monitor-exporter 1.3.4

A Prometheus exporter for OP5 Monitor

monitor-exporter

• Overview
• Metrics naming
  • Service performance data
  • Host performance data
  • State
  • Metric labels
  • Performance metrics name to labels
• Configuration
  • monitor-exporter
• Using Redis cache
• Logging
• Prometheus configuration
  • Static config
  • File discovery config for usage with monitor-promdiscovery
• Installing
• Running
  • Development with Quart built in webserver
  • Production deployment
    • Deploying with gunicorn
  • Test the connection
• System requirements
• License

Overview

The monitor-exporter utilises ITRS, former OP5, Monitor's API to fetch host and service-based performance data and publish it in a way that lets Prometheus scrape the performance data and state as metrics.

Benefits:

• Enable advanced queries and aggregation on time series
• Prometheus based alerting rules
• Grafana graphing
• Take advantage of metrics already collected by Monitor, without rerunning checks
• Collect hosts and services performance data and state and translate to Prometheus metrics

This solution is a perfect gateway for any Monitor users that would like to start using Prometheus and Grafana.

Metrics naming

Service performance data

Metrics that are scraped with the monitor-exporter will have the following naming structure:

monitor_<check_command>_<perfname>_<unit>

Unit is only added if it exists for the performance data

For example the check command check_ping will result in two metrics:

monitor_check_ping_rta_seconds
monitor_check_ping_pl_ratio

Host performance data

In Monitor the host also have a check to verify the state of the host. The metric name is always called monitor_check_host_alive. If this check as multiple performance values they will be reported as individual metrics, e.g.

monitor_check_host_alive_pkt{hostname="foo.com", environment="production", service="isalive"} 1
monitor_check_host_alive_rta{hostname="foo.com", environment="production", service="isalive"} 2.547
monitor_check_host_alive_pl_ratio{hostname="foo.com", environment="production", service="isalive"} 0.0

Service label will always be isalive

State

State metrics is reported for both hosts and services. State metrics is reported as value 0 (okay), 1 (warning), 2 (critical) and 4 (unknown).

For hosts the metric name is:

monitor_host_state

For services the metric name is:

monitor_service_state

Metric labels

The monitor-exporter adds a number of labels to each metric:

• hostname - is the host_name in Monitor
• service - is the service_description in Monitor
• downtime - if the host or service is currently in a downtime period - true/false. If the host is in downtime its services are also in downtime. Attention, downtime is only support if monitor-export is running in cache mode.
• address - the hosts real address
• acknowledged - is applicable if a host or service is in warning or critical and have been acknowledged by operations - 0/1 where 1 is acknowledged.

Optionally the monitor-exporter can be configured to pass all or specific custom variables configured in Monitor as labels Prometheus.

Any host based custom variables that is used as labels is also set for its services.

Labels created from custom variables are all transformed to lowercase.

Performance metrics name to labels

As described above, the default naming of the Prometheus name is:

monitor_<check_command>_<perfname>_<unit>

For some check commands this does not work well like for the self_check_by_snmp_disk_usage_v3 check command where the perfname are the unique mount paths. For checks where the perfname is defined depending on a specific name, you can change it so the perfname becomes a label instead. This is defined in the configuration like:

  perfnametolabel:
    # The command name
    self_check_by_snmp_disk_usage_v3:
      # the label name to be used
      label_name: disk
    check_disk_local_mb:
      label_name: local_disk

So if the check command is self_check_by_snmp_disk_usage_v3, the Prometheus metrics will have a format like:

monitor_self_check_by_snmp_disk_usage_v3_bytes{hostname="monitor", service="Disk usage /", disk="/_used"} 48356130816.0

If we did not make this transformation, we would get the following:

monitor_self_check_by_snmp_disk_usage_v3_slash_used_bytes{hostname="monitor", service="Disk usage /"} 48356130816.0

Which is bad since we get specific metric name from the perfname.

Please be aware of naming conventions for perfname and services, especially when they include a name depending on what is checked like a mountpoint or disk name.

Configuration

monitor-exporter

All configuration is made in the config.yml file. Please see read thee file for all configuration options.

When running with gunicorn the port is defined by gunicorn

Using Redis cache

If you have a large Monitor configuration, the load of the Monitor server can get high when collecting host and service data over the api with a high rate. We strongly recommend that you instead collect host and service data in a batch and store it in a redis cache. The interval of the batch collecting is configurable, but considering that most service checks in Monitor are often done in 5 minutes interval, collecting every minute should be more than enough.

To use caching just add this to your config.yml:

cache:
  # Use redis for cache - future may support others
  # Values below is the default
  redis:
    # redis host
    host: localhost
    # redis port
    port: 6379
    # the auth string used in redis
    #auth: secretstuff
    # the redis db to use
    db: 0
  # The interval to collect data from Monitor in secoends
  interval: 60
  # The time to live for the stored Monitor objects in the redis cache
  ttl: 300

Redis must be installed on some host on the network and be accessible from the server running monitor-exporter

Logging

The log stream is configure in the above config. If logfile is not set the logs will go to stdout.

Logs are formatted as json so it's easy to store logs in log servers like Loki and Elasticsearch.

Prometheus configuration

Prometheus can be used with static configuration or with dynamic file discovery using the project monitor-promdiscovery

Please add the the job to the scrape_configs in prometheus.yml.

The target is the host_name configured in Monitor.

Static config

scrape_configs:
  - job_name: 'op5monitor'
    metrics_path: /metrics
    static_configs:
      - targets:
          - monitor
          - google.se
    relabel_configs:
      - source_labels: [__address__]
        target_label: __param_target
      - source_labels: [__param_target]
        target_label: instance
      - target_label: __address__
        replacement: localhost:9631

File discovery config for usage with monitor-promdiscovery

scrape_configs:
  - job_name: 'op5monitor'
    scrape_interval: 1m
    metrics_path: /metrics
    file_sd_configs:
      - files:
          - 'sd/monitor_sd.yml'
    relabel_configs:
      - source_labels: [__address__]
        target_label: __param_target
      - source_labels: [__param_target]
        target_label: instance
      - target_label: __address__
        replacement: localhost:9631

Installing

1. Clone the git repo.

2. Install dependencies

   pip install -r requirements.txt

3. Build a distribution

   python setup.py sdist

4. Install locally

   pip install dist/monitor-exporter-X.Y.Z.tar.gz

Running

Development with Quart built in webserver

python -m  monitor_exporter -f config.yml

The switch -p enable setting of the port.

Production deployment

There are a number of ASGI containers that can be can use to deploy monitor-exporter. The dependency for these are not included in the distribution.

Deploying with gunicorn

First install the guincorn dependency into the python environment.

pip install gunicorn==20.1.0
pip install uvicorn==0.14.0

Running with the default config.yml. The default location is current directory.

gunicorn --access-logfile /dev/null -w 4 -k uvicorn.workers.UvicornWorker "wsgi:create_app()"

Set the path to the configuration file.

gunicorn --access-logfile /dev/null -w 4 -k uvicorn.workers.UvicornWorker "wsgi:create_app('/etc/monitor-exporter/config.yml')"

Port for gunicorn is default 8000, but can be set with -b, e.g. -b localhost:9631

Docker

Alt 1: Edit the config.yml in repo:

docker run -p 9631:9631 monitor-exporter

Alt 2: Have config in separate location

docker run -v /path/to/config:/monitor-exporter/config/ -p 9631:9631 monitor-exporter

Test the connection

Check if the exporter is working.

curl -s http://localhost:9631/health

Get metrics for a host where target is a host using the same host_name in Monitor

curl -s http://localhost:9631/metrics?target=foo.com

System requirements

Python 3.8

For required packages, please review requirements.txt

License

The monitor-exporter is licensed under GPL version 3.