[Apr 04, 2024] 305-300 Exam Dumps, 305-300 Practice Test Questions [Q23-Q43]

Explanation
Docker stack is a command that allows users to deploy and manage a stack of services on a Docker Swarm cluster. A stack is a group of interrelated services that share dependencies and can be orchestrated and scaled together. A stack is typically defined by a Compose file, which is a YAML file that describes the services, networks, volumes, and other resources of the stack. To use docker stack to run a Compose file on a Swarm, the user must first create and initialize a Swarm cluster, which is a group of machines (nodes) that are running the Docker Engine and are joined into a single entity. The Swarm cluster has one or more managers, which are responsible for maintaining the cluster state and orchestrating the services, and one or more workers, which are the nodes that run the services.
When the user runs docker stack deploy with a Compose file, the command parses the file and creates the services as specified. However, docker stack does not build or upload the images referenced in the Compose file to any registry. Instead, it instructs the Swarm nodes to pull the images from a registry, which can be the public Docker Hub or a private registry. The user must ensure that the images are available in the registry before deploying the stack, otherwise the deployment will fail. The user can use docker build and docker push commands to create and upload the images to the registry, or use an automated build service such as Docker Hub or GitHub Actions. The user must also make sure that the image names and tags in the Compose file match the ones in the registry, and that the Swarm nodes have access to the registry if it is private. By pulling the images from a registry, docker stack ensures that the Swarm nodes have the same and latest version of the images, and that the images are distributed across the cluster in an efficient way.
The other options are not correct. Docker stack does not build the images locally or on the Swarm nodes, nor does it copy or transfer the images to the Swarm nodes. Dockerstack also does not pass the images to the Swarm master, as this would create a bottleneck and a single point of failure. Docker stack relies on the registry as the source of truth for the images, and delegates the image pulling to the Swarm nodes. References:
* Deploy a stack to a swarm | Docker Docs1
* docker stack deploy | Docker Docs2
* docker build | Docker Docs3
* docker push | Docker Docs4

Explanation
Nested page table extensions, such as Intel Extended Page Table (EPT) or AMD Rapid Virtualization Indexing (RVI), are hardware features that facilitate the virtualization of memory. They allow the CPU to perform the translation of guest virtual addresses to host physical addresses in a single step, without the need for software-managed shadow page tables. This reduces the overhead and complexity of memory management for virtual machines, and improves their performance and isolation. Nested page table extensions do not directly affect the virtualization of other hardware components, such as network interfaces, host bus adapters, hard disks, or IO cache.
References:
* Second Level Address Translation – Wikipedia
* c – What is use of extended page table? – Stack Overflow
* Hypervisor From Scratch – Part 4: Address Translation Using Extended …

Explanation
The purpose of the kubelet service in Kubernetes is to run containers on the worker nodes according to the Kubernetes configuration. The kubelet is an agent or program that runs on each node and communicates with the Kubernetes control plane. It receives a set of PodSpecs that describe the desired state of the pods that should be running on the node, and ensures that the containers described in those PodSpecs are running and healthy. The kubelet also reports the status of the node and the pods back to the control plane. The kubelet does not manage containers that were not created by Kubernetes. References:
* Kubernetes Docs – kubelet
* Learn Steps – What is kubelet and what it does: Basics on Kubernetes

Explanation
The output of xl list shows the state of the domains. The domain with ID 6, Ubuntu, has a state of “b-“. This means that the domain is blocked, which means it is idle or waiting for I/O.
https://xenbits.xen.org/docs/unstable/man/xl.1.html

* Both Vagrant and Docker can share directories from the host file system to a guest. This allows the guest to access files and folders from the host without copying them. Vagrant uses the config.vm.synced_folder option in the Vagrantfile to specify the shared folders1. Docker uses the -v or –volume flag in the docker run command to mount a host directory as a data volume in the container2.
* Both Vagrant and Docker can download required base images. Base images are the starting point for creating a guest environment. Vagrant uses the config.vm.box option in the Vagrantfile to specify the base image to use1. Docker uses the FROM instruction in the Dockerfile to specify the base image to use2. Both Vagrant and Docker can download base images from public repositories or local sources.
* Both Vagrant and Docker can apply changes to a base image. Changes are modifications or additions to the base image that customize the guest environment. Vagrant uses provisioners to run scripts or commands on the guest after it is booted1. Docker uses instructions in the Dockerfile to execute commands on the baseimage and create a new image2. Both Vagrant and Docker can save the changes to a new image or discard them after the guest is destroyed.
* Vagrant and Docker differ in how they start system images. Vagrant starts system images as virtual machines by default, using a provider such as VirtualBox, VMware, or Hyper-V1. Docker starts system images as containers by default, using the native containerization functionality on macOS, Linux, and Windows2. Containers are generally more lightweight and faster than virtual machines, but less secure and flexible. References: 1: Vagrant vs. Docker | Vagrant | HashiCorp Developer 2: Vagrant vs Docker:
Which Is Right for You? (Could Be Both) – Kinsta Web Development Tools

unshare

/etc/docker/daemon.json

Explanation
Containerd is an industry-standard container runtime that uses Runc (a low-level container runtime) by default, but can be configured to use others as well1. Containerd manages the complete container lifecycle of its host system, from image transfer and storage to containerexecution and supervision1. It supports the standards established by the Open Container Initiative (OCI)1. Containerd does not require the Docker engine and Docker CLI to be installed, as it can be used independently or with other container platforms2. Containerd is not a text file format, nor does it run in each Docker container or provide DHCP client functionality. Containerd is not the initial process run at the start of any Docker container, as that is the role of the container runtime, such as Runc3. References: 1 (search for “containerd”), 2 (search for “Containerd is an open source”), 3 (search for “It uses rune to start containers”).

Explanation
The Linux kernel module that must be loaded in order to use QEMU with hardware virtualization extensions is KVM (Kernel-based Virtual Machine). KVM is a full virtualization solution that allows a user space program (such as QEMU) to utilize the hardware virtualization features of various processors (such as Intel VT or AMD-V). KVM consists of a loadable kernel module, kvm.ko, that provides the core virtualization infrastructure and a processor specific module, kvm-intel.ko or kvm-amd.ko. KVM must be loaded into the kernel of the host system in order to use the virtualization extensions of the host system’s CPU. This enables QEMU to run multiple virtual machines with unmodified Linux or Windows images, each with private virtualized hardware. KVM is integrated with QEMU, so there is no need to load it into the kernel of each virtual machine or the first virtual machine. KVM also does not require paravirtualization, which is a technique that modifies the guest operating system to communicate directly with the hypervisor, bypassing the emulation layer. References:
* Features/KVM – QEMU
* Kernel-based Virtual Machine
* KVM virtualization on Red Hat Enterprise Linux 8 (2023)

Explanation
Container-based virtualization is a method of operating system-level virtualization that allows multiple isolated user spaces (containers) to run on the same host system1. Each container shares the same operating system kernel as the host, but has its own file system, libraries, and processes2. Therefore, the statements A and C are false, as containers do not run their own kernels or rely on hardware support from the CPU. The statement E is also false, as Linux does support container-based virtualization through various technologies, such as cgroups, namespaces, LXC, Docker, etc12. The statement B is true, as different containers may use different distributions of the same operating system, such as Debian, Ubuntu, Fedora, etc., as long as they are compatible with the host kernel3. The statement D is also true, as all containers run within the operating system kernel of the host system, which provides isolation and resource management for them12. References:
* 1: Containerization (computing) – Wikipedia.
* 2: What are containers? | Google Cloud.
* 3: What is Container-Based Virtualization? – StackHowTo.

Explanation
The WORKDIR instruction sets the working directory for any subsequent RUN, CMD, ENTRYPOINT, COPY and ADD instructions that follow it in the Dockerfile1. The RUN instruction executes commands in a new layer on top of the current image and commits the results2. The RUN cd command does not change the working directory for the next RUN instruction, because each RUN command runs in a new shell and a new environment3. Therefore, the file test is created in the root directory (/) of the container image, not in the /tmp directory. References:
* Dockerfile reference: WORKDIR
* Dockerfile reference: RUN
* difference between RUN cd and WORKDIR in Dockerfile

Explanation
The purpose of a .dockerignore file is to specify files that Docker does not submit to the Docker daemon when building a Docker image. A .dockerignore file is a text file that contains a list of files or directories that should be excluded from the build context, which is the set of files and folders that are available for use in a Dockerfile. By using a .dockerignore file, you can avoid sending files or directories that are large, contain sensitive information, or are irrelevant to the Docker image to the daemon, which can improve the efficiency and security of the build process. The other options are incorrect because they do not describe the function of a
.dockerignore file. Option A is wrong because a .dockerignore file does not affect the files existing in a Docker image, but only the files sent to the daemon during the build. Option C is wrong because a .dockerignore file does not exist in the root file system of containers, but in the same directory as the Dockerfile. Option D is wrong because a .dockerignore file does not affect the volumes that Docker attaches to a container, but only the files included in the build context. Option E is wrong because a .dockerignore file does not affect the parts of a Dockerfile that are executed, but only the files available for use in a Dockerfile. References:
* What are .dockerignore files, and why you should use them?
* Dockerfile reference | Docker Docs
* How to use .dockerignore and its importance – Shisho Cloud

Explanation
Cloud-init is a tool that processes configurations and runs through five stages during the initial boot of Linux VMs in a cloud. It allows users to customize a Linux VM as it boots for the first time, by applying user data to the instance. User data can include scripts, commands, packages, files, users, groups, SSH keys, and more.
Cloud-init can also interact with various cloud platforms and services, such as Azure, AWS, OpenStack, and others. The purpose of cloud-init is to prepare the generic image of an laaS instance to fit a specific instance’s configuration, such as hostname, network, security, and application settings. References:
* Cloud-init – The standard for customising cloud instances
* Understanding cloud-init – Azure Virtual Machines
* Tutorial – Customize a Linux VM with cloud-init in Azure – Azure Virtual Machines

Explanation
Vagrant is a tool that allows users to create and configure lightweight, reproducible, and portable development environments. Vagrant supports multiple providers, which are the backends that Vagrant uses to create and manage the virtual machines. By default, VirtualBox is the default provider for Vagrant. VirtualBox is still the most accessible platform to use Vagrant: it is free, cross-platform, and has been supported by Vagrant for years. With VirtualBox as the default provider, it provides the lowest friction for new users to get started with Vagrant. However, users can also use other providers, such as VMware, Hyper-V, Docker, or LXC, depending on their preferences and needs. To use another provider, users must install it as a Vagrant plugin and specify it when running Vagrant commands. Users can also change the default provider by setting the VAGRANT_DEFAULT_PROVIDER environmental variable. References:
* Default Provider – Providers | Vagrant | HashiCorp Developer1
* Providers | Vagrant | HashiCorp Developer2
* How To Set Default Vagrant Provider to Virtualbox3

Explanation
The option dom0_mem is used to set the initial and maximum memory size of the Domain-0, which is the privileged domain that starts first and manages the unprivileged domains (DomU) in Xen. The option dom0_mem must be specified in the bootloader configuration, such as GRUB or GRUB2, when Xen is booted.
This ensures that the Domain-0 kernel can allocate memory for storing memory metadata and network related parameters based on the boot time amount of memory. If the option dom0_mem is not specified in the bootloader configuration, the Domain-0 will use all the available memory on the host system by default, which may cause performance and security issues. References:
* Managing Xen Dom0s CPU and Memory
* Xen Project Best Practices
* Dom0 Memory – Where It Has Not Gone