iDRAC password-less login – iDRAC certificate login

Summary

Enabling certificate login on iDRAC makes it possible to run commands quickly and across many servers. It can be extremely useful in many cases. This post will show how to enable certificate based login on iDRAC and how to run commands against multiple servers in sequence.

First check the users on a remote server with SSH:

 jonas@hydra:~$ ssh root@192.168.1.120
 root@192.168.1.120's password:
 /admin1-> racadm
 racadm>>get idrac.users
racadm get idrac.users
iDRAC.Users.1 [Key=iDRAC.Embedded.1#Users.1]
iDRAC.Users.2 [Key=iDRAC.Embedded.1#Users.2]
iDRAC.Users.3 [Key=iDRAC.Embedded.1#Users.3]
iDRAC.Users.4 [Key=iDRAC.Embedded.1#Users.4]
iDRAC.Users.5 [Key=iDRAC.Embedded.1#Users.5]
iDRAC.Users.6 [Key=iDRAC.Embedded.1#Users.6]
iDRAC.Users.7 [Key=iDRAC.Embedded.1#Users.7]
iDRAC.Users.8 [Key=iDRAC.Embedded.1#Users.8]
iDRAC.Users.9 [Key=iDRAC.Embedded.1#Users.9]
iDRAC.Users.10 [Key=iDRAC.Embedded.1#Users.10]
iDRAC.Users.11 [Key=iDRAC.Embedded.1#Users.11]
iDRAC.Users.12 [Key=iDRAC.Embedded.1#Users.12]
iDRAC.Users.13 [Key=iDRAC.Embedded.1#Users.13]
iDRAC.Users.14 [Key=iDRAC.Embedded.1#Users.14]
iDRAC.Users.15 [Key=iDRAC.Embedded.1#Users.15]
iDRAC.Users.16 [Key=iDRAC.Embedded.1#Users.16]

Let’s use “User10” for this example:

 racadm>>get iDRAC.Users.10
 racadm get iDRAC.Users.10
 [Key=iDRAC.Embedded.1#Users.10]
 Enable=Disabled
 IpmiLanPrivilege=15
 MD5v3Key=
 !!Password=******** (Write-Only)
 Privilege=0x0
 SHA1v3Key=
 SHA256Password=
 SHA256PasswordSalt=
 SNMPv3AuthenticationType=SHA
 SNMPv3Enable=Disabled
 SNMPv3PrivacyType=AES
 SolEnable=Disabled
 UserName=

Update the username, password and privilege:

 racadm>>set iDRAC.Users.10.UserName jonas
 racadm set iDRAC.Users.10.UserName jonas
 [Key=iDRAC.Embedded.1#Users.10]
 Object value modified successfully

racadm>>set iDRAC.Users.10.Password calvin
 racadm set iDRAC.Users.10.Password calvin
 [Key=iDRAC.Embedded.1#Users.10]
 Object value modified successfully

racadm>>set iDRAC.Users.10.Privilege 0x1ff
 racadm set iDRAC.Users.10.Privilege 0x1ff
 [Key=iDRAC.Embedded.1#Users.10]
 Object value modified successfully

racadm>>set iDRAC.Users.10.IpmiLanPrivilege 4
 racadm set iDRAC.Users.10.IpmiLanPrivilege 4
 [Key=iDRAC.Embedded.1#Users.10]
 Object value modified successfully

racadm>>set iDRAC.Users.10.Enable enabled
 racadm set iDRAC.Users.10.Enable enabled
 [Key=iDRAC.Embedded.1#Users.10]
 Object value modified successfully

racadm>>exit

/admin1-> exit
 CLP Session terminated
 Connection to 192.168.1.120 closed.
 jonas@hydra:~$

If no key is available, generate it:

 jonas@hydra:~$ ssh-keygen -t rsa
 Generating public/private rsa key pair.
 Enter file in which to save the key (/home/jonas/.ssh/id_rsa):
 Enter passphrase (empty for no passphrase):
 Enter same passphrase again:
 Your identification has been saved in /home/jonas/.ssh/id_rsa.
 Your public key has been saved in /home/jonas/.ssh/id_rsa.pub.
 The key fingerprint is:
 43:15:av:24:2f:55:c5:5c:y5:v2:75:3e:ad:fa:f0:eb jonas@hydra
 The key's randomart image is:
 +--[ RSA 2048]----+
 | |
 | |
 | |
 | o . |
 | + S . |
 | o + o |
 | . o o + . |
 |+.o .o . |
 |=o ..=B. |
 +-----------------+
 jonas@hydra:~$

Check the key:

jonas@hydra:~$ cat ~/.ssh/id_rsa.pub
ssh-rsa AAASBAASdfjsgdfnsryserhbnsfgjkdTFXNFTSDtjdRTYjsdrwsrthjsTGJsdRJGKdRTjsrtjksidHMdFgjdNsfgbCFjkdfghikdMddndRTYjdmdyikdr+EYFFTM8et+UH7uHPlC6PwWNJWn147gmN16o6JJBXzEt1MSI5Tz659lOhVO8sNomP7aV3onCS59ioED3ctdD7N4YYomVnkqHxu2SpI7B1SrXXmCi3iwY3Q3TXaYBgRc7IOG7j3P9UgNHcJ3OgFn+qcps9Dq1pXIeWDSEFwCI19T8nOjsZxLCN/DmphuwEG7J6f+q+xqhQ9t0rLwZGCmcCEi9eSnvQSjOtLwHUIJJu7RzS95PAW3qmTwem2YbtHT jonas@hydra
jonas@hydra:~$

Push the key to the iDRAC:

 jonas@hydra:~$ ssh jonas@192.168.1.120 "racadm sshpkauth -i 10 -k 1 -t 'ssh-rsa AAASBAASdfjsgdfnsryserhbnsfgjkdTFXNFTSDtjdRTYjsdrwsrthjsTGJsdRJGKdRTjsrtjksidHMdFgjdNsfgbCFjkdfghikdMddndRTYjdmdyikdr+EYFFTM8et+UH7uHPlC6PwWNJWn147gmN16o6JJBXzEt1MSI5Tz659lOhVO8sNomP7aV3onCS59ioED3ctdD7N4YYomVnkqHxu2SpI7B1SrXXmCi3iwY3Q3TXaYBgRc7IOG7j3P9UgNHcJ3OgFn+qcps9Dq1pXIeWDSEFwCI19T8nOjsZxLCN/DmphuwEG7J6f+q+xqhQ9t0rLwZGCmcCEi9eSnvQSjOtLwHUIJJu7RzS95PAW3qmTwem2YbtHT jonas@hydra'"
 jonas@192.168.1.120's password:
 PK SSH Authentication operation completed successfully.
 jonas@hydra:~$
 jonas@hydra:~$

Verify that the key is installed correctly on the iDRAC:

 jonas@hydra:~$ ssh jonas@192.168.1.120 "racadm sshpkauth -v -i 10 -k all"
 --- User 10 ---

Key 1 : ssh-rsa AAASBAASdfjsgdfnsryserhbnsfgjkdTFXNFTSDtjdRTYjsdrwsrthjsTGJsdRJGKdRTjsrtjksidHMdFgjdNsfgbCFjkdfghikdMddndRTYjdmdyikdr+EYFFTM8et+UH7uHPlC6PwWNJWn147gmN16o6JJBXzEt1MSI5Tz659lOhVO8sNomP7aV3onCS59ioED3ctdD7N4YYomVnkqHxu2SpI7B1SrXXmCi3iwY3Q3TXaYBgRc7IOG7j3P9UgNHcJ3OgFn+qcps9Dq1pXIeWDSEFwCI19T8nOjsZxLCN/DmphuwEG7J6f+q+xqhQ9t0rLwZGCmcCEi9eSnvQSjOtLwHUIJJu7RzS95PAW3qmTwem2YbtHT jonas@hydra

Key 2 :

Key 3 :

Key 4 :

That’s all

Let’s try running a few commands against servers with our key installed:

jonas@hydra:~$ for i in {131..134}; do echo -n "Server number: $i: "; ssh 192.168.1.$i "racadm serveraction powerstatus"; done
 Server number: 131: Server power status: ON
 Server number: 132: Server power status: ON
 Server number: 133: Server power status: ON
 Server number: 134: Server power status: ON
 jonas@hydra:~$
 jonas@hydra:~$ for i in {1..4}; do echo -n "Server number: $i: "; ssh 192.168.1.17$i "racadm storage get vdisks"; done
 Server number: 1: Disk.Virtual.0:RAID.Integrated.1-1
 Server number: 2: Disk.Virtual.0:RAID.Integrated.1-1
 Server number: 3: Disk.Virtual.0:RAID.Integrated.1-1
 Server number: 4: Disk.Virtual.0:RAID.Integrated.1-1
 jonas@hydra:~$

All works well. Enjoy your iDRAC automation powers!

Redfish tutorial videos for beginners

I recently made a collection of videos for people to get started with Redfish on iDRAC using either PowerShell or Python. Hopefully they’ll be helpful for those starting out with the Redfish API on Dell EMC servers (or in general).

For scripts, please refer to the Dell EMC Github page here:

https://github.com/dell/iDRAC-Redfish-Scripting

 

Redfish with Python: Getting started with the environment

Redfish with Python: Basic scripts

Redfish with Python: Modifying server settings with SCP (Server Configuration Profiles)

 

Redfish with PowerShell: Setting up the environment

Redfish with PowerShell: Modifying server settings

Redfish with PowerShell: Modifying server settings with SCP (Server Configuration Profiles)

Leveraging OpenStack for Deep Learning & Machine Learning with GPU pass-through

As part of preparing for OpenStack days in Tokyo 2017 I built an environment to show how GPU pass-through can be used on OpenStack as a means of providing instances ready for Machine learning and Deep learning. This is a rundown of the process

Introduction

Deep Learning and Machine Learning have in recent years grown to become increasingly vital in the advancement of humanity in key areas such as life sciences, medicine and artificial intelligence. Traditionally it has been difficult and costly to create scalable, self-service environments to enable developers and end users alike to leverage these technological advancements. In this post we’ll look at the practical steps for the process of enable GPU powered virtual instances on Red Hat OpenStack. These can in turn be utilized by research staff to run in-house or commercial software for Deep Learning and Machine Learning.

Benefits

Virtual instances for Deep Learning and Machine Learning become easy and quick to create and consume. The addition of GPU powered Nova compute nodes can be done smoothly with no impact to existing cloud infrastructure. Users can choose from multiple GPU types and virtual machine types and the Nova Scheduler will be aware of where the required GPU resources reside for instance creation.

Prerequisites

This post describes how to modify key OpenStack services on an already deployed cloud to allow for GPU pass-through and subsequent assignment to virtual instances. As such it assumes an already functional Red Hat OpenStack overcloud is available. The environment used for the example in this document is running Red Hat OSP10 (Newton) on Dell EMC PowerEdge servers. The GPU enabled servers used for this example are PowerEdge C4130’s with NVIDIA M60 GPUs.

Process outline

After a Nova compute node with GPUs has been added to the cluster using Ironic bare-metal provisioning the following steps are taken:

  • Disabling the Nouveau driver on the GPU compute node
  • Enabling IOMMU in the kernel boot options
  • Modifying the Nova compute service to allow PCIe pass-through
  • Modifying the Nova scheduler service to filter on the GPU ID
  • Creating a flavor utilizing the GPU ID

Each step is described in more detail below.

Disabling the Nouveau driver on the GPU compute node

On the Undercloud, list the current Overcloud server nodes

[stack@toksc-osp10b-dir-01 ~]$ nova list

+--------------------------------------+-------------------------+--------+------------+-------------+---------------------+
| ID                                   | Name                    | Status | Task State | Power State | Networks            |
+--------------------------------------+-------------------------+--------+------------+-------------+---------------------+
| 8449f79f-fc17-4927-a2f3-5aefc7692154 | overcloud-cephstorage-0 | ACTIVE | -          | Running     | ctlplane=192.0.2.14 |
| ac063e8d-9762-4f2a-bf19-bd90de726be4 | overcloud-cephstorage-1 | ACTIVE | -          | Running     | ctlplane=192.0.2.9  |
| b7410a12-b752-455c-8146-d856f9e6c5ab | overcloud-cephstorage-2 | ACTIVE | -          | Running     | ctlplane=192.0.2.12 |
| 4853962d-4fd8-466d-bcdb-c62df41bd953 | overcloud-cephstorage-3 | ACTIVE | -          | Running     | ctlplane=192.0.2.17 |
| 6ceb66b4-3b70-4171-ba4a-e0eff1f677a9 | overcloud-compute-0     | ACTIVE | -          | Running     | ctlplane=192.0.2.16 |
| 00c7d048-d9dd-4279-9919-7d1c86974c46 | overcloud-compute-1     | ACTIVE | -          | Running     | ctlplane=192.0.2.19 |
| 2700095a-319c-4b5d-8b17-96ddadca96f9 | overcloud-compute-2     | ACTIVE | -          | Running     | ctlplane=192.0.2.21 |
| 0d210259-44a7-4804-b084-f2af1506305b | overcloud-compute-3     | ACTIVE | -          | Running     | ctlplane=192.0.2.15 |
| e469714f-ce40-4b55-921e-bcadcb2ae231 | overcloud-compute-4     | ACTIVE | -          | Running     | ctlplane=192.0.2.10 |
| fefd2dcd-5bf7-4ac5-a7a4-ed9f70c63155 | overcloud-compute-5     | ACTIVE | -          | Running     | ctlplane=192.0.2.13 |
| 085cce69-216b-4090-b825-bdcc4f5d6efa | overcloud-compute-6     | ACTIVE | -          | Running     | ctlplane=192.0.2.20 |
| 64065ea7-9e69-47fe-ad87-ed787f671621 | overcloud-compute-7     | ACTIVE | -          | Running     | ctlplane=192.0.2.18 |
| cff03230-4751-462f-a6b4-6578bd5b9602 | overcloud-controller-0  | ACTIVE | -          | Running     | ctlplane=192.0.2.22 |
| 333b84fc-142c-40cb-9b8d-1566f7a6a384 | overcloud-controller-1  | ACTIVE | -          | Running     | ctlplane=192.0.2.24 |
| 20ffdd99-330f-4164-831b-394eaa540133 | overcloud-controller-2  | ACTIVE | -          | Running     | ctlplane=192.0.2.11 |
+--------------------------------------+-------------------------+--------+------------+-------------+---------------------+

Compute nodes 6 and 7 are equipped with NVIDIA M60 GPU cards. Node 6 will be used for this example.

From the Undercloud, SSH to the GPU compute node:

[stack@toksc-osp10b-dir-01 ~]$ ssh heat-admin@192.0.2.20
Last login: Tue May 30 06:36:38 2017 from gateway
[heat-admin@overcloud-compute-6 ~]$
[heat-admin@overcloud-compute-6 ~]$

Verify that the NVIDIA GPU cards are present and recognized:
[heat-admin@overcloud-compute-6 ~]$ lspci -nn | grep NVIDIA
04:00.0 VGA compatible controller [0300]: NVIDIA Corporation GM204GL [Tesla M60] [10de:13f2] (rev a1)
05:00.0 VGA compatible controller [0300]: NVIDIA Corporation GM204GL [Tesla M60] [10de:13f2] (rev a1)
84:00.0 VGA compatible controller [0300]: NVIDIA Corporation GM204GL [Tesla M60] [10de:13f2] (rev a1)
85:00.0 VGA compatible controller [0300]: NVIDIA Corporation GM204GL [Tesla M60] [10de:13f2] (rev a1)

Use the device ID obtained in the previous command to check if the Nouveau driver is currently in use for the GPUs:
[heat-admin@overcloud-compute-6 ~]$ lspci -nnk -d 10de:13f2
04:00.0 VGA compatible controller [0300]: NVIDIA Corporation GM204GL [Tesla M60] [10de:13f2] (rev a1)
                Subsystem: NVIDIA Corporation Device [10de:115e]
                Kernel driver in use: nouveau
                Kernel modules: nouveau

 

Disable the Nouveau driver and enable IOMMU in the kernel boot options:

[heat-admin@overcloud-compute-6 ~]$ sudo su -
Last login: 火  5月 30 06:37:02 UTC 2017 on pts/0
[root@overcloud-compute-6 ~]#
[root@overcloud-compute-6 ~]# cd /boot/grub2/

Make a backup of the grub.cfg file before modifying it:
[root@overcloud-compute-6 grub2]# cp -p grub.cfg grub.cfg.orig.`date +%Y-%m-%d_%H-%M`
[root@overcloud-compute-6 grub2]# vi grub.cfg

Modify the following line and append the Noveau blacklist and Intel IOMMU options:
linux16 /boot/vmlinuz-3.10.0-514.2.2.el7.x86_64 root=UUID=a69bf0c7-8d41-42c5-b1f0-e64719aa7ffb ro console=tty0 console=ttyS0,115200n8 crashkernel=auto rhgb quiet

After modification:
linux16 /boot/vmlinuz-3.10.0-514.2.2.el7.x86_64 root=UUID=a69bf0c7-8d41-42c5-b1f0-e64719aa7ffb ro console=tty0 console=ttyS0,115200n8 crashkernel=auto rhgb quiet modprobe.blacklist=nouveau intel_iommu=on iommu=pt

Also modify the rescue boot option:
linux16 /boot/vmlinuz-0-rescue-e1622fe8eb7d44d0a2d57ce6991b2120 root=UUID=a69bf0c7-8d41-42c5-b1f0-e64719aa7ffb ro console=tty0 console=ttyS0,115200n8 crashkernel=auto rhgb quiet

After modification:
linux16 /boot/vmlinuz-0-rescue-e1622fe8eb7d44d0a2d57ce6991b2120 root=UUID=a69bf0c7-8d41-42c5-b1f0-e64719aa7ffb ro console=tty0 console=ttyS0,115200n8 crashkernel=auto rhgb quiet modprobe.blacklist=nouveau intel_iommu=on iommu=pt

Make the same modifications to “/etc/defaults/grub”:
[heat-admin@overcloud-compute-6 ~]$ vi /etc/default/grub

Re-generate the GRUB configuration files with grub2-mkconfig:
[root@overcloud-compute-6 grub2]# grub2-mkconfig -o /boot/grub2/grub.cfg
Generating grub configuration file ...
Found linux image: /boot/vmlinuz-3.10.0-514.2.2.el7.x86_64
Found initrd image: /boot/initramfs-3.10.0-514.2.2.el7.x86_64.img
Found linux image: /boot/vmlinuz-0-rescue-e1622fe8eb7d44d0a2d57ce6991b2120
Found initrd image: /boot/initramfs-0-rescue-e1622fe8eb7d44d0a2d57ce6991b2120.img
done

Reboot the Nova compute node:
[root@overcloud-compute-6 grub2]# reboot
PolicyKit daemon disconnected from the bus.
We are no longer a registered authentication agent.
Connection to 192.0.2.20 closed by remote host.
Connection to 192.0.2.20 closed.<\pre>

After the reboot is complete, SSH to the node to verify that the Nouveau module is no longer active for the GPUs:

[stack@toksc-osp10b-dir-01 ~]$ ssh heat-admin@192.0.2.20
Last login: Tue May 30 07:39:42 2017 from 192.0.2.1
[heat-admin@overcloud-compute-6 ~]$
[heat-admin@overcloud-compute-6 ~]$
[heat-admin@overcloud-compute-6 ~]$
[heat-admin@overcloud-compute-6 ~]$ lspci -nnk -d 10de:13f2
04:00.0 VGA compatible controller [0300]: NVIDIA Corporation GM204GL [Tesla M60] [10de:13f2] (rev a1)
                Subsystem: NVIDIA Corporation Device [10de:115e]
                Kernel modules: nouveau

The Kernel module is present but not listed as being active. PCIe pass-through is now possible.

Modifying the Nova compute service to allow PCIe pass-through

From the Undercloud, SSH to the compute node and become root with sudo:

[stack@toksc-osp10b-dir-01 ~]$ ssh heat-admin@192.0.2.20
[heat-admin@overcloud-compute-6 ~]$ sudo su -
Last login: 火  5月 30 07:40:13 UTC 2017 on pts/0

Backup the nova.conf file and edit the configuration file:
[root@overcloud-compute-6 ~]# cd /etc/nova
[root@overcloud-compute-6 nova]# cp -p nova.conf nova.conf.orig.`date +%Y-%m-%d_%H-%M`
[root@overcloud-compute-6 nova]# vi nova.conf

Add the following two lines at the beginning of the “[DEFAULT]” section:
pci_alias = { "vendor_id":"10de", "product_id":"13f2", "device_type":"type-PCI", "name":"m60" }
pci_passthrough_whitelist = { "vendor_id": "10de", "product_id": "13f2" }

Note:
The values for “vendor_id” and “product_id” can be found in the output of “lspci -nn | grep NVIDIA” as shown earlier. Note that the PCIe alias and whitelist is made on a Vendor / Product basis. This means no specific data for each PCIe device is required and new cards of the same type can be added and used without having to modify the configuration file.

The value for “name” is arbitrary and can be anything. However, it will be used to filter on the GPU type later and a brief, descriptive name is suggested as best-practice. A value of “m60” is used in this example.

Restart the Nova compute service:

[root@overcloud-compute-6 nova]# systemctl restart openstack-nova-compute.service

Modifying the Nova scheduler service to filter on the GPU ID

On each of the Nova Controller nodes, perform the following steps:
From the Undercloud, SSH to the controller nodes and become root with sudo:

[stack@toksc-osp10b-dir-01 ~]$ ssh heat-admin@192.0.2.20
[heat-admin@overcloud-compute-6 ~]$ sudo su -
Last login: 火  5月 30 07:40:13 UTC 2017 on pts/0

Create a backup and then modify the nova.conf configuration file:
[root@ overcloud-controller-0 ~]# cd /etc/nova
[root@ overcloud-controller-0 ~]# cp -p nova.conf nova.conf.orig.`date +%Y-%m-%d_%H-%M`
[root@ overcloud-controller-0 ~]# vi nova.conf

Add the following three lines at the beginning of the “[DEFAULT]” section:
pci_alias = { "vendor_id":"10de", "product_id":"13f2", "device_type":"type-PCI", "name":"m60" }
pci_passthrough_whitelist = { "vendor_id": "10de", "product_id": "13f2" }
scheduler_default_filters = RetryFilter, AvailabilityZoneFilter, RamFilter, DiskFilter, ComputeFilter, ComputeCapabilitiesFilter, ImagePropertiesFilter, ServerGroupAntiAffinityFilter, ServerGroupAffinityFilter, PciPassthroughFilter

Note: Ensure to match the values for “vendor_id”, “product_id” and “name” with those used while modifying the nova.conf file on the Nova compute node.

Note: Also change “scheduler_use_baremetal_filters” from “False” to “True”

Restart the nova-scheduler service:

[root@ overcloud-controller-0 ~]# systemctl restart openstack-nova-scheduler.service

Creating a flavor utilizing the GPU ID

The only step remaining is to create a flavor to utilize the GPU. For this a flavor containing a PCIe filter matching the “name” value in the nova.conf files will be created.
Create the base flavor without PCIe passthrough alias:

[stack@toksc-osp10b-dir-01 ~]$ openstack flavor create gpu-mid-01 --ram 4096 --disk 15 --vcpus 4
+----------------------------+--------------------------------------+
| Field                      | Value                                |
+----------------------------+--------------------------------------+
| OS-FLV-DISABLED:disabled   | False                                |
| OS-FLV-EXT-DATA:ephemeral  | 0                                    |
| disk                       | 15                                   |
| id                         | 04447428-3944-4909-99d5-d5eaf6e83191 |
| name                       | gpu-mid-01                           |
| os-flavor-access:is_public | True                                 |
| properties                 |                                      |
| ram                        | 4096                                 |
| rxtx_factor                | 1.0                                  |
| swap                       |                                      |
| vcpus                      | 4                                    |
+----------------------------+--------------------------------------+

Check that the flavor has been created correctly:
[stack@toksc-osp10b-dir-01 ~]$ openstack flavor list
+--------------------------------------+------------+------+------+-----------+-------+-----------+
| ID                                   | Name       |  RAM | Disk | Ephemeral | VCPUs | Is Public |
+--------------------------------------+------------+------+------+-----------+-------+-----------+
| 04447428-3944-4909-99d5-d5eaf6e83191 | gpu-mid-01 | 4096 |   15 |         0 |     4 | True      |
+--------------------------------------+------------+------+------+-----------+-------+-----------+

Add the PCIe passthrough alias information to the flavor:
[stack@toksc-osp10b-dir-01 ~]$ openstack flavor set gpu-mid-01 --property "pci_passthrough:alias"="m60:1"

Note: The “m60:1” indicate that one (1) of the specified resource – in this case a GPU, is requested. If more than one GPU is required for a particular flavor, just modify the value. For example: “m60:2” for a dual-GPU flavor.

Verify that the flavor has been modified correctly:

[stack@toksc-osp10b-dir-01 ~]$ nova flavor-show gpu-mid-01
+----------------------------+--------------------------------------+
| Property                   | Value                                |
+----------------------------+--------------------------------------+
| OS-FLV-DISABLED:disabled   | False                                |
| OS-FLV-EXT-DATA:ephemeral  | 0                                    |
| disk                       | 15                                   |
| extra_specs                | {"pci_passthrough:alias": "m60"}     |
| id                         | 04447428-3944-4909-99d5-d5eaf6e83191 |
| name                       | gpu-mid-01                           |
| os-flavor-access:is_public | True                                 |
| ram                        | 4096                                 |
| rxtx_factor                | 1.0                                  |
| swap                       |                                      |
| vcpus                      | 4                                    |
+----------------------------+--------------------------------------+

That is all. Instances with the GPU flavor can now be created via the command line or the Horizon web interface.

Arduino SONAR

After seeing this awesome Arduino RADAR project by Dejan Nedelkovski I simply had to build one myself. It’s actually a SONAR though as it utilizes sound for detection rather than radio waves. It was a fairly quick and easy build but it requires both the Arduino sketch as well as a separate one for Processing to draw the GUI. Here it is in action:

Logitech / Logicool G13 cleaning / washing

After knocking over a full pint of beer into my Belkin ergonomic keyboard and my much loved Logitech/Logicool G13 programmable gaming keyboard I had to find a way to save them from the garbage bin.

Unfortunately the Belkin was beyond repair. Pressing any of the keys would result in gibberish and washing out the beer with water didn’t improve things. The G13 however could be taken apart more easily and I was happy to see that it can be separated into two parts which makes the keys very easy to clean off without affecting the underlying circuit boards.

Note that although the G13 had most of the keys fused together by the dried beer it still seemed to function better than the Belkin keyboard. The underlying circuit boards appeared undamaged or unaffected.

If you want to try this, start off with a few tools. I used a razor-knife and a small pair of scissors as well as a Phillips screwdriver. You’ll also need a sponge, dish washing liquid and a hair dryer.

g13_cleaning-3798

Carefully peal off the protective rubber feet so they don’t break. The scissors were useful here as the razor knife risk cutting the feet while removing them. They don’t have to come all the way off but I removed them anyway to get full access to the screws underneath.

g13_cleaning-3797

 

There are six screws that need to be removed in total and each is hidden behind a rubber foot or, as is the case with the middle one, a thin plastic seal. Once the rubber covers are removed, unscrew the six screws which hold the keyboard together:

g13_cleaning-37922

Once the screws are removed, use the razor knife to gently split the keyboard apart at the seams. I started at the joystick side, worked my way down and around from there. Finally the upper part could also be loosened although the dried beer held it together fairly well.

After the key part has been removed from the base it’ll look like this:

g13_cleaning-3788

g13_cleaning-3789

g13_cleaning-3791

Now the upper part with the keys can be washed with dishwashing liquid and a sponge to remove the beer / sugar / etc depending on what was spilled into it in the first place.

g13_cleaning-3793

Rinse and dry thoroughly with a hairdryer to ensure there is no water left between the keys. After that it’s just a matter to snap the key section back on top of the base, screw in the screws and finally add the rubber covers / feet to the bottom of the keyboard. After the procedure the keyboard is good as new and works just fine when connected to the PC again.

g13_cleaning-3799