Barcelona, Spain
October 25-28, 2016

Event Details

Please note: All times listed below are in Central Time Zone


Perform Schema Rolling Upgrades in Just One Release Cycle

Reliable Openstack deployment should be as close to 100% availability as possible and always up to date with the latest release. To achieve this, during an upgrade services should be stopped and replaced with new one with no API downtime. In projects like keystone, glance or neutron this means keeping compatibility of DB schema between releases. The complexity of maintaining this compatibility, while keeping performance and security on a high level, is a hot topic in the community. Current approach in projects like nova or cinder requires keeping the data compatibility for 2 or 3 releases. In this presentation we want to show solutions, how to reduce the data migration time period to one release cycle. This would reduce the code complexity and performance overhead in database layer.


What can I expect to learn?

Attendees should learn about existing solutions for online schema upgrades in Openstack projects like keystone, glance and neutron. Also, listeners will get to know the proposed improvements in upgrade process.

Tuesday, October 25, 12:15pm-12:55pm (10:15am - 10:55am UTC)
Difficulty Level: Intermediate
Intel Corporation
Artur Korzeniewski is a software engineer at Intel, currently working in Neutron community on subjects related to upgradability and HA of services. He is Neutron Upgrades team member, dedicated to improve the process of upgrade. Before joining the Neutron team, he was closely coupled with OpenStack since Diablo release, working on resource scheduling and compute assurance. Artur likes new... FULL PROFILE
Intel Corporation
@ OpenStack since 2014. After joining Red Hat in 2018, contributing to security related projects and areas. In the past, developed and run network level monitoring and filtering security applications in WheelSystems.com and SurfSafe.com. Experienced Python and Erlang programmer, started at Grono.net, which was the largest deployment of Django and Python in 2005, later worked as a Solutions... FULL PROFILE
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