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Prometheus remote_write metricset

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Prometheus remote_write metricset

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This is the remote_write metricset of the module prometheus. This metricset can receive metrics from a Prometheus server that has configured remote_write setting accordingly, for instance:

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

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.

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

- module: prometheus
  metricsets: ["remote_write"]
  host: "localhost"
  port: "9201"

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

- module: prometheus
  metricsets: ["remote_write"]
  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

Histograms and types

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This functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.

metricbeat.modules:
- module: prometheus
  metricsets: ["remote_write"]
  host: "localhost"
  port: "9201"

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

rate_counters parameter (default: false) 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

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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:

  1. _total suffix: the metric is of Counter type
  2. _sum suffix: the metric is of Counter type
  3. _count suffix: the metric is of Counter type
  4. _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:

metricbeat.modules:
- module: prometheus
  metricsets: ["remote_write"]
  host: "localhost"
  port: "9201"
  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. 
metricbeat.modules:
- module: prometheus
  metricsets: ["remote_write"]
  host: "localhost"
  port: "9201"
  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.

Fields

For a description of each field in the metricset, see the exported fields section.

Here is an example document generated by this metricset:

{
    "@timestamp": "2020-02-28T13:55:37.221Z",
    "@metadata": {
        "beat": "metricbeat",
        "type": "_doc",
        "version": "8.0.0"
    },
    "service": {
        "type": "prometheus"
    },
    "agent": {
        "version": "8.0.0",
        "type": "metricbeat",
        "ephemeral_id": "ead09243-0aa0-4fd2-8732-1e09a6d36338",
        "hostname": "host1",
        "id": "bd12ee45-881f-48e4-af20-13b139548607"
    },
    "ecs": {
        "version": "1.4.0"
    },
    "host": {},
    "event": {
        "dataset": "prometheus.remote_write",
        "module": "prometheus"
    },
    "metricset": {
        "name": "remote_write"
    },
    "prometheus": {
        "metrics": {
            "container_tasks_state": 0
        },
        "labels": {
            "name": "nodeexporter",
            "id": "/docker/1d6ec1931c9b527d4fe8e28d9c798f6ec612f48af51949f3219b5ca77e120b10",
            "container_label_com_docker_compose_oneoff": "False",
            "instance": "cadvisor:8080",
            "container_label_com_docker_compose_service": "nodeexporter",
            "state": "iowaiting",
            "monitor": "docker-host-alpha",
            "container_label_com_docker_compose_project": "dockprom",
            "job": "cadvisor",
            "image": "prom/node-exporter:v0.18.1",
            "container_label_maintainer": "The Prometheus Authors <[email protected]>",
            "container_label_com_docker_compose_config_hash": "2cc2fedf6da5ff0996a209d9801fb74962a8f4c21e44be03ed82659817d9e7f9",
            "container_label_com_docker_compose_version": "1.24.1",
            "container_label_com_docker_compose_container_number": "1",
            "container_label_org_label_schema_group": "monitoring"
        }
    }
}
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