Sorna-agent

------------------

**CHANGES**

- Now it uses [aiodocker][aiodocker] instead of [docker-py][dockerpy] to
prevent timeouts with many concurrent requests.

NOTE: You need to run `pip install -r requirements.txt` to install the
non-pip (GitHub) version of aiodocker correctly, before running
`pip install sorna-agent`.

**FIXES**

- Fix corner-case exceptions in statistics/heartbeats.

[aiodocker]: https://github.com/achimnol/aiodocker
[dockerpy]: https://github.com/docker/docker-py

------------------

**CHANGES**

- Increase docker API timeouts.

**FIXES**

- Fix heartbeats stop working after kernel/agent timeouts.

- Fix exception logging in the main server loop.

------------------

**FIXES**

- Hotfix for missing dependency: coloredlogs

------------------

**NEW**

- `--agent-ip-override` CLI option to override the IP address of agent
reported to the manager.

------------------

**NEW**

- Add support for kernel restarts.
Restarting preserves kernel metadata and its ID, but removes and recreates
the working volume and the container itself.

- Add `--debug` option to the CLI command.

------------------

**NEW**

- Add support for GPU-enabled kernels (using [nvidia-docker plugin][nvdocker]).
The kernel images must be built upon nvidia-docker's base Ubuntu images and
have the label "io.sorna.nvidia.enabled" set `yes`.

**CHANGES**

- Change the agent to add "lablup/" prefix when creating containers from
kernel image names, to ease setup and running using the public docker
repository. (e.g., "lablup/kernel-python3" instead of "kernel-python3")

- Change the prefix of kernel image labels from "com.lablup.sorna." to
"io.sorna." for simplicity.

- Increase the default idle timeout to 30 minutes for offline tutorial/workshops.

- Limit the CPU cores available in kernel containers.
It uses an optional "io.sorna.maxcores" label (default is 1 when not
specified) to determine the requested number of CPU cores in kernels, with a
hard limit of 4.

NOTE: You will still see the full count of CPU cores of the underlying
system when running `os.cpu_count()`, `multiprocessing.cpu_count()` or
`os.sysconf("SC_NPROCESSORS_ONLN")` because the limit is enforced by the CPU
affinity mask. To get the correct result, try
`len(os.sched_getaffinity(os.getpid()))`.

[nvdocker]: https://github.com/NVIDIA/nvidia-docker