Venus module to manage dashboard
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
baiziyu 8c53ac83ea Add venusclient install process 1 week ago
devstack Add venusclient install process 1 week ago
doc Fix copyright of the files 5 months ago
tools * initial commit. 12 months ago
venus_dashboard Fix copyright of the files 5 months ago
venv * initial commit. 12 months ago
.gitignore * initial commit. 12 months ago
.gitreview change gerrit remove address 7 months ago
.zuul.yaml .zuul.yaml: add Zuul support to new repo 1 year ago
CONTRIBUTING.rst * initial commit. 12 months ago
HACKING.rst * initial commit. 12 months ago
LICENSE * initial commit. 12 months ago
MANIFEST.in * initial commit. 12 months ago
README.rst update README 5 months ago
babel.cfg * initial commit. 12 months ago
bindep.txt * initial commit. 12 months ago
karma.conf.js * initial commit. 12 months ago
manage.py * initial commit. 12 months ago
package.json * initial commit. 12 months ago
requirements.txt Remove python-venusclient temporarily. 5 months ago
setup.cfg Merge "Remove python v3.10 support" 5 months ago
setup.py Fix copyright of the files 5 months ago
test-requirements.txt * initial commit. 12 months ago
test-shim.js * initial commit. 12 months ago
tox.ini Remove python v3.10 support 5 months ago

README.rst

Venus Dashboard

Provide a dashboard for OpenStack Log Management Service (venus).

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.