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baiziyu-inspur bb07f9a470 fix VENUS_FILES directory.

Change-Id: Ib0c6e920adff9f9fe1dca52bfdb9a526b7f4ade1

2021-06-08 14:24:52 +08:00

api-ref/source

Initialize the Venus project

2020-11-11 08:19:55 +00:00

devstack

fix VENUS_FILES directory.

2021-06-08 14:24:52 +08:00

doc

Initialize the Venus project

2020-11-11 08:19:55 +00:00

etc/venus

delete mysql storage and use config file store data

2021-05-11 14:40:14 +08:00

releasenotes

remove unicode from code

2021-01-03 16:08:28 +08:00

tools/config

Initialize the Venus project

2020-11-11 08:19:55 +00:00

venus

repair the elasticsearch store day result to json

2021-06-03 14:03:16 +08:00

.gitignore

Add devstack support

2021-03-16 09:33:36 +08:00

.gitreview

Added .gitreview

2020-11-10 02:23:44 +00:00

.zuul.yaml

Add pep8 job for venus

2020-11-11 09:03:11 +00:00

CONTRIBUTING.rst

fix the spelling mistake

2020-12-17 14:07:31 +08:00

HACKING.rst

remove six in HACKING.rst

2021-01-07 10:18:54 +08:00

LICENSE

Initialize the Venus project

2020-11-11 08:19:55 +00:00

MANIFEST.in

Add devstack support

2021-03-16 09:33:36 +08:00

README.bak.rst

Rename readme file

2020-11-20 07:38:37 +00:00

README.rst

Hello Venus

2020-11-25 01:11:18 +00:00

requirements.txt

Fix elasticsearch version issues

2021-06-02 14:18:54 +08:00

setup.cfg

Merge "setup.cfg: Replace dashes with underscores"

2021-05-14 00:36:45 +00:00

setup.py

Initialize the Venus project

2020-11-11 08:19:55 +00:00

test-requirements.txt

Initialize the Venus project

2020-11-11 08:19:55 +00:00

tox.ini

fix the spelling mistake

2020-12-17 14:07:31 +08:00

README.rst

Hello Venus

An OpenStack Log Management Service.

About Venus

In light of the problems and needs of retrieval, storage and analysis etc. of logs on the OpenStack platform, we developed the OpenStack log management module Venus.

This project can provide a one-stop solution to log collection, cleaning, indexing, analysis, alarm, visualization, report generation and other needs, which involves helping operator or maintainer to quickly solve retrieve problems, grasp the operational health of the platform, and improve the level of platform management.

Additionally, this project plans to use machine learning algorithms to quickly locate IT failures and root causes, and improve operation and maintenance efficiency.