Create Machine Images Using gcloud compute
Coursera · Google Cloud · Updated
Platform rating
4.5/5
AI Tutor Rating
8.3/10
Duration
Self-paced
Classes
6
This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab provides a quick introduction on how to create a VM machine image using gcloud compute to preserve the configuration, metadata, permissions, and disk data of the VM.
Create Machine Images Using gcloud compute is a self-paced lab on Coursera that provides hands-on practice creating virtual machine images within the Google Cloud console. The course teaches how to use the gcloud compute command-line tool to preserve a VM's configuration, metadata, permissions, and disk data in a reusable image. This focused, practical skill is designed for developers, engineers, and cloud practitioners who need to manage and standardize infrastructure on Google Cloud Platform.
What you'll learn in Create Machine Images Using gcloud compute
Our Review of Create Machine Images Using gcloud compute
Create Machine Images Using gcloud compute is structured as a single, focused hands-on lab, which is both its greatest strength and its primary limitation. The teaching format is purely practical, dropping learners directly into the Google Cloud console to follow guided steps. This approach is highly effective for building muscle memory with the gcloud CLI and the console interface, ensuring that by the end, a learner can execute the specific task of creating a VM image from scratch. The self-paced nature and lack of prerequisites make it accessible, but the depth is intentionally narrow, covering only this one operation without broader context on image management strategies or lifecycle.
The course's value is tightly linked to its low $10 price point and the inclusion of a certificate. For the cost, it delivers a concrete, job-relevant skill that can be completed in a short sitting, offering immediate utility for someone needing to learn this specific procedure. However, the curriculum suggests a learner will be able to perform this isolated technical task but may not understand when or why to use machine images in a broader DevOps or MLOps workflow. It serves as a precise tool in a toolbox rather than a comprehensive lesson on infrastructure as code.
Pros and cons of Create Machine Images Using gcloud compute
Pros
- Provides immediate, practical hands-on experience in the live Google Cloud console.
- Focuses on a specific, high-utility skill for infrastructure management and automation.
- Self-paced format with no prerequisites makes it highly accessible for beginners.
- Low $10 cost offers good value for a targeted, certificate-bearing skill lab.
- Directly teaches industry-relevant gcloud CLI commands for real-world tasks.
Things to consider
- Extremely narrow scope covers only one procedure without broader conceptual context.
- Lacks any instructional video or deep-dive explanations, relying solely on lab instructions.
- As a single lab, it does not constitute a full course and offers limited learning breadth.
Who should take Create Machine Images Using gcloud compute?
This course is best for Google Cloud users, such as developers or junior engineers, who need to quickly learn the exact steps for creating a VM machine image via the command line. It fits someone with immediate, practical need for this skill, preferring a hands-on, learn-by-doing format over theoretical lectures. It is also suitable for learners building a portfolio of specific, certificate-demonstrated cloud skills.
Create Machine Images Using gcloud compute at a glance
| Provider | Coursera |
|---|---|
| Instructor | Google Cloud |
| Level | Beginner |
| Time to complete | Self-paced |
| Pricing | $10 |
| Certificate | Certificate |
| Prerequisites | None |
Fit
Best for
Not ideal for
The bottom line on Create Machine Images Using gcloud compute
Create Machine Images Using gcloud compute is a cost-effective, targeted lab that successfully teaches a precise technical skill. It delivers exactly what it promises, a hands-on walkthrough for creating VM images, making it a worthwhile quick win for practitioners needing this capability. However, learners should not expect a broad course, as it is a single-topic module without deeper strategic instruction.
Create Machine Images Using gcloud compute: frequently asked questions
What exactly will I learn to do in the Create Machine Images Using gcloud compute lab?
You will learn to create a VM machine image using the gcloud compute command-line tool, preserving the VM's configuration, metadata, permissions, and disk data, all within a hands-on Google Cloud console lab.
Do I need any prior experience with Google Cloud or the command line to take this course?
No, the course lists no prerequisites, making it accessible for beginners. However, comfort with following technical instructions in a console is beneficial.
Is the certificate from this $10 Coursera lab worth it for my resume?
The certificate verifies a specific, practical Google Cloud skill, which can be valuable for demonstrating hands-on competency in infrastructure tasks, especially for entry-level cloud roles.
How does this self-paced lab compare to a full Coursera course on Google Cloud?
This lab is a single, focused hands-on activity, whereas a full course would include video lectures, multiple modules, and broader conceptual knowledge. This lab is for learning one specific procedure quickly.
How can I get the most value out of the Create Machine Images Using gcloud compute hands-on lab?
To get the most value, follow the lab steps carefully, experiment with the commands in the provided console, and take notes on the gcloud syntax and the image creation process for future reference.