GCP Associate Cloud Engineer - Google Cloud Certification

Understand why enterprises and startups move from data centers to the cloud and learn the cloud's advantages with step-by-step visuals and real enterprise scenarios.

Explore why enterprises need thousands of servers, where servers provide web, file, email, and database services. Show how data centers host them to prevent single points of failure.

Data centers require specialized infrastructure—power, cooling, networking, and security. Learn how peak load provisioning and overprovisioning drive high upfront costs and risks for geographic expansion.

Explore how cloud computing mirrors the electricity grid by renting infrastructure, offering on-demand access, elasticity, and pay-as-you-go from providers like AWS, Azure, and Google Cloud.

Explore cloud advantages like pay for use and economies of scale. Experience stop guessing capacity, increased speed and agility, go global in minutes, and avoid undifferentiated heavy lifting.

Discover cloud terminology like elasticity, agility, global reach, availability, latency, and cost models from CapEx to opex, pay as you go, economies of scale, and avoiding undifferentiated heavy lifting.

Explore elastic cloud concepts, pay-as-you-go economics, and rapid agility through real scenarios. Identify high availability, geo distribution, low latency, economies of scale, and avoiding undifferentiated heavy lifting.

Discover how Google Cloud leverages its private fiber network and data-centric heritage to deliver fast, secure access to hundreds of compute, storage, analytics, and AI services.

Discover a structured, step-by-step path to learning cloud services with a global gateway via a cloud account, free beginner credits, and practical hands-on deployment across regions.

Create a Google Cloud account and start a free trial with $300 credit by entering personal and payment details, verifying your mobile number, and following the signup steps on cloud.google.com.

Maximize learning efficiency by speed watching and adjusting playback to 1.25x to 2x on the Udemy interface, starting at 1x and gradually increasing, prioritizing comprehension while optimizing every minute.

Explore regions and zones to understand how multiple data centers boost low latency and high availability across global deployments, enabled by cloud providers' regional infrastructure.

Assess compliance requirements, data locality laws, latency to users, service availability in the region, and pricing before deploying your application to the right cloud region.

Deploy your applications across multiple regions to reduce latency and serve users faster. Achieve global footprint, comply with data residency regulations, and improve availability and disaster recovery.

Zones, or availability zones, offer high availability within a single region by deploying across multiple isolated but connected zones with independent power, independent network, and low-latency links.

Understand regions and zones, including disaster recovery, data residency, and low latency, with insights into multi-zone and multi-region deployments, scenarios, and common misconceptions.

Explore how Google Cloud regions and zones are named and structured, using us-west-1 and us-west-1a as examples, and plan across multiple zones for high availability.

Meet the instructor for this course, Ranga Karanam, founder of in28minutes, who brings decades of programming with Java, Python, and JavaScript, and cloud certifications on AWS, Azure, and Google Cloud.

Explore virtualization by showing why dedicated servers are inefficient, how virtual machines on a single host with a hypervisor save resources, and the move to cloud services.

Learn how virtualization tackles resource wastage and high costs by running multiple virtual machines on a single physical server, enabled by a hypervisor like VMware, with centralized management and isolation.

Launch virtual machines in the cloud using on-demand services like EC2, Azure VMs, or Google Compute Engine. Choose region, OS, and hardware, paying only for usage.

Learn to create a google cloud compute engine virtual machine, choose region and machine type, select debian, and connect via ssh to run basic commands.

Choose the right virtual machine hardware by selecting the machine family and type for your workload, and pick public or custom images to optimize performance to cost.

Create a compute engine vm, enable http traffic, install apache, host a simple hello world page that shows the vm name and internal ip, accessible via the external ip.

Troubleshoot a gce web server by verifying the external ip, ensuring http access is enabled, ssh into the vm, inspect /var/www/html, and start apache2 with sudo.

Compare internal, external ephemeral, and external static IP addresses in Google Cloud VPCs, noting accessibility, permanence, and billing implications for virtual machines.

Demonstrates how to manage IP addresses for Google Cloud VMs. It covers internal and external IPs, ephemeral vs static, and how to assign none, reserve, and release static IPs.

Explore static external IP behavior for Compute Engine instances, ensuring consistent addresses across stops, restarts, and reassignments, and use internal IPs for private-network communication.

Learn how to bootstrap a compute engine vm using a startup script to install Apache, configure the web page, and enable http traffic.

Reduce vm startup time by using a pre-installed custom image and share hardened images from disks, snapshots, or cloud storage across projects.

Create a custom image from a VM disk after stopping the VM. Deploy a new VM from that image with a startup script and enable http traffic in United States.

Explore instance templates in Google Cloud to launch multiple VMs quickly from an immutable template, configured with image, startup script, labels, image family, and a managed instance group option.

Explore reusable vm configurations by creating instance templates, customize boot disks with a custom image, enable http traffic, and automate startup scripts to deploy vms.

Explore scenarios for launching Google Cloud VMs with startup scripts, instance templates, and managed instance groups, and use custom and hardened images to speed and secure deployments.

Explore the Google Cloud Console to access all services, mark favorites like Compute Engine, and set up budgets and alerts to monitor costs.

Discover cost-saving options for Compute Engine virtual machines, including sustained use discounts, committed use discounts, and spot VMs, and learn when to apply each strategy.

Google Cloud automatically applies sustained use discounts to VMs running more than 25% of a billing month, increasing with usage, with no upfront commitment. Some machine types may not apply.

Learn how committed use discounts save money on workloads by committing to one or three years, with either a minimum resource usage or minimum spend and greater savings for terms.

Use spot VMs to run non-urgent workloads at deep discounts by leveraging spare Google Cloud capacity, with dynamic pricing and a 30-second termination warning. Apply only to fault-tolerant, cost-sensitive workloads.

Explore sustained use discounts that auto-apply after 25% of the month, and learn to purchase one- or three-year committed use discounts; discuss spot vms in compute engine.

Explore cost optimization for Compute Engine VMs: commit 1–3 years; sustained use discounts apply after 25% of month; spot VMs suit fault-tolerant workloads, but use regular VMs for time-sensitive APIs.

Explore compute engine vm observability by viewing metrics and logs in the observability tab, including cpu utilization, network traffic, and disk throughput, and install Cloud Ops Agent for monitoring.

Explore the scope of compute engine resources, including regional differences in machine types, images, and instance templates. Learn to stop a VM to change its machine type.

discover how to use internal dns names for gce vms in the same vpc, mapping to the internal ip address and enabling communication without ip addresses, using the format vm_name.zone.project_id.internal.

Explore licensing costs for VM OS on Google Cloud, including pay-as-you-go on-demand pricing, bring your own license or subscription, and complexities of using paid OS like SUSE or Windows.

Reserve an entire host for one customer with sole-tenant nodes to ensure host-level isolation, then use node groups and affinity rules to place VMs.

Attach labels to cloud resources, including VMs, using key-value pairs like environment:production and team:devops to improve cost management, organization, and automation.

Review key Compute Engine concepts such as machine types, custom machine configurations, and images; use instance templates and discounts like sustained use, committed use, and spot VMs for cost optimization.

Choose zone and region for cost, compliance, and latency. Distribute VMs across multiple zones for high availability, and experiment with machine types and GPUs for workload gains.

Identify prerequisites to create a VM in Google Cloud—account, project, billing, and Compute Engine APIs—and explore SSH access, HTTP/HTTPS firewall rules, committed use discounts, and custom image hardening and sharing.

Explore instance groups in Google Cloud, including managed groups with identical VMs, health checks, auto-scaling and auto-healing, and unmanaged groups with varied configurations, plus regional versus zonal availability.

Explore how a MIG maintains a constant number of identical vms from an instance template, with health checks, self-healing, auto scaling, load balancing, MIGs, and rolling updates or canary deployments.

Explore key configurations for managing a managed instance group, including rolling update, rolling restart, and rolling replace, with templates, update timing options, max surge, and max unavailable.

Different applications require different layers and protocols. For example, gaming uses UDP at the transport layer for responses, while databases use TCP/TLS for reliable transfer, and web apps use HTTP.

Compare layer 4 and layer 7 load balancing, highlighting fast, low-overhead routing by IP address and port versus flexible routing by URL path, headers, and host.

Explore cloud load balancing terminology, defining backend as the managed instance group and frontend as the user entry point, with routing rules route by path, host, or http headers.

Explore how gcloud serves as the primary Google Cloud CLI, enabling you to create, delete, update, and view resources across VMs, databases, and Kubernetes via Cloud Shell and configuration workflows.

Learn to manage multiple gcloud configurations, create, activate, describe, and list configurations, and switch between environments by naming configurations clearly and setting core project properties.

Learn the gcloud command structure: group, subgroup, and action—and apply it to manage compute instances, regions, zones, and filters, including listing, creating, describing, and deleting resources.

Master gcloud command structure (group, subgroup, action) with compute instances create. Set default region and zone, manage configurations, and view the active project with gcloud config list.

discover how cloud shell runs on a temporary vm with five gb persistent home storage and prebuilt tools; learn about 20-minute inactivity timeouts and home directory persistence.

Configure default regions and zones for compute engine instances using project metadata, cloud console settings, or local gcloud config, with command options taking highest priority.

Explore essential gcloud compute instances commands to manage virtual machines, including listing, starting, stopping, hard reset, deleting, and describing instances, with disk handling options like --delete-disk and --keep-disk.