I want to use Manjaro in GCP compute engine with GUI but there isn't any image available in compute engine
You need to install Manjaro in your own machine first using something like VirtualBox. Then you can upload the local boot disk to GCS and use that.
See details here: https://cloud.google.com/compute/docs/images/importing-virtual-disks
Seems Manjaro is based on Arch but GCP only supports CentOS/Debian/Red Hat/Ubuntu
(https://cloud.google.com/compute/docs/images/importing-virtual-disks#supported_operating_systems)
Don't if it will work.
For GUI, you need to install X and VNC server then use vnc client to connect.
Besides what Cloud Ace already mentions, there's another resource I believe you might find of interest.
There is actually an ArchLinux dedicated repo in the official GCP GitHub page, which contains some instructions as per how to install ArchLinux into a GCE instance by either using a preconfigured image in the available public images in GCP or building yourself your own custom image. I believe the process of building an image could be attempted with Manjaro, given the fact that it is originally intended for ArchLinux. It has potential to work.
In the end, if the custom image building does not work out with Manjaro, you can always use the Arch Linux public image mentioned in the GitHub I shared (which is the minimal base Arch Linux image), and install the desktop environment you like.
Hope this helps.
Related
I'm new to Azure-Pipeline and struggling to put together a C++ oriented pipeline that uses camke which properly compiles, run tests and build documentation on Ubuntu, macOS, and Windows.
I managed the macOS and Ubuntu cases rather easily but am struggling with the Windows case not knowing what's installed and what's in system PATH for the given image & container I've selected.
Not being super familiar with the Azure-Platform I'm basically relying on commit-push-run-pipeline every single little change to my YAML file thus wasting time and resources.
I can't imagine that the only way is to blindly try out commands by commit, push and run the pipeline.
I managed to find a basic description of the currently (hopefully) available images here following the included software link for Windows link yoou end up on a comprehensive list of what's supposedly installed (I have some doubts on whether this documentation actually matches the content of the image). Calling some of those tools like cmake and choco, present in the above list, failed. Whether or not they're actually installed and in system PATH I have no idea.
Q1: Is there any way to locally test out an Azure-Pipeline YAML?
Q2: Is there any way to figure what is actually installed on a given image/container (without issuing a DIR /s from the root folder??)
Q3: Is it possible to connect to a running container (or is it a VM???) instance and directly tinker with it?
Q4: Alternatively, is it possible to run such an image locally (Docker)? Does it imply execution on a Windows machine or is that a standalone VM image?
EDIT: Found out about this question, although doesn't quite answer mine: Is there a tool to validate an Azure DevOps Pipeline locally?
Q1: Is there any way to locally test out an Azure-Pipeline YAML?
The answer is yes. You could create your private agent to execute the Azure-Pipeline YAML.
Self-hosted agents
Q2: Is there any way to figure what is actually installed on a given
image/container (without issuing a DIR /s from the root folder??)
Just as you know, we could check the document Software for the software installed on the agent. If you want to know the install the path of some software, you could check the debug log from the build task. For example, cmake. We could check the build log from the cmake task:
Q3: Is it possible to connect to a running container (or is it a
VM???) instance and directly tinker with it?
For the hosted agent, I am afraid the answer is not.
Q4: Alternatively, is it possible to run such an image locally
(Docker)? Does it imply execution on a Windows machine or is that a
standalone VM image?
The answer is yes, we could Run a self-hosted agent in Docker. And it imply execution on a Windows machine.
I would like to run a custom Docker image with GPU on Google Compute Engine.
I have built and pushed the image to the Google Container Registry.
It seems logical to use Container-Optimized OS for a host machine in Google Cloud Engine since I don't need any extra soft on the host machine except Docker, Nvidia GPU drivers and nvidia-container-runtime.
I managed to install nvidia-drivers with this solution.
But I can't run my Docker image with GPU (using --gpu all option) without nvidia-container runtime. This step is specified in official Docker documentation.
Is there a way to install nvidia-container-runtime on Container-Optimized OS in Google Cloud VM?
You don't have to set --gpu all, because this is the default option for nvidia-container-runtime. The assumption, that you don't need anything else is wrong, because it requires libnvidia-container.
To precisely answer the question: No, because libnvidia-container needs to be installed on the OS and nvidia-container-runtime needs to be installed within the K8s container. The one exposes an interface - and the other connects it. And so the one is useless without the other.
I am using the compute engine of the google cloud platform to do computations.
I am using Ubuntu as the OS and every time I create a new instance, I have to install the software I need from scratch, including the build-essential.
I am pretty sure there is a way to specify the software I would like to have in my VM but couldn´t figure out a straightforward way to do it.
You should use GCE custom images to create VM images with pre-installed software that you need.
Alternatively, you can consider using startup scripts in which you can install software during VM startup. But in contrast to custom images it will increase VM startup time, because startup script will be running during VM startup.
For some time I am managing EC2 (Windows Boxes), RDS and S3 on AWS.
I do know manual steps that must be made in order to set up lets say a normal box (DB, Storage and Server. I heard about Vagrand, but everywhere I looked it mainly talks about Linux boxes on AWS.
My main question is: Is Vagrand a tool that will save me time for deyploment (windows), or should I not use it at all (in Windows scenario).
Vagrant plays nicely with AWS (via vagrant-aws plugin).
Vagrant seems to play nicely with Windows as well since version 1.6 and the introduction of WinRM support (ssh alternative for Windows).
However AWS plugin doesn't support WinRM communicator yet. So you'll need to pre-bake your Windows AMIs with SSH service pre installed, if you want vagrant to provision it.
Update (29/03/2016): Thanks to Rafael Goodman for pointing to vagrant-aws-winrm plugin as a possible workaround.
The Google Compute Engine announcement mentions support for RHEL, SUSE, and FreeBSD. On VM creation only Debian and CentOS are available. Is FreeBSD support still being worked on or do I need to create my own disk image to start with?
FreeBSD is now supported by the service, but images are not provided by Google. Paul Rashidi has posted detailed steps for creating a FreeBSD image.
Later in the same thread, Dave Cottlehuber shares a tool he created to make installation easier.
For RHEL and SUSE, there is a signup link in the Premium Operating Systems documentation.
update: On June 9th, we published a video walking through the details of How to build a custom image for Compute Engine.
I've been working on a script to build images for FreeBSD on Google Compute Engine, see:
https://plus.google.com/112202779615695172291/posts/eYajb8JKerY
for more details.
Anther option for building images can be found here:
https://github.com/daveish/freebsd-gce-tools