Lingxian Kong fdc96d9d9e Use HMAC.hexdigest to avoid non-ascii characters for package data
hmac.compare_digest() method in python 3 doesn't suppport non-ASCII
characters, so that we need to use HMAC.hexdigest() to avoid non-ASCII
bytes.

For backward compability, we still need to support HMAC created by
using HMAC.digest() in the old amphorae.

Change-Id: I1061e855d0ce06d91a26d217291008197e4a708b
Depends-On: https://review.openstack.org/#/c/567688/
Story: 2002125
Task: 19807
2018-06-01 08:00:20 +00:00
2018-05-23 00:26:43 +00:00
2017-04-30 08:36:44 +00:00
2018-05-08 07:25:35 -07:00
2018-03-07 11:57:31 +00:00
2017-10-16 09:32:41 +08:00
2016-12-15 00:48:02 +00:00
2017-03-02 11:50:57 +00:00

Team and repository tags

image

Octavia

Latest Version

Octavia is an operator-grade open source scalable load balancer for use in large OpenStack deployments. It delivers load balancing services on amphorae and provides centralized command and control. Octavia is currently the reference backend for Neutron LBaaS. In the near future, Octavia is likely to become the standard OpenStack LBaaS API endpoint.

Octavia is distributed under the terms of the Apache License, Version 2.0. The full terms and conditions of this license are detailed in the LICENSE file.

Project resources

Developer documentation for the Octavia project is available at https://docs.openstack.org/octavia/latest/

Release notes for the Octavia project are available at https://docs.openstack.org/releasenotes/octavia/

The project source code repository is located at https://git.openstack.org/cgit/openstack/octavia

Project status, bugs, and requests for feature enhancements are tracked on https://launchpad.net/octavia

For more information on project direction and guiding principles for contributors, please see the CONSTITUTION.rst file in this directory, or specifications in the specs/ sub-directory.

The project roadmap is available at https://wiki.openstack.org/wiki/Octavia/Roadmap

Description
Load Balancing as a Service (LBaaS) for OpenStack
Readme 97 MiB
Languages
Python 97.5%
Shell 1.9%
Jinja 0.6%