{
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            "Programming Language :: Python",
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        "description": "# \ud83d\udd25 mae [![](https://img.shields.io/pypi/v/mae.svg)](https://pypi.org/project/mae) [![](https://img.shields.io/pypi/pyversions/mae.svg)](https://pypi.org/project/mae) [![](https://travis-ci.org/paambaati/mae.svg?branch=master)](https://travis-ci.org/paambaati/mae) [![Maintainability](https://api.codeclimate.com/v1/badges/87b24e61fd1c6a998254/maintainability)](https://codeclimate.com/github/paambaati/mae/maintainability) [![Test Coverage](https://api.codeclimate.com/v1/badges/87b24e61fd1c6a998254/test_coverage)](https://codeclimate.com/github/paambaati/mae/test_coverage)\n\n`mae` collects Prometheus metrics from your Mesos apps.\n\nSee [Deployment Strategy](#deployment-strategy) to learn how to set up `mae` on your Mesos cluster.\n\n## Requirements\n\n`mae` requires Python (>= 2.7), and supports Python 3 (>= 3.5).\n\n## Installation\n\n```\npip install mae\n```\n\n## Usage\n```\n$ mae --help\n\nusage: mae [-h] app_port slave_address slave_port\n\npositional arguments:\n  app_port       Port on which this exporter will run on\n  slave_address  Mesos slave address\n  slave_port     Mesos slave port\n```\nThe logging level of the CLI can also be configured with the `LOG_LEVEL` environment variable. Read the [`logging` library's levels](https://docs.python.org/2/library/logging.html#logging-levels) for all the available levels.\n\n## Task Labels\n\nOnce `mae` is up and running, it will start collecting metrics from all apps that have the `prometheus.metrics.enabled` label. You can also customize how the metrics are collected  \u2014\n\n| [Task Label](https://docs.mesosphere.com/1.7/usage/tutorials/task-labels/)                           \t| Description                                                                                                              \t| Required? \t| Default    \t|\n|---------------------------------\t|--------------------------------------------------------------------------------------------------------------------------\t|-----------\t|------------\t|\n| `prometheus.metrics.enabled`    \t| Enables metrics collection. If the label isn't found, the app's metrics are not collected.                               \t| Yes       \t|            \t|\n| `prometheus.metrics.port_index` \t| The port index where your app is exposing its Prometheus metrics. This is useful for Mesos apps that use multiple ports. \t| No        \t| `0`        \t|\n| `prometheus.metrics.endpoint`   \t| The endpoint where your app is exposing its metrics.                                                                     \t| No        \t| `/metrics` \t|\n\n## Deployment Strategy\n\n`mae` is designed to be run as a daemon on all Mesos slave nodes. This ideally involves 2 steps \u2014\n\n1. [Install `mae`](#installation) as part of your base image/AMI or via [user data](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/user-data.html).\n2. Run `mae` as a daemon. For example, if your distro supports `systemd`, here's a sample script that runs the exporter on port `8888` \u2014\n    ```\n    # Save this to /etc/systemd/system/mae.service\n    [Unit]\n    Description=Mesos App Exporter\n    After=network.target\n\n    [Service]\n    Type=simple\n    Restart=on-failure\n    Environment=\"LOG_LEVEL=INFO\"\n    ExecStart=/usr/local/bin/mae 8888 localhost 5051 # Assuming the Mesos slave process is running on port 5051\n\n    [Install]\n    WantedBy=multi-user.target\n    ```\n\n\n",
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