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Prometheus

Collect metrics from Prometheus servers with Elastic Agent.

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

What's this?
Security
Observability
Subscription level
What's this?
Basic

This integration can collect metrics from:

Metrics

Prometheus Exporters (Collectors)

The Prometheus integration collector dataset connects to the Prometheus server and pulls metrics using either the /metrics endpoint or the Prometheus Federation API.

Scraping from a Prometheus exporter

To scrape metrics from a Prometheus exporter, configure the hosts setting to it. The path to retrieve the metrics from (/metrics by default) can be configured with Metrics Path.

Histograms and types

Use Types parameter (default: true) enables a different layout for metrics storage, leveraging Elasticsearch types, including histograms.

Rate Counters parameter (default: true) enables calculating a rate out of Prometheus counters. When enabled, Metricbeat stores the counter increment since the last collection. This metric should make some aggregations easier and with better performance. This parameter can only be enabled in combination with Use Types.

When Use Types and Rate Counters are enabled, metrics are stored like this:

{
  "_index": ".ds-metrics-prometheus.collector-default-000001",
  "_id": "JlK9AHMBeyDc0b9rCwVA",
  "_version": 1,
  "_score": null,
  "_source": {
    "@timestamp": "2020-06-29T15:40:55.028Z",
    "prometheus": {
      "labels": {
        "slice": "inner_eval",
        "instance": "localhost:9090",
        "job": "prometheus"
      },
      "prometheus_engine_query_duration_seconds_sum": {
        "counter": 0.002697546,
        "rate": 0.00006945900000000001
      },
      "prometheus_engine_query_duration_seconds_count": {
        "rate": 1,
        "counter": 37
      }
    },
    "dataset": {
      "type": "metrics",
      "name": "prometheus.collector",
      "namespace": "default"
    },
    "agent": {
      "ephemeral_id": "98420e91-ee6d-4883-8ad3-02fa8d47f5c1",
      "id": "9fc3e975-6789-4738-a11a-ba7108b0a92c",
      "name": "minikube",
      "type": "metricbeat",
      "version": "8.0.0"
    },
    "ecs": {
      "version": "1.5.0"
    },
    "event": {
      "module": "prometheus",
      "duration": 15397122,
      "dataset": "prometheus.collector"
    },
    "metricset": {
      "period": 10000,
      "name": "collector"
    },
    "service": {
      "address": "localhost:9090",
      "type": "prometheus"
    },
    "stream": {
      "namespace": "default",
      "type": "metrics",
      "dataset": "prometheus.collector"
    },
    "host": {},
  },
  "fields": {
    "@timestamp": [
      "2020-06-29T15:40:55.028Z"
    ]
  },
  "highlight": {
    "event.dataset": [
      "@kibana-highlighted-field@prometheus.collector@/kibana-highlighted-field@"
    ]
  },
  "sort": [
    1593445255028
  ]
}

Scraping all metrics from a Prometheus server

We recommend using the Remote Write dataset for this, and make Prometheus push metrics to Agent.

Filtering metrics

In order to filter out/in metrics one can make use of Metrics Filters Include, Metrics Filters Exclude settings:

Metrics Filters Include: ["node_filesystem_*"]
Metrics Filters Exclude: ["node_filesystem_device_*"]

The configuration above will include only metrics that match node_filesystem_* pattern and do not match node_filesystem_device_*.

To keep only specific metrics, anchor the start and the end of the regexp of each metric:

  • the caret ^ matches the beginning of a text or line,
  • the dollar sign $ matches the end of a text.
Metrics Filters Include: ["^node_network_net_dev_group$", "^node_network_up$"]

An example event for collector looks as following:

{
    "@timestamp": "2022-09-21T13:53:53.737Z",
    "ecs": {
        "version": "8.0.0"
    },
    "service": {
        "address": "http://prometheus-server-server:80/metrics",
        "type": "prometheus"
    },
    "data_stream": {
        "namespace": "default",
        "type": "metrics",
        "dataset": "prometheus.collector"
    },
    "elastic_agent": {
        "id": "68e3d23a-08cd-4477-924b-25f491194aba",
        "version": "8.4.0",
        "snapshot": true
    },
    "host": {},
    "metricset": {
        "period": 10000,
        "name": "collector"
    },
    "prometheus": {
        "prometheus_target_sync_length_seconds": {
            "value": 0.000103602
        },
        "labels": {
            "scrape_job": "kubernetes-services",
            "instance": "prometheus-server-server:80",
            "quantile": "0.5",
            "job": "prometheus"
        }
    },
    "event": {
        "duration": 10509824,
        "agent_id_status": "verified",
        "ingested": "2022-09-21T13:53:54Z",
        "module": "prometheus",
        "dataset": "prometheus.collector"
    }
}

The fields reported are:

Exported fields

FieldDescriptionTypeMetric Type
@timestamp
Event timestamp.
date
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 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
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.module
Event module.
constant_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
prometheus.*.counter
Prometheus counter metric
object
counter
prometheus.*.histogram
Prometheus histogram metric
object
prometheus.*.rate
Prometheus rated counter metric
object
gauge
prometheus.*.value
Prometheus gauge metric
object
gauge
prometheus.labels.*
Prometheus metric labels
object
prometheus.labels_fingerprint
Autogenerated ID representing the fingerprint of labels object
keyword
prometheus.metrics.*
Prometheus metric
object
gauge
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

Prometheus Server Remote-Write

The Prometheus remote_write can receive metrics from a Prometheus server that has configured remote_write setting accordingly, for instance:

remote_write:
  - url: "http://localhost:9201/write"

In Kuberneter additionally should be created a Service resource:

---
apiVersion: v1
kind: Service
metadata:
  name: elastic-agent
  namespace: kube-system
  labels:
    app: elastic-agent
spec:
  ports:
    - port: 9201
      protocol: TCP
      targetPort: 9201
  selector:
    app: elastic-agent
  sessionAffinity: None
  type: ClusterIP

This Service can be used as a remote_write.url in Prometheus configuration:

remote_write:
  - url: "http://elastic-agent.kube-system:9201/write"

TIP: In order to assure the health of the whole queue, the following configuration parameters should be considered:

  • max_shards: Sets the maximum number of parallelism with which Prometheus will try to send samples to Metricbeat. It is recommended that this setting should be equal to the number of cores of the machine where Metricbeat runs. Metricbeat can handle connections in parallel and hence setting max_shards to the number of parallelism that Metricbeat can actually achieve is the optimal queue configuration.
  • max_samples_per_send: Sets the number of samples to batch together for each send. Recommended values are between 100 (default) and 1000. Having a bigger batch can lead to improved throughput and in more efficient storage since Metricbeat groups metrics with the same labels into same event documents. However this will increase the memory usage of Metricbeat.
  • capacity: It is recommended to set capacity to 3-5 times max_samples_per_send. Capacity sets the number of samples that are queued in memory per shard, and hence capacity should be high enough so as to be able to cover max_samples_per_send.

TIP: To limit amount of samples that are sent by the Prometheus Server can be used write_relabel_configs configuration. It is a relabeling, that applies to samples before sending them to the remote endpoint. Example:

remote_write:
  - url: "http://localhost:9201/write"
    write_relabel_configs:
      - source_labels: [job]
        regex: 'prometheus'
        action: keep

Metrics sent to the http endpoint will be put by default under the prometheus. prefix with their labels under prometheus.labels. A basic configuration would look like:

host: "localhost"
port: "9201"

Also consider using secure settings for the server, configuring the module with TLS/SSL as shown:

host: "localhost"
ssl.certificate: "/etc/pki/server/cert.pem"
ssl.key: "/etc/pki/server/cert.key"
port: "9201"

and on Prometheus side:

remote_write:
  - url: "https://localhost:9201/write"
    tls_config:
        cert_file: "/etc/prometheus/my_key.pem"
        key_file: "/etc/prometheus/my_key.key"
        # Disable validation of the server certificate.
        #insecure_skip_verify: true

An example event for remote_write looks as following:

{
    "agent": {
        "name": "kind-control-plane",
        "id": "af0df4c2-33b7-41fd-8eb5-573376996db2",
        "ephemeral_id": "5c3d912b-9bf3-4747-b784-1f7c275a5979",
        "type": "metricbeat",
        "version": "8.4.0"
    },
    "@timestamp": "2022-09-22T12:23:35.757Z",
    "ecs": {
        "version": "8.0.0"
    },
    "service": {
        "type": "prometheus"
    },
    "data_stream": {
        "namespace": "default",
        "type": "metrics",
        "dataset": "prometheus.remote_write"
    },
    "elastic_agent": {
        "id": "af0df4c2-33b7-41fd-8eb5-573376996db2",
        "version": "8.4.0",
        "snapshot": true
    },
    "host": {},
    "metricset": {
        "name": "remote_write"
    },
    "prometheus": {
        "node_cpu_guest_seconds_total": {
            "rate": 0,
            "counter": 0
        },
        "node_cpu_seconds_total": {
            "rate": 0,
            "counter": 2284.68
        },
        "labels": {
            "app": "prometheus",
            "app_kubernetes_io_managed_by": "Helm",
            "instance": "172.19.0.2:9100",
            "release": "prometheus-server",
            "cpu": "5",
            "heritage": "Helm",
            "mode": "user",
            "node": "kind-control-plane",
            "component": "node-exporter",
            "service": "prometheus-server-node-exporter",
            "namespace": "kube-system",
            "job": "kubernetes-service-endpoints",
            "chart": "prometheus-15.10.1"
        }
    },
    "event": {
        "agent_id_status": "verified",
        "ingested": "2022-09-22T12:24:16Z",
        "module": "prometheus",
        "dataset": "prometheus.remote_write"
    }
}

The fields reported are:

Exported fields

FieldDescriptionTypeMetric Type
@timestamp
Event timestamp.
date
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 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
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.module
Event module.
constant_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
prometheus.*.counter
Prometheus counter metric
object
counter
prometheus.*.histogram
Prometheus histogram metric
object
prometheus.*.rate
Prometheus rated counter metric
object
gauge
prometheus.*.value
Prometheus gauge metric
object
gauge
prometheus.labels.*
Prometheus metric labels
object
prometheus.labels_fingerprint
Autogenerated ID representing the fingerprint of all labels and the list of metrics names
keyword
prometheus.metrics.*
Prometheus metric
object
gauge
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

Histograms and types

use_types parameter (default: true) enables a different layout for metrics storage, leveraging Elasticsearch types, including histograms.

rate_counters parameter (default: true) enables calculating a rate out of Prometheus counters. When enabled, Metricbeat stores the counter increment since the last collection. This metric should make some aggregations easier and with better performance. This parameter can only be enabled in combination with use_types.

When use_types and rate_counters are enabled, metrics are stored like this:

{
    "prometheus": {
        "labels": {
            "instance": "172.27.0.2:9090",
            "job": "prometheus"
        },
        "prometheus_target_interval_length_seconds_count": {
            "counter": 1,
            "rate": 0
        },
        "prometheus_target_interval_length_seconds_sum": {
            "counter": 15.000401344,
            "rate": 0
        }
        "prometheus_tsdb_compaction_chunk_range_seconds_bucket": {
            "histogram": {
                "values": [50, 300, 1000, 4000, 16000],
                "counts": [10, 2, 34, 7]
            }
        }
    },
}

Types' patterns

Unlike collector metricset, remote_write receives metrics in raw format from the prometheus server. In this, the module has to internally use a heuristic in order to identify efficiently the type of each raw metric. For these purpose some name patterns are used in order to identify the type of each metric. The default patterns are the following:

. _total suffix: the metric is of Counter type . _sum suffix: the metric is of Counter type . _count suffix: the metric is of Counter type . _bucket suffix and le in labels: the metric is of Histogram type

Everything else is handled as a Gauge. In addition there is no special handling for Summaries so it is expected that Summary's quantiles are handled as Gauges and Summary's sum and count as Counters.

Users have the flexibility to add their own patterns using the following configuration:

types_patterns:
    counter_patterns: ["_my_counter_suffix"]
    histogram_patterns: ["_my_histogram_suffix"]

The configuration above will consider metrics with names that match _my_counter_suffix as Counters and those that match _my_histogram_suffix (and have le in their labels) as Histograms.

To match only specific metrics, anchor the start and the end of the regexp of each metric:

  • the caret ^ matches the beginning of a text or line,
  • the dollar sign $ matches the end of a text.
types_patterns:
    histogram_patterns: ["^my_histogram_metric$"]

Note that when using types_patterns, the provided patterns have higher priority than the default patterns. For instance if _histogram_total is a defined histogram pattern, then a metric like network_bytes_histogram_total will be handled as a histogram, even if it has the suffix _total which is a default pattern for counters.

Prometheus Queries (PromQL)

The Prometheus query dataset executes specific Prometheus queries against Promethes Query API.

Instant queries

The following configuration performs an instant query for up metric at a single point in time:

queries:
- name: 'up'
  path: '/api/v1/query'
  params:
    query: "up"

More complex PromQL expressions can also be used like the following one which calculates the per-second rate of HTTP requests as measured over the last 5 minutes.

queries:
- name: "rate_http_requests_total"
  path: "/api/v1/query"
  params:
    query: "rate(prometheus_http_requests_total[5m])"

Range queries

The following example evaluates the expression up over a 30-second range with a query resolution of 15 seconds:

queries:
- name: "up_master"
  path: "/api/v1/query_range"
  params:
    query: "up{node='master01'}"
    start: "2019-12-20T23:30:30.000Z"
    end: "2019-12-21T23:31:00.000Z"
    step: 15s

An example event for query looks as following:

{
    "agent": {
        "name": "kind-control-plane",
        "id": "68e3d23a-08cd-4477-924b-25f491194aba",
        "type": "metricbeat",
        "ephemeral_id": "63ab98c3-c4ae-4a30-84f9-9a2d7f459728",
        "version": "8.4.0"
    },
    "@timestamp": "2022-09-21T14:06:49.000Z",
    "ecs": {
        "version": "8.0.0"
    },
    "service": {
        "address": "http://prometheus-server-server:80",
        "type": "prometheus"
    },
    "data_stream": {
        "namespace": "default",
        "type": "metrics",
        "dataset": "prometheus.query"
    },
    "elastic_agent": {
        "id": "68e3d23a-08cd-4477-924b-25f491194aba",
        "version": "8.4.0",
        "snapshot": true
    },
    "host": {},
    "metricset": {
        "period": 10000,
        "name": "query"
    },
    "prometheus": {
        "query": {
            "instant_vector": 0.7838951248394681
        },
        "labels": {}
    },
    "event": {
        "duration": 1153570,
        "agent_id_status": "verified",
        "ingested": "2022-09-21T14:06:50Z",
        "module": "prometheus",
        "dataset": "prometheus.query"
    }
}

The fields reported are:

Exported fields

FieldDescriptionTypeMetric Type
@timestamp
Event timestamp.
date
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 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
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.module
Event module.
constant_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
prometheus.labels.*
Prometheus metric labels
object
prometheus.labels_fingerprint
Autogenerated ID representing the fingerprint of labels object and includes query name
keyword
prometheus.query.*
Prometheus value resulted from PromQL
object
gauge
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

Dashboard

Prometheus integration is shipped including default overview dashboard. Default dashboard works only for remote_write datastream and collector darastream, if metrics are scraped from the Prometheus server metrics endpoint.

Changelog

VersionDetailsKibana version(s)

1.14.0

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

8.9.0 or higher

1.13.1

Enhancement View pull request
Migrate Prometheus Server Overview dashboard to lens.

8.9.0 or higher

1.13.0

Enhancement View pull request
Ensure event.kind is correctly set for pipeline errors.

8.9.0 or higher

1.12.1

Bug fix View pull request
Fix remote_write ingest pipeline to include both metric path 'prometheus.' and 'prometheus.metrics.' to fingerprint calculation

8.9.0 or higher

1.12.0

Enhancement View pull request
Use ecs definition of the 'event.dataset' field

8.9.0 or higher

1.11.0

Enhancement View pull request
Enable TSDB by default for remote_write datastreams. This improves storage usage and query performance. For more details, see https://www.elastic.co/guide/en/elasticsearch/reference/current/tsds.html

8.9.0 or higher

1.10.0

Enhancement View pull request
Align fingerprint field name across all datastreams, add handling of pipeline failures to the collector and query datastreams

8.9.0 or higher

1.9.0

Enhancement View pull request
Add dimension and metric_type fields to remote_write datastream

8.9.0 or higher

1.8.0

Enhancement View pull request
Enable TSDB by default for collector and query metrics data streams. This improves storage usage and query performance. For more details, see https://www.elastic.co/guide/en/elasticsearch/reference/current/tsds.html. Still TSDB is not supported for remote_write

8.9.0 or higher

1.7.0

Enhancement View pull request
Revert metrics field definition to the format used before introducing metric_type

8.9.0 or higher

1.6.0

Enhancement View pull request
Add metric_type fields to collector and query datastreams for TSDB support

8.9.0 or higher

1.5.0

Enhancement View pull request
Add dimension fields to collector and query datastreams for TSDB support

8.4.0 or higher

1.4.0

Enhancement View pull request
Add processor configuration

8.4.0 or higher

1.3.2

Bug fix View pull request
Fix timeout and connect_timeout parameter parsing issue

8.4.0 or higher

1.3.1

Enhancement View pull request
Added categories and/or subcategories.

8.4.0 or higher

1.3.0

Enhancement View pull request
Support data_stream.dataset name

8.4.0 or higher

1.2.0

Enhancement View pull request
Enable setting condition on Prometheus Collector

8.4.0 or higher

1.1.0

Enhancement View pull request
Remove "integration" from the package name

8.4.0 or higher

1.0.1

Enhancement View pull request
Removing x-pack references and updating default values

8.4.0 or higher

1.0.0

Enhancement View pull request
Promote integration to GA

8.4.0 or higher

0.14.0

Enhancement View pull request
Update default dashboard

—

0.13.0

Enhancement View pull request
Revert index mapping changes for histogram type

—

0.12.0

Bug fix View pull request
Disable leader election by default, remove bearer token file default value

—

0.11.0

Bug fix View pull request
Fix histogram type in collector data_stream

—

0.10.0

Enhancement View pull request
Hide some configuration for remote_write data_stream; Add leader election for collector and query data_streams

—

0.9.2

Enhancement View pull request
reworded a link to related documentation in the Readme so it is clearer

—

0.9.1

Enhancement View pull request
Add documentation for multi-fields

—

0.9.0

Enhancement View pull request
Add standard HTTP options to the package

—

0.8.0

Enhancement View pull request
Improve default datastream enablement

—

0.7.0

Enhancement View pull request
Release prometheus package for v8.0.0

—

0.6.1

Enhancement View pull request
Uniform with guidelines

—

0.6.0

Enhancement View pull request
Update to ECS 1.12.0

—

0.5.1

Enhancement View pull request
Escape special characters in docs

—

0.5.0

Enhancement View pull request
Update integration description

—

0.4.1

Enhancement View pull request
Fix yml code blocks

—

0.4.0

Enhancement View pull request
Set event.module and event.dataset

—

0.3.5

Enhancement View pull request
Updating package owner

—

0.3.4

Bug fix View pull request
Correct sample event file.

—

0.3.3

Bug fix View pull request
Change kibana.version constraint to be more conservative.

—

0.1.0

Enhancement View pull request
initial release

—

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