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cluster-logger-0.5.0
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Library for wrapping cluster logging for Altamira projects.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cluster-logger-0.5.0 |
| نام | cluster-logger |
| نسخه کتابخانه | 0.5.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Nick Gernert |
| ایمیل نویسنده | nicholas.gernert@altamiracorp.com |
| آدرس صفحه اصلی | https://bitbucket.di2e.net/projects/PIR/repos/websl-logging |
| آدرس اینترنتی | https://pypi.org/project/cluster-logger/ |
| مجوز | - |
# Cluster Logging library for python 3.6
This is a library for python 3.6 that will help fulfil a
requirement for cluster services and logging to elastic search.
## Requirements
- Python 3.6+
- pipenv
- Elasticsearch
- Fluentd
- Kibana
## Pipenv & Pipfile
Pipenv combines package management and virtualenv into one tool.
pipenv: https://docs.pipenv.org/basics
To install:
```bash
$ pip install pipenv
```
Pipfile replaces requirements.txt and it will specify both dependencies and dev dependencies in one file.
## Development Installation
```bash
# install dependencies
pipenv install --dev
# activate virtual environment
pipenv shell
# alternativly you can start your script in a virtual environment context
pipenv run python main.py message that you want to send
```
## ULM Configuration
The default configuration uses Environment variables to configure the logger.
These values were grabbed from version 2.0 of ULM-logging-common Java implementation. Not every value is implemented yet and changes are upto date in table.
[Repo](https://bitbucket.di2e.net/projects/PIR/repos/logging-common/browse)
| Variable | Default Value | Description | Implemented |
| -------- | ------------- | ----------- | ----------: |
| ULM_FLUENTD_HOST | localhost | host of the FluentD service | ✔️
| ULM_FLUENTD_PORT | 24224 | port of FluentD tcp "in_forward" | ✔️
| ULM_FLUENTD_LABEL_ENVS | | comma separated list(with or without space) of other ENV vars to add as fields to FluentD logs | ✔️
| ULM_FLUENTD_TAG | (project).(app) | tag to use when sending logs to fluentd, e.g. the MLA_IDENT string such as "Myapp.logs" | ✔️
| ULM_FLUENTD_BUFFER | 1048576 | an integer of the number of bytes to allow in the buffer. Excess will be dropped (default is 1MiB) | ❌
| ULM_FLUENTD_TIMEOUT | 3.0 | an float of the number of ms to allow for communication with FluentD. | ✔️
| ULM_FLUENTD_CLIENT | async | Whether to send async messages or not. This will send async as long as the value has async somewhere in the string. | ✔️
| ULM_FLUENTD_ENABLE_TIMEMS_FIELD | False | Enables an additional field to contain the millisecond timestamp | ❌
| ULM_FLUENTD_TIMEMS_FIELD | timems | the name of the field to contain the millisecond timestamp | ❌
## Standalone Usage (Development)
It may be required to run the following command to get elastic search to run.
```bash
sudo sysctl -w vm.max_map_count=262144
```
### Local
```bash
$ pipenv run python main.py -h
usage: main.py [-h] [-n HOST] [-p PORT] [-e [ENV [ENV ...]]] [-o PROJECT]
[-a APP] [-c COUNT]
Console Application to test Cluster Logging using fluentd.
positional arguments:
message Message to be logged.
optional arguments:
-h, --help show this help message and exit
-n HOST, --host HOST Hostname to listen on. (default=localhost)
-p PORT, --port PORT Port number to bind to. (default=24224)
-e [ENV [ENV ...]], --env [ENV [ENV ...]]
Environment Keys to add to message.
-o PROJECT, --project PROJECT
Tag for the project
-a APP, --app APP Tag for the application
-c COUNT, --count COUNT
The number of times to send message.
```
### Docker
```bash
$ docker build -t TAG_FOR_THE_BUILD:VERSION .
# all env values can be set with -e
$ docker run -e host=fluentd \
-e port=24224 -e msg="message you want to send" TAG_FOR_THE_BUILD:VERSION
# If you want to run the whole environment you can use docker-compose up
$ docker-compose up
```
### Api
Follows the python logger implementation with logging levels. [python.org](https://docs.python.org/3/library/logging.html)
| Level | Numeric value |
| -------- | ------------: |
| CRITICAL | 50 |
| ERROR | 40 |
| WARNING | 30 |
| INFO | 20 |
| DEBUG | 10 |
| NOTSET | 0 |
Logging level can be set for logging using:
```python
import logging
logging.basicConfig(level=logging.WARNING)
```
Setting the logging level will filter levels below the set logging level. For logging levels error and above the stack trace will be added to the log message.
### Standard Configuration
These environment variables can be set either system-wide or added to the `.env` file:
There are 3 Environment variables that will be extracted by default:
- `HOST` - host that the container is running on.
- `APP_VERSION` - Version of the app.
- `LOGGER_VERBOSE` - Whether the fluent logger library is verbose or not.
- `MARATHON_APP_ID` - The ID that is assigned by DCOS.
- `MARATHON_APP_DOCKER_IMAGE` - The image that the container was built from.
There are three ways to get application properties into log messages.
- pass a dictionary of key value pairs
- pass a list of keys that are on the container environment
- or pass a JSON file with key value pairs.
NOTE:
- The dictionary will overwrite values in environment and JSON file.
- The Environment will overwrite values in the JSON file.
### Usage
Activate your venv
```bash
# Linux / MacOS
source {NAME_OF_VENV}/bin/activate
```
```bat
REM Windows
{NAME_OF_VENV}\Scripts\activate
```
Install cluster logger into your venv. Cluster Logger has been installed into pypi.
```bash
$ pip install cluster_logger
```
To Use
```python
import cluster_logger
import logging
# Then init the ClusterLogger class
env_keys = ['MARATHON_APP_LABELS', 'MARATHON_APP_RESOURCE_CPUS']
props = {'HOST', '192.168.0.12'}
logging.basicConfig(level=logging.DEBUG) # set logging level
cluster_logger.initLogger('Rasters', # Project name
'intent_client', # Application name
'fluentd', # Fluentd Host name (optional) will default to fluentd if nothing is passed in and HOST isn't set on the environment
24224, # Fluentd Port Number(optional)
'/path/to/settings.json', # JSON settings file (optional)
env_keys, # Environment Keys (optional)
props) # Specific Properties (optional)
# in Module where you will log
import cluster_logger
# General Logger
logger = cluster_logger.getLogger(__name__)
# Metric Logger
metrics = cluster_logger.getLogger(__name__ + '.metrics', is_metric=True)
logger.exception('Custom Message to send typically an error')
logger.log(logging.INFO, {'Duration', 58})
```
### Contributing
```bash
# bump the version that is stored in setup.py and cluster_logger/__init__.py
# assuming pipenv install --dev was ran first
$ pipenv run bumpversion minor # possible: major / minor / patch
$ git push
```
نیازمندی
| مقدار | نام |
|---|---|
| - | fluent-logger |
نحوه نصب
نصب پکیج whl cluster-logger-0.5.0:
pip install cluster-logger-0.5.0.whl
نصب پکیج tar.gz cluster-logger-0.5.0:
pip install cluster-logger-0.5.0.tar.gz