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The Tooling of AML 3304: A narrative story

Susan and Kirandeep had just graduated from Cestar college.

Kirandeep was so excited because she had just landed her dream job as an ML OPS Specialist.

Kirandeep couldn't wait to tell Susan all about it, and so she began to explain about the various tools she used in her job.

She told Susan about Ansible, which is a tool that helps with automation of cloud infrastructure.

With Ansible, Kirandeep can quickly and easily deploy her projects to the cloud.

Kirandeep also talked about Circle CI, which is a continuous integration and delivery platform. With Circle CI, Kirandeep can easily build and test her projects in the cloud, meaning she can deploy and manage her projects much faster. Finally, Kirandeep discussed GitLab, which is a version control system.

With GitLab, Kirandeep can save different versions of her projects and easily go back to a previous version if things don't work out with the current version.

Kirandeep was excited to be able to use these technologies in her new job, and she was very proud of herself for learning how to use them.

With these tools, she can now deploy her projects faster and easier, and she can also keep track of her projects and their different versions.

And that is how Susan and Kirandeep learned about the various tools and technologies used in Kirandeep's new job as an ML OPS Specialist.

1. What is Ansible? Answer: Ansible is a tool that helps with automation of cloud infrastructure.

2. What does Circle CI do? Answer: Circle CI is a continuous integration and delivery platform.

We can connect a project in

CIRCLECI.com⁠

to a GITLAB Project.

When a Developer commits a code change to the GITLAB Repository: This could be configured to run a Build Script on Gitlab to build the project and run test cases.

3. What is the purpose of GitLab? Answer: GitLab is a version control system that allows users to save different versions of their projects and easily go back to a previous version if necessary. GitLab gives us instrumentation (API Hooks) to connect to CI/CD Orchestration tools such as CircleCI. GitLab gives us better Project management support that other Source Code Repositories, including Git ISSUES.

4. How can Ansible help Kirandeep in her job? Answer: Ansible can help Kirandeep quickly and easily deploy her projects to the cloud. 5. What are the benefits of using Circle CI? Answer: The benefits of using Circle CI include being able to build and test projects in the cloud, meaning projects can be deployed and managed faster. 6. How can GitLab help Kirandeep manage her projects? Answer: With GitLab, Kirandeep can save different versions of her projects and easily go back to a previous version if things don't work out with the current version. 7. What is the overall data flow when using GitLab, Ansible, and Circle CI together? Answer: The overall data flow when using GitLab, Ansible, and Circle CI together is that developers can commit their code to GitLab, use Ansible to deploy it to the cloud, and use Circle CI to build and test their projects in the cloud. 8. What is the application architecture of how GitLab, Ansible, and Circle CI work together? Answer: The application architecture of how GitLab, Ansible, and Circle CI work together involves GitLab being used for version control, Ansible for automation of cloud infrastructure, and Circle CI for continuous integration and delivery. 9. How can using these technologies help Kirandeep? Answer: Using these technologies can help Kirandeep deploy her projects faster and easier, and also keep track of her projects and their different versions. 10. What is the main difference between Ansible and Circle CI? Answer: The main difference between Ansible and Circle CI is that Ansible helps with automation of cloud infrastructure, whereas Circle CI is a continuous integration and delivery platform.

Introduction to Ansible for ML Cloud Dev Ops Engineers

Ansible is a powerful automation platform for managing and configuring applications, systems, and cloud services. It is an open-source platform that can be used to automate tasks and provide a consistent configuration across multiple systems and environments. In this technical lecture, we will explore four use cases for Ansible in ML cloud DevOps environments.

Use Case 1: Automating Application Deployment

Ansible can be used to automate the deployment of applications quickly and easily. This includes configuring the necessary infrastructure, such as servers and databases, deploying the code, and running tests to ensure that the services are running correctly. By using Ansible, DevOps engineers can deploy applications to production faster and with fewer errors.

Use Case 2: Automating Infrastructure Provisioning

Ansible can be used to automate the provisioning of cloud infrastructure such as servers, databases, and storage. This makes it easier to scale up or scale down as needed, while at the same time ensuring that the infrastructure is configured correctly and securely.

Use Case 3: Automating Configuration Management

Ansible can be used to automate the management and configuration of services. This includes setting up and configuring applications, configuring security settings, and managing user accounts. This can help ensure that applications and services are always configured correctly and securely.

Use Case 4: Automating Continuous Delivery

Ansible can be used to automate the continuous delivery process, ensuring that applications are always up to date and deployed correctly. This includes running tests, deploying the application, and deploying any necessary configuration changes. This helps DevOps engineers keep applications running smoothly and securely.

Conclusion

Ansible is a powerful automation platform that can be used to automate tasks and provide a consistent configuration across multiple systems and environments in ML cloud DevOps environments. This technical lecture has explored four use cases for Ansible, demonstrating how it can be used to automate application deployment, infrastructure provisioning, configuration management, and continuous delivery.

PYTHON CODE Sample:

# Configure Ansible on your machine

$ pip install ansible

# Create directory structure

$ mkdir ~/ansible-tutorial

$ mkdir ~/ansible-tutorial/files

$ mkdir ~/ansible-tutorial/inventory

$ mkdir ~/ansible-tutorial/playbooks

# Create an inventory file

$ touch ~/ansible-tutorial/inventory/hosts

# Create a playbook

$ touch ~/ansible-tutorial/playbooks/example.yml

# Create a template file

$ touch ~/ansible-tutorial/files/template.j2

# Write our playbook

$ nano ~/ansible-tutorial/playbooks/example.yml

---

- name: Example playbook

hosts: all

tasks:

- name: Copy the template file

template:

src: template.j2

dest: /etc/example.conf

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