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Elastic Google Cloud Infrastructure: Scaling and Automation Course

Elastic Google Cloud Infrastructure: Scaling and Automation Course Course

This accelerated course delivers core automation and scaling skills through practical labs—an ideal quick-upskill option for practicing IT pros.

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9.7/10 Highly Recommended

Elastic Google Cloud Infrastructure: Scaling and Automation Course on Coursera — This accelerated course delivers core automation and scaling skills through practical labs—an ideal quick-upskill option for practicing IT pros.

Pros

  • Excellent hands-on exposure to networking, load balancing, and autoscaling.
  • Well-scoped for busy professionals—can be completed in ~7 hours.
  • Labs reinforce practical application of concepts, not just theory.

Cons

  • Assumes prior exposure to foundational GCP; not suited for absolute beginners.
  • Lacks a capstone — learners should integrate modules into a broader project independently.

Elastic Google Cloud Infrastructure: Scaling and Automation Course Course

Platform: Coursera

What will you learn in Elastic Google Cloud Infrastructure: Scaling and Automation Course

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  • Securely interconnect on-premises infrastructure and Google Cloud networks.

  • Configure load balancing and autoscaling for Compute Engine VM instances.

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  • Automate infrastructure deployment using IaC and scripting techniques.

  • Utilize managed Google Cloud services and automate their provisioning.

Program Overview

Module 1: Introduction

⏳ ~10 min

  • Topics: Course overview, program context, target audience.

  • Hands-on: Guided through course structure and expectations.

Module 2: Interconnecting Networks

⏳ ~2 hours

  • Topics: VPCs, subnetworks, VPNs, firewall rules, hybrid cloud connectivity.

  • Hands-on: Labs to connect on-prem and GCP networks securely.

Module 3: Load Balancing & Autoscaling

⏳ ~2–3 hours

  • Topics: Internal/external load balancers, health checks, instance groups, autoscaling policies.

  • Hands-on: Configure and test load balancing with autoscaling groups in Compute Engine.

Module 4: Infrastructure Automation

⏳ ~2–3 hours

  • Topics: Infrastructure as Code (IaC), scripting with Deployment Manager/CLI.

  • Hands-on: Automate resource provisioning and configuration via scripts.

Module 5: Managed Services

⏳ ~2 hours

  • Topics: Overview of managed services (e.g., Cloud SQL, Cloud Storage), when and how to use them.

  • Hands-on: Deploy managed services and explore integrations via labs.

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Job Outlook

  • Equips Cloud and DevOps Engineers to design scalable, automated GCP environments.

  • Ideal for roles like Cloud Solution Architect, DevOps Engineer, and Site Reliability Engineer.

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FAQs

Is this course suitable for absolute beginners in Google Cloud?
No, it’s not ideal for total beginners. Assumes prior exposure to Google Cloud basics (VPCs, IAM, Compute). Beginners may struggle with advanced labs on networking and automation. Recommended to complete a GCP fundamentals course first. Best fit for those with at least 3–6 months of cloud familiarity.
How hands-on is the automation training in this course?
The course uses real labs for Deployment Manager and CLI scripting. Learners automate VM provisioning, load balancers, and services. Practical focus is on Infrastructure as Code (IaC). Scripts reinforce repeatable, production-style workflows. You’ll finish with working automated deployments on GCP.
What kind of job roles benefit from this course?
Designed for Cloud Engineers and DevOps professionals. Skills align with Site Reliability Engineering practices. Helpful for Cloud Solution Architects designing scalable systems. Automation focus appeals to IT pros moving into DevOps. Strengthens credentials for cloud-native infrastructure roles.
Does the course include a capstone project to test skills?
No, there’s no dedicated capstone project. Modules are standalone with guided labs. Learners are encouraged to integrate labs into personal projects. Real-world application is left to the student’s initiative. It’s best to supplement with a self-driven project for practice.
How long does it realistically take to complete this course?
Official duration is about 7–8 hours across modules. Most learners can finish within 1–2 days of focused study. Beginners may take longer revisiting foundational topics. Labs can extend depending on troubleshooting time. Designed as a quick upskill program for working professionals.

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