a name specified by the user. The sender decides which value to use.
keyword
service.address
Address where data about this service was collected from. This should be a URI, network address (ipv4:port or [ipv6]:port) or a resource path (sockets).
keyword
service.type
The type of the service data is collected from. The type can be used to group and correlate logs and metrics from one service type. Example: If logs or metrics are collected from Elasticsearch, service.type would be elasticsearch.
keyword
tags
List of keywords used to tag each event.
keyword

Topic Metrics

Topics are subscription-based message broadcast channels. When a producing application sends a message, multiple recipients who are 'subscribed' to that topic receive a broadcast of the message. Metrics show statistics of exchanged messages, consumers, producers and memory usage.

An example event for topic looks as following:

{
    "@timestamp": "2022-12-09T04:21:20.298Z",
    "activemq": {
        "topic": {
            "consumers": {
                "count": 0
            },
            "mbean": "org.apache.activemq:brokerName=localhost,destinationName=ActiveMQ.Advisory.MasterBroker,destinationType=Topic,type=Broker",
            "memory": {
                "broker": {
                    "pct": 0
                }
            },
            "messages": {
                "dequeue": {
                    "count": 0
                },
                "dispatch": {
                    "count": 0
                },
                "enqueue": {
                    "count": 1,
                    "time": {
                        "avg": 0,
                        "max": 0,
                        "min": 0
                    }
                },
                "expired": {
                    "count": 0
                },
                "inflight": {
                    "count": 0
                },
                "size": {
                    "avg": 1024
                }
            },
            "name": "ActiveMQ.Advisory.MasterBroker",
            "producers": {
                "count": 0
            }
        }
    },
    "agent": {
        "ephemeral_id": "cf2dc538-c1ce-41e4-8c82-90a77985107b",
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "name": "docker-fleet-agent",
        "type": "metricbeat",
        "version": "8.5.0"
    },
    "data_stream": {
        "dataset": "activemq.topic",
        "namespace": "ep",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.5.1"
    },
    "elastic_agent": {
        "id": "46343e0c-0d8c-464b-a216-cacf63027d6f",
        "snapshot": false,
        "version": "8.5.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": [
            "web"
        ],
        "dataset": "activemq.topic",
        "duration": 18261916,
        "ingested": "2022-12-09T04:21:21Z",
        "kind": "metric",
        "module": "activemq",
        "type": [
            "info"
        ]
    },
    "host": {
        "architecture": "x86_64",
        "containerized": false,
        "hostname": "docker-fleet-agent",
        "id": "66392b0697b84641af8006d87aeb89f1",
        "ip": [
            "172.18.0.7"
        ],
        "mac": [
            "02-42-AC-12-00-07"
        ],
        "name": "docker-fleet-agent",
        "os": {
            "codename": "focal",
            "family": "debian",
            "kernel": "5.15.49-linuxkit",
            "name": "Ubuntu",
            "platform": "ubuntu",
            "type": "linux",
            "version": "20.04.5 LTS (Focal Fossa)"
        }
    },
    "metricset": {
        "name": "topic",
        "period": 10000
    },
    "service": {
        "address": "http://elastic-package-service-activemq-1:8161/api/jolokia/%3FignoreErrors=true\u0026canonicalNaming=false",
        "type": "activemq"
    },
    "tags": [
        "activemq-topic"
    ]
}

Exported fields

FieldDescriptionTypeUnitMetric Type
@timestamp
Event timestamp.
date
activemq.topic.consumers.count
Number of consumers subscribed to this destination.
long
gauge
activemq.topic.mbean
MBean that this event is related to.
keyword
activemq.topic.memory.broker.pct
Percent of memory limit used.
float
percent
gauge
activemq.topic.messages.dequeue.count
Number of messages that has been acknowledged (and removed) from the destination.
long
gauge
activemq.topic.messages.dispatch.count
Number of messages that has been delivered to consumers, including those not acknowledged.
long
gauge
activemq.topic.messages.enqueue.count
Number of messages that have been sent to the destination.
long
gauge
activemq.topic.messages.enqueue.time.avg
Average time a message was held on this destination.
double
gauge
activemq.topic.messages.enqueue.time.max
The longest time a message was held on this destination.
long
gauge
activemq.topic.messages.enqueue.time.min
The shortest time a message was held on this destination.
long
gauge
activemq.topic.messages.expired.count
Number of messages that have been expired.
long
gauge
activemq.topic.messages.inflight.count
Number of messages that have been dispatched to, but not acknowledged by, consumers.
long
gauge
activemq.topic.messages.size.avg
Average message size on this destination.
long
gauge
activemq.topic.name
Topic name
keyword
activemq.topic.producers.count
Number of producers attached to this destination.
long
gauge
agent.id
Unique identifier of this agent (if one exists). Example: For Beats this would be beat.id.
keyword
cloud.account.id
The cloud account or organization id used to identify different entities in a multi-tenant environment. Examples: AWS account id, Google Cloud ORG Id, or other unique identifier.
keyword
cloud.availability_zone
Availability zone in which this host, resource, or service is located.
keyword
cloud.instance.id
Instance ID of the host machine.
keyword
cloud.provider
Name of the cloud provider. Example values are aws, azure, gcp, or digitalocean.
keyword
cloud.region
Region in which this host, resource, or service is located.
keyword
container.id
Unique container id.
keyword
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
error.message
Error message.
match_only_text
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.duration
Duration of the event in nanoseconds. If event.start and event.end are known this value should be the difference between the end and start time.
long
event.ingested
Timestamp when an event arrived in the central data store. This is different from @timestamp, which is when the event originally occurred. It's also different from event.created, which is meant to capture the first time an agent saw the event. In normal conditions, assuming no tampering, the timestamps should chronologically look like this: @timestamp < event.created < event.ingested.
date
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
host.ip
Host ip addresses.
ip
host.name
Name of the host. It can contain what hostname returns on Unix systems, the fully qualified domain name, or a name specified by the user. The sender decides which value to use.
keyword
service.address
Address where data about this service was collected from. This should be a URI, network address (ipv4:port or [ipv6]:port) or a resource path (sockets).
keyword
service.type
The type of the service data is collected from. The type can be used to group and correlate logs and metrics from one service type. Example: If logs or metrics are collected from Elasticsearch, service.type would be elasticsearch.
keyword
tags
List of keywords used to tag each event.
keyword

Changelog

VersionDetailsKibana version(s)

1.1.0

Enhancement View pull request
Enable 'secret' for the sensitive fields, supported from 8.12.

8.8.0 or higher

1.0.0

Enhancement View pull request
Make ActiveMQ GA.

8.8.0 or higher

0.16.1

Bug fix View pull request
Update link to the correct reindexing procedure.

—

0.16.0

Enhancement View pull request
Update README to use documentation guidelines.

—

0.15.0

Enhancement View pull request
Add metric_type and support tooltip for period.

—

0.14.2

Bug fix View pull request
Resolve host.ip field conflict.

—

0.14.1

Bug fix View pull request
Add null and ignore_missing check to handle event.original field.

—

0.14.0

Enhancement View pull request
Update the package format_version to 3.0.0.

—

0.13.1

Bug fix View pull request
Remove forwarded tag from metrics data streams.

—

0.13.0

Enhancement View pull request
Revert changes to permissions to reroute events to logs-- for log datastream

—

0.12.0

Enhancement View pull request
Enable time series data streams for the metrics datasets. This dramatically reduces storage for metrics and is expected to progressively improve query performance. For more details, see https://www.elastic.co/guide/en/elasticsearch/reference/current/tsds.html.

—

0.11.0

Enhancement View pull request
Add metric_type mappings for broker, queue and topic datastreams.

—

0.10.0

Enhancement View pull request
Add permissions to reroute events to logs-- for log datastream

—

0.9.2

Enhancement View pull request
Added dimension fields for topic datastream for TSDB enablement

—

0.9.1

Enhancement View pull request
Added dimension fields for queue datastream for TSDB enablement

—

0.9.0

Enhancement View pull request
Added dimension fields for broker datastream for TSDB enablement

—

0.8.0

Enhancement View pull request
Rename ownership from obs-service-integrations to obs-infraobs-integrations

—

0.7.0

Enhancement View pull request
Migrate visualizations to lens.

—

0.6.1

Enhancement View pull request
Added categories and/or subcategories.

—

0.6.0

Enhancement View pull request
Update ECS version to 8.5.1.

—

0.5.0

Enhancement View pull request
Added infrastructure category.

—

0.4.3

Enhancement View pull request
Add additional ECS fields.

—

0.4.2

Bug fix View pull request
Remove unnecessary fields from fields.yml

—

0.4.1

Enhancement View pull request
fixed line break in readme

—

0.4.0

Enhancement View pull request
Update the package to follow the best practices, fix minor bugs, update the system tests as per the 5.17.1 version of ActiveMQ, update dashboards

—

0.3.1

Enhancement View pull request
Add documentation for multi-fields

—

0.3.0

Enhancement View pull request
Support Kibana 8.0

—

0.2.0

Enhancement View pull request
Uniform with guidelines

—

0.1.0

Enhancement View pull request
Update to ECS 1.12.0

—

0.0.1

Enhancement View pull request
initial release

—

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