Significant features include operator-friendly additions like Ironic Rescue Mode, a new drag-and-drop method for creating orchestration templates, and registering RBAC policies in project code as opposed to separate project files. Additional new features and projects with emerging applications like support for vGPUs (AI/machine learning, HPC), Cinder multi-attach (HA, enterprise support), OpenStack-Helm for containerizing OpenStack services (edge), and a CNI daemon in Kuryr (container networking).
For example, a single Intel GVT-g or a NVIDIA GRID vGPU physicalGraphics Processing Unit (pGPU) can be virtualized as multiple virtual GraphicsProcessing Units (vGPUs) if the hypervisor supports the hardware driver and hasthe capability to create guests using those virtual devices.
OpenStack gets support for virtual GPUs and new container features
OpenStack is the standard for private clouds and is also available as a service via dozens of public cloud providers around the world. At its core, OpenStack is an open source integration engine that provides APIs to orchestrate bare metal, virtual machine and container resources on a single network. The same OpenStack code powers a global network of public and private clouds, backed by the largest ecosystem of technology providers, to enable cost savings, control and portability.
The main driver for most OpenStack deployments is the cost benefit of using a leaner and more open IaaS. Canonical's Charmed OpenStack also offers a range of cloud services, and compatibility with hybrid cloud and multi-cloud operations tools. While legacy virtualisation continues to be important, the future is cloud APIs and container-based operations, which Charmed OpenStack delivers.
The Zed release was a collaboration between over 710 contributors from more than 140 organizations and 44 countries, resulting in 15,500 changes in 27 weeks. Feature advancements in Zed include security enhancements, such as OAuth 2.0 support in Keystone, and hardware enablement features, such as new backend drivers for Cinder. Nova also supports virtual IOMMU devices on x86 hosts using the libvirt driver.
OpenStack is an infrastructure platform that can launch bare metal, virtual machines (VMs), graphics processing units (GPUs) and container architectures. The OpenStack community has constantly been evolving to include technologies such as Ceph, Kubernetes, and Tensorflow, with over 40 million cores already in production and more than 180 public cloud data centers running worldwide.
Kata Containers is an open source community working to build a secure container runtime with lightweight virtual machines that feel and perform like containers, but provide stronger workload isolation using hardware virtualization technology as a second layer of defense.
Since launching in December 2017, the community successfully merged the best parts of Intel Clear Containers with Hyper.sh RunV and scaled to include support for major architectures including AMD64, ARM, IBM p-series and IBM z-series in addition to x86_64. Kata Containers also supports multiple hypervisors including QEMU, Cloud-Hypervisor and Firecracker and integrates with the containerd project among others.
A set of support limitations applies to virtualization in Red Hat Enterprise Linux 8 (RHEL 8). This means that when you use certain features or exceed a certain amount of allocated resources when using virtual machines in RHEL 8, Red Hat will not support these guests unless you have a specific subscription plan.
Features listed in Recommended features in RHEL 8 virtualization have been tested and certified by Red Hat to work with the KVM hypervisor on a RHEL 8 system. Therefore, they are fully supported and recommended for use in virtualization in RHEL 8.
Features listed in Unsupported features in RHEL 8 virtualization may work, but are not supported and not intended for use in RHEL 8. Therefore, Red Hat strongly recommends not using these features in RHEL 8 with KVM.
In addition, unless stated otherwise, all features and solutions used by the documentation for RHEL 8 virtualization are supported. However, some of these have not been completely tested and therefore may not be fully optimized.
Red Hat provides support with KVM virtual machines that use specific guest operating systems (OSs). For a detailed list of supported guest OSs, see the Certified Guest Operating Systems in the Red Hat KnowledgeBase.
The recommended machine types for KVM virtual machines on supported architectures, and the corresponding values for the --machine option, are as follows. Y stands for the latest minor version of RHEL 8.
For a list of guest OSs supported on RHEL hosts, RHV, or other virtualization solutions, see Certified Guest Operating Systems in Red Hat OpenStack Platform, Red Hat Virtualization, OpenShift Virtualization and Red Hat Enterprise Linux with KVM.
QEMU is an essential component of the virtualization architecture in RHEL 8, but it is difficult to manage manually, and improper QEMU configurations may cause security vulnerabilities. Therefore, using qemu-* command-line utilities, such as qemu-kvm is not supported by Red Hat. Instead, use libvirt utilities, such as virsh, virt-install, and virt-xml, as these orchestrate QEMU according to the best practices.
Note that S3-PR on a multipathed vDisk is supported in RHV. Therefore, if you require Windows Cluster support, Red Hat recommends using RHV as your virtualization solution. For details, see Cluster support on RHV guests.
Note that some of the unsupported features are supported on other Red Hat products, such as Red Hat Virtualization and Red Hat OpenStack platform. For more information, see Unsupported features in RHEL 8 virtualization.
By providing self-contained execution environments without the overhead of a full virtual machine, containers have become an appealing proposition for deploying applications at scale. The credit goes to Docker for making containers easy-to-use and hence making them popular. From enabling multiple engineering teams to play around with their own configuration for development, to benchmarking or deploying a scalable microservices architecture, containers are finding uses everywhere.
AI development is often deployed in container and virtualized environments to gain portability, efficiency, and scalability. NVIDIA AI Enterprise is certified for running AI workloads on mainstream container platforms such as VMware Tanzu, Red Hat OpenShift, HPE Ezmeral, and upstream Kubernetes to accelerate a diverse range of AI use cases across hybrid- or multi-cloud environments.
OpenStack Nova supports provisioning of virtual machines (VMs), bare metal and containers. True, BUT, Nova design started off as a virtual machine scheduler, with features specific to this use case. Nova enhancements to unify requesting any compute instance, be it VM, container or Bare Metal, while wonderful, unfortunately is convoluted at best, requiring the user to execute additional steps. Further, it does not yet support the more advanced requirements of bare metal provisioning such as storage and network configuration.
We do not intend to compete with Nova. Nova focuses on VM management and provides many advanced features like live migrating, availability zone, host aggregates, etc. The ironic driver allows to manage baremetals via Nova's API (which is unified for VMs, baremetals, and containers, but in fact, it's customized for VMs). Baremetal instance in Nova seems like a pretended VM which ocuppies all resources of the compute node, While Mogan is designed specifically for baremetals, it offers bare metals as first class resources to users, supporting variety of bare metal provisioning drivers including Ironic.
If you have specific hardware requirements for your project, or you are developing on one hardware platform and need to target another like Windows vs MacOS, you will need to use a virtual machine. Most other 'software only' requirements can be met by using containers.
It is entirely possible to use containers and virtual machines in unison although the practical use-cases may be limited. A virtual machine can be created that emulates a unique hardware configuration. An operating system can then be installed within this virtual machine's hardware. Once the virtual machine is functional and boots the operating system, a container runtime can be installed on the operating system. At this point we have a functional computational system with emulated hardware that we can install containers on.
One practical use for this configuration is experimentation for system on chip deployments. Popular system on chip computational devices like the Raspberry Pi, or BeagleBone development boards can be emulated as a virtual machine, to experiment with running containers on them before testing on the actual hardware.
Booting via the BIOS is available for hypervisors supporting fullvirtualization. In this case the BIOS has a boot order priority (floppy,harddisk, cdrom, network) determining where to obtain/find the boot image.
The content of the type element specifies the type of operating system tobe booted in the virtual machine. hvm indicates that the OS is onedesigned to run on bare metal, so requires full virtualization. linux(badly named!) refers to an OS that supports the Xen 3 hypervisor guest ABI.There are also two optional attributes, arch specifying the CPUarchitecture to virtualization, and machine referring to the machinetype. The Capabilities XML provides details on allowedvalues for these. If arch is omitted then for most hypervisor drivers,the host native arch will be chosen. For the test, ESX and VMWarehypervisor drivers, however, the i686 arch will always be chosen even onan x86_64 host. Since 0.0.1
When booting a domain using container based virtualization, instead of a kernel/ boot image, a path to the init binary is required, using the init element.By default this will be launched with no arguments. To specify the initial argv,use the initarg element, repeated as many time as is required. Thecmdline element, if set will be used to provide an equivalent to/proc/cmdline but will not affect init argv. 2ff7e9595c
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