Pass the LPI DevOps Tools Engineer 701-100 Questions and answers with CertsForce

In Docker Swarm, to list the nodes in the cluster, you use the docker node ls command. This command displays information about all nodes in the Swarm, including their status, availability, and roles.

docker node ls: This is the correct command to list the nodes in a Docker Swarm cluster.

The other options are incorrect:

A: docker-swarm listnodes is not a valid Docker command.

B: docker engine ls lists Docker engines but not specifically Swarm nodes.

D: docker machine ls lists Docker machines managed by Docker Machine, not Swarm nodes.

E: docker swarm nodes is not a valid command.

References:

Docker Documentation - node ls

The git push command is used to upload local repository content to a remote repository. Pushing is how you transfer commits from your local repository to a remote repository. It is the command used to copy local commits to a remote repository.

References: Git documentation

Container virtualization has significant implications for DevOps practices, and the two main implications are:

Decoupling of Packaging and Infrastructure: Containers encapsulate an application and its dependencies into a single package. This means the application can run consistently across different environments without being affected by differences in the underlying infrastructure. This decoupling facilitates more reliable deployments and easier migration between environments.

Testing Under Production Conditions: Containers can replicate production environments on a developer’s local machine or in a CI/CD pipeline. This allows developers to test their applications under conditions that closely mimic the production environment, which can lead to identifying issues early and ensuring the software behaves as expected when deployed.

The other options are not correct:

Detailed Knowledge of IT Infrastructure: Containers abstract away much of the underlying infrastructure details, so developers do not need in-depth knowledge of it.

Complicating Deployment: Containers simplify deployment through standardization and automation, rather than complicating it.

Application Specific Adjustment: Containers are designed to run applications without the need for significant adjustments specific to the container platform, provided that the container image is correctly configured.

References:

Docker Documentation

Kubernetes Documentation

In Docker, the run subcommand is used to create and start a new container from an image. The full command typically includes the image name and any additional parameters needed to configure the container.

References:

Docker Documentation - run

In a continuous delivery pipeline, artifacts are the final outputs produced during the build and integration stages. These artifacts are then deployed to different environments for testing and production.

Executable Applications: Artifacts can include executable files like .exe or .jar packages that are ready to be run.

Compiled Packages: Precompiled packages for installation via package managers (e.g., .deb or .rpm files) are suitable artifacts.

Docker Images: Docker container images encapsulate the application and its dependencies, making them ideal artifacts for consistent deployment across environments.

References:

Continuous Delivery

Artifact Repository

Cloud-init is a tool used to initialize cloud instances and configure them on first boot. It integrates with the managed system by providing systemd units that are activated at different stages of the boot process to handle various initialization tasks.

systemd units: Cloud-init provides several systemd service units which are included in the boot process. These units handle the early initialization, configuration, and final setup stages.

The other options are incorrect:

A: There is no cloud-init-worker command.

C: Cloud-init does not replace the instance’s original init system.

D: Cloud-init does not provide a Linux kernel module.

E: There is no cloud-init-daemon service that keeps the instance in sync with the desired configuration.

References:

Cloud-Init Documentation - Systemd

Packer is a tool for creating machine and container images for multiple platforms from a single source configuration. A Packer template consists of various sections, but the builders section is mandatory.

builders: This section defines the builders that Packer will use to create the machine images. It specifies the platform, source image, and configuration required to build the final image.

The other sections are optional but can be included for more complex configurations:

A. images: Not a standard section in Packer templates.

B. provisioners: Optional section used for provisioning the image after it is built.

D. variables: Optional section for defining variables to be used in the template.

E. post-processors: Optional section for defining actions to be taken after the image is built.

References:

Packer Documentation - Template

In Prometheus, the scrape_config section of the configuration file defines how and which nodes (targets) should be scraped (monitored). This section specifies the endpoints Prometheus should scrape, the frequency of scraping, and any relabeling configurations.

scrape_config: This is the correct section where you define the targets to be monitored by Prometheus.

The other options are incorrect:

B. targets: This is part of scrape_config but not a top-level configuration section.

C. rules: This section is used to define alerting and recording rules, not targets.

D. listener: This is not a standard section in Prometheus configuration.

E. nodes: This is not a standard section in Prometheus configuration.

References:

Prometheus Documentation - Configuration