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.

Understand why enterprises need thousands of servers, illustrated by in28minutes' browser and server interactions, and how avoiding a single point of failure leads to data center-based, scalable infrastructure.

Explore how data centers house thousands of servers with power, cooling, networking, and security, and why high upfront costs push enterprises toward cloud to reduce latency and expand globally.

Explore how cloud computing turns infrastructure into rentable resources, delivering on-demand access, elasticity, and pay as you go pricing from providers like AWS, Azure, and Google Cloud.

Discover the advantages of cloud computing, including pay-for-use, a capex-to-opex shift, economies of scale, and elasticity, enabling global deployment and increased speed while avoiding 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.

Explore Google Cloud's private fiber network and its secure data transit. Learn about Google's data and AI leadership and the service catalog across compute, storage, databases, analytics, and machine learning.

Discover a step-by-step path to learning cloud services with a practical gateway: create a cloud account to access global regions, deploy resources, and use free credits for beginners.

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 how regions and availability zones create low latency and high availability by distributing data centers across multiple regions, enabling global deployment with cloud providers.

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, expand globally, meet data residency requirements, and improve availability and disaster recovery.

Explore how zones enable high availability within a single region by deploying across Zone A, Zone B, and Zone C in London region. Each zone has independent power and connectivity.

Understand how regions and zones enable disaster recovery, low latency, and data residency, and when to deploy across multiple zones or regions for high availability.

Discover how Google Cloud regions and availability zones are named and organized, and learn to deploy across multiple zones and regions for higher 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.

Create your first virtual machine in Google Cloud, explore machine types and images, install a web server, and explore startup scripts, custom images, and troubleshooting.

Learn how Google Compute Engine provisions and manages virtual machines, controls their life cycle, attaches storage, and configures networking, with load balancing and auto scaling.

Create and manage a Google Compute Engine VM, connect with SSH, and explore start–stop cycles, labels, default US Central region, and Debian image with HTTP firewall enabled.

Select the machine family and type to define hardware, including vCPUs, memory, and networking, then choose an image—public or custom—to set the operating system.

Set up a Google Compute Engine vm, install apache2, and host a hello world page that shows host name and external IP.

Understand how internal and external ip addresses differ: external ip addresses are internet reachable and may change on restart; internal ip addresses stay within the cloud network.

Reserve a regional static external IP, attach it to a VM, and verify that the static address remains assigned after stopping the instance.

Master static IP management in GCP by switching an IP between VMs in the same project. Release unused static IPs to avoid unnecessary charges, even when the VM is stopped.

Learn to bootstrap a Compute Engine VM with a startup script to automatically install Apache, apply OS patches, and serve a simple web page, enhancing secure, automated web server setup.

Create an instance template to predefine machine type, image or image family, labels, and startup script, then launch virtual machines or groups across regions and zones; templates cannot be updated.

Learn to reduce VM boot time by hardening a custom image with operating system patches and pre-installed software, then deploy it via instance templates for scalable, secure deployments.

Troubleshoot launching Apache on a Google Cloud VM by verifying the external IP, SSH access, and the /var/www/html/index.html content, then start Apache and adjust firewall rules for HTTP traffic.

Explore the Google Cloud Platform web console, learn to access services via the pencil or search, pin favorites, and navigate dashboard, APIs, billing, monitoring, activity, and project settings.

Remember long-term information by practicing active learning, taking notes, and regular review. Develop recall across weeks and months through consistent note-taking and periodic review.

Explore sustained use discounts that lower VM costs on Compute Engine and Kubernetes Engine after 25% usage, with discounts increasing and exclusions for E2, A2, App Engine flexible, and Dataflow.

Understand committed use discounts for Google Cloud virtual machines, offering up to 70% off for 1- or 3-year commitments on Google Kubernetes Engine and Compute Engine instances.

Save costs with preemptable VMs, short-lived cheaper compute instances. Use for non-immediate batch workloads, while noting 24-hour max, possible termination, and no guaranteed SLA.

Understand spot VMs, the latest version of preemptible VMs, with no maximum runtime, potential reclamation by Google Cloud with a 30-second notice, and dynamic pricing with 60–91% discounts.

Understand compute engine billing: pay by second after a one-minute minimum, with storage charges continuing when a VM stops. Create budgets and alerts to control costs and use sustained-use discounts.

Enable live migration to keep vm instances running during maintenance by migrating to another host in the same zone, and configure availability policy to migrate or terminate with automatic restart.

Create custom machine types in Google Cloud compute engine to fit workloads beyond predefined options. Specify VCPUs, memory, and optional GPUs on E2, N2, and N1 families, with operating systems.

Learn to accelerate math and graphic intensive workloads on Google Compute Engine by adding GPUs to virtual machines or choosing GPU machine families, ensuring the correct GPU-enabled images.

Learn that a virtual machine belongs to a project, that you must stop to change its machine type, and how to filter and use images and instance templates with monitoring.

Apply best practices for virtual machines in Google Cloud Platform. Choose zones and regions based on cost, availability, latency, and hardware needs, including CPU and memory-optimized types, GPUs, and labels.

Identify prerequisites for creating a Google Cloud VM: a project, billing, and enabled Compute Engine APIs. Learn about sole-tenant nodes, node templates, labels, and firewall rules for secure, no-external-ip access.

Review how to configure Google Compute Engine VMs by selecting images, creating custom images and machine types, using instance templates, and applying sustained, committed, or preemptable discounts.

Encourage learners to leave ratings and reviews, as feedback drives course recommendations and helps others discover this GCP associate cloud engineer preparation course.

Learn to manage Google Cloud resources using the gcloud command line interface, part of the Google Cloud SDK, and configure projects, regions, and zones via Cloud Shell.

Explore how to use gcloud config to view and set core properties like project, account, region, and zone; learn to print specific values, adjust verbosity, and access help.

learn to manage multiple gcloud configurations on the same machine by creating, listing, describing, deleting, and activating configurations, and by switching between them while setting default project, zone, and region.

Learn the gcloud command structure by exploring groups, subgroups, and actions with compute, instances, and machine types; practice listing, creating, describing, deleting instances, and filtering zones and regions.

Demonstrate configuring gcloud compute instances create, including machine type default, listed, or custom; boot disk, service accounts, startup and shutdown scripts, network settings, and options like preemptible and maintenance policy.

Configure compute engine defaults by setting the region and zone via centralized project metadata, local gcloud config, or per-command options, with command-specific settings taking highest priority.

Explore gcloud list and describe commands to enumerate regions, zones, images, and other resources, apply filters, sort results, and view resource URIs.

Explore gcloud compute instance commands to start, stop, delete, reset, describe, move, and list, including delete discs options and moving a VM between zones.

Learn to manage Google Cloud instance templates from the command line with gcloud compute instance-templates create, list, describe, and delete, and to create instances from templates using a source instance.

Learn consistently to improve long-term retention with a two-week specific plan and a visible desk reminder, scheduling daily study blocks of lectures to boost goal achievement by more than 50%.

Explore instance groups on Google Cloud, especially managed instance groups (MIG) and unmanaged groups, with auto-scaling, auto-healing, and managed releases, plus regional versus zonal deployment.

Create and manage a managed instance group using an instance template, configure autoscaling with CPU utilization or load balancer metrics, set a cool-down, and enable autohealing with health checks.

Manage a Google Cloud instance group with autoscaling and health checks to keep two healthy instances running, automatically replacing unhealthy ones, and learn group configuration and monitoring.

Update a managed instance group with rolling updates and rolling restart, configuring canary testing and new instance templates, proactive or opportunistic upgrades, and managing max surge and max unavailable.

Distribute instances across multiple zones with regional MIGs to survive zonal failures, and use unmanaged or stateful MIGs with health checks and proper availability policies for resilient autoscaling.

Master managing google cloud managed instance groups with gcloud compute instance groups managed, covering create, list, describe, update and delete, plus autoscaling setup, health checks, and auto healing policies.

Learn to manage a Google Cloud managed instance group with gcloud: resize the group, recreate or update instances, and set a new instance template, using zone-aware commands.

Learn to update a managed instance group to a new template using rolling actions, including restart, replace, and cannery version updates with maximum surge and maximum unavailable controls.

Embrace challenges as opportunities to grow and unlock your full potential. Learn from feedback, celebrate effort, and stay curious to develop a growth mindset.

Explore cloud load balancing, distributing traffic across virtual machine instances in regional scopes, with health checks, auto scaling, a single anycast IP, and internal load balancing for high availability.

Explore how application, transport, and network layers enable protocols like HTTP, HTTPS, TCP, TLS, UDP, and IP to communicate between systems, and how TCP ensures reliability while UDP favors performance.

Configure a Google Cloud load balancer to distribute traffic across a managed instance group, using HTTP/HTTPS, TCP, or UDP with front end, back end, and host and path rules.

Explore cloud load balancing terminology in GCP, including backends, front ends, host and path rules, and SSL termination, and learn how HTTPS client traffic pairs with internal HTTP to VMs.

Explore how a Google Cloud load balancer distributes traffic across a managed instance group, with a backend service and frontend, and review the hierarchy from instance template to backend.

Choose the right Google Cloud load balancer by traffic type and scope, for internal TCP/UDP or HTTP/HTTPS, or external with regional or global options and advanced traffic management.

Explore the features of Google Cloud load balancers, including external HTTP(S) proxy load balancers, SSL offloading, and pass-through versus proxy behavior. Compare internal and external TCP/UDP options.

Learn load balancing across multiple regions with health checks, multiple migs, and host and path rules to route to microservice backends, plus global HTTPS traffic and SSL termination.

Learn to stay ahead of technology by making daily learning a habit through the 28-day learning pledge, committing 28 minutes of study each day for 28 days.

Explore why cloud providers offer managed services and learn terms like infrastructure as a service, platform as a service, function as a service, container as a service, and serverless.

Explore infrastructure as a service and platform as a service, compare responsibilities for OS, runtime, and apps, and review examples like EC2 and Elastic Beanstalk.

Explore how containers power microservices with Docker images that run language runtimes anywhere. Discover container orchestration, autoscaling, service discovery, load balancing, and cloud provider options.

Discover serverless computing in the gcp associate cloud engineer course: hide infrastructure, gain scalable, automated high availability, and pay per invocation, with aws lambda, azure functions, and google functions.

Clarify serverless terminology and expectations by distinguishing level one and level two features, including zero cost for zero invocations, zero infrastructure worries, and automatic scale to zero with pay-per-invocation.

Get a 10,000-foot overview of Google Cloud compute services, from Compute Engine (IaaS) to App Engine, Cloud Functions, and Cloud Run, highlighting container use and serverless options.

Uncover the origin of in28minutes and its message of investing in yourself, learning something new every day, and viewing change as an opportunity in the cloud era.

Explore app engine, the simplest way to deploy and scale apps on GCP with end-to-end management and runtimes for Go, Java, .NET, Node JS, PHP, Ruby, and Python.

Compare App Engine standard and flexible environments, noting sandbox restrictions, docker-based deployment, and compute engine VM access; learn when v2 standard or flexible suits your runtime.

Explore the App Engine component hierarchy—application as the container, multiple services, and versions with instances. Learn to split traffic and roll back to specific versions.

Compare app engine standard and flexible environments by highlighting pricing, manual, basic, and automatic scaling, storage, noting standard's scale-to-zero and seconds startup versus flexible's minimum one instance and minutes startup.

Compare automatic, basic, and manual scaling for App Engine, where automatic scales by load with thresholds, basic saves costs but isn't supported by flexible, and manual relies on load prediction.

Set up a new project, enable App Engine APIs, create a python standard app with app.yaml and main.py, deploy via gcloud app deploy, and fix Cloud Build IAM permissions.

Deploy and compare App Engine versions, view traffic splits and instances in the App Engine UI, and manage services with gcloud commands to switch to v2 while keeping v1 live.

Deploy V3 with the --no-promote option to test it while V2 stays live, then gradually split traffic using IP, random, or cookie methods until all traffic shifts to V3.

Create and deploy multiple app engine services and versions by configuring app.yaml and using gcloud app deploy, then migrate or split traffic to specific versions via the UI.

Explore configuring app.yaml for Google App Engine, including runtime, API version, environment, env variables, handlers, and auto scaling options (automatic, basic, manual) with CPU and concurrency settings.

Learn to route traffic across multiple App Engine services and versions using URLs, dispatch.yaml, and Cloud Load Balancing, including custom domain setups.

Deploy app engine versions without downtime by shifting traffic from v1 to v2 with gcloud app deploy. Promote immediately or deploy with --no-promote and migrate traffic gradually, including canary testing.

Explore splitting traffic between App Engine versions in GCP using IP, cookie, or random methods, including default IP splitting and its accuracy issues.

Master App Engine management from the command line with gcloud app commands like create, deploy, browse, and describe. Specify region, YAML name, promote options, and container image for flexible environments.

Master gcloud app instances commands—list, delete, describe, scp, and ssh—for App Engine, and note how standard scales to zero while flexible supports file transfer and remote access.

Explore App Engine services and versions with gcloud commands to browse, list, describe, delete, start, stop, and migrate traffic between versions, including traffic splits and hide no traffic.

Configure cron jobs in App Engine with cron.yaml to run scheduled http GET requests at predefined intervals, deployable via gcloud app deploy cron.yaml.

Explore app engine yaml files, including dispatch.yaml for routing and queue.yaml for task queues. Deploy dispatch.yaml with gcloud app deploy, and configure queue settings like name, rate, and retries.

Explore App Engine basics: regional deployment and one-to-one project-region mapping, standard versus flexible runtimes, scale down to zero, and balancing resident and dynamic instances for cost and performance.

Explore how a single Google App Engine app per project hosts multiple services and versions. Learn to perform canary deployments with traffic splits and why region choice is permanent.

Face a challenge by troubleshooting on your own, then search Google, ask ChatGPT with clear questions, and post your question in the course discussion board before helping others.