openstack/venus
Code Issues Proposed changes
A log management component for OpenStack
59 Commits 6 Branches 13 Tags 48 MiB
Python 98.6%
Shell 1.3%
Mako 0.1%
53990ad4e2
Go to file
Zuul 53990ad4e2 Merge "remove six in venus/api/middleware/fault.py"
2020-12-23 01:42:56 +00:00
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 delete the section of useless in venus.conf 2020-12-10 14:10:59 +08:00
releasenotes Initialize the Venus project 2020-11-11 08:19:55 +00:00
tools/config Initialize the Venus project 2020-11-11 08:19:55 +00:00
venus Merge "remove six in venus/api/middleware/fault.py" 2020-12-23 01:42:56 +00:00
.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 Initialize the Venus project 2020-11-11 08:19:55 +00:00
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 add lxml to requirements 2020-12-21 02:54:53 +00:00
setup.cfg add wsgi entry_point 2020-12-17 10:16:47 +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.