openstack
/
venus
Code Issues Proposed changes
A log management component for OpenStack
93 Commits 5 Branches 11 Tags 48 MiB
Python 98.6%
Shell 1.3%
Mako 0.1%
Go to file
YuehuiLei e5e455ca8f remove six in HACKING.rst 
Change-Id: I668b1480601234d7ac9d77959793366ea9a4c156
 		2021-01-07 10:18:54 +08:00
api-ref/source Initialize the Venus project 2020-11-11 08:19:55 +00:00
doc Initialize the Venus project 2020-11-11 08:19:55 +00:00
etc/venus fix json file formmat in policy.json 2021-01-03 16:27:37 +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 test 2021-01-03 16:13:25 +08:00
.gitignore Add git ignore files 2020-12-17 16:56:56 +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 Initialize the Venus project 2020-11-11 08:19:55 +00:00
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 remove six in venus/common/utils.py, add urlib3 in requirement.txt 2020-12-22 18:04:03 -08:00
setup.cfg remove py37 2021-01-04 10:28:15 +08:00
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.