SUSE currently consumes a lot of electricity for keeping servers up an running as well as workstations at the office rooms, air-conditions and so on. The project is about to collect information where all the power is going to and to find sweet spots for saving power (and money).

I want to gain some knowledge about CI and devops. I wrote a script to generated configuration files for pxe server and slp sever.

More and more customers use our products in mission critical environment. They have a huge need that things run smooth. With Hack Week we have the challenge

The evfilter project (https://github.com/lhc4/libevfilter/) isn't able to substitute multiple events to one event or vice versa. I want to improve that and repair some other bugs.

Use machine learning and natural language processing techniques to analyze the changes made in a project, and classify them in: * Small / unimportant fix

This will greatly enhance the usefulness of QEMU virtual serial ports, because the Linux kernel interprets a break on the serial console as a SysRq, but there is currently no way to pass this signal over a pseudo-terminal.

Machinery supports inspection of SLES11 and SLES12 systems right now. It would be beneficial to be able to also inspect RHEL systems for various reasons:

In last hackweek, I implemented a RSA private key parser in kernel: https://github.com/SUSE/hackweek/wiki/RSA-private-key-parser-in-kernel

Dochazka is a long-term project to replace the obsolete Attendance & Time Tracking system used by the Prague office since 2007. Dochazka is a complex system consisting of three major components: - RESTful backend App::Dochazka::REST (with lots of help from Web::MREST)