GCP for Beginners - Become a Google Cloud Digital Leader

Explore cloud fundamentals, understand why startups and enterprises move away from data centers, and discover what cloud is and its advantages through a step-by-step visual approach with real enterprise scenarios.

Enterprises need thousands of servers to scale beyond single-server limits and prevent a single point of failure by using data centers for large, reliable operations.

Explore data centers: their required power, cooling, networking, and security. Learn challenges like high upfront costs, peak load provisioning, and latency, and see why cloud offers a faster alternative.

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

Discover the key advantages of the cloud, including pay-for-use economics, economies of scale, and elastic capacity. Learn how these benefits enable faster development, global deployment, and reduced undifferentiated heavy lifting.

Recall elasticity, agility, global reach, latency, and availability, and contrast CapEx with OpEx to see how pay-as-you-go costs and economies of scale empower managed services and reduce undifferentiated heavy lifting.

Analyze cloud concepts through scenarios, illustrating elasticity, pay-as-you-go costs, agility in provisioning, high availability, geo-distribution, low latency, economies of scale, and avoiding undifferentiated heavy lifting.

Explore how Google Cloud leverages a private fiber-optic network to deliver fast, secure data across compute, storage, databases, analytics, and machine learning.

Learn a structured, step-by-step path to mastering cloud services across AWS, Azure, and Google Cloud, and discover how a cloud account provides global access, a gateway, and free credits.

Create a Google Cloud account and start a free trial with $300 credit by providing your personal details, verifying your mobile number, and entering card and tax information.

Use playback speed to maximize learning efficiency in your GCP for beginners course, saving time while maintaining comprehension by starting at 1x and gradually increasing to 1.25x, 1.5x, or 2x.

Learn how regions and zones define cloud infrastructure, and how multi-region, multi-data-center deployments deliver low latency and high availability across the globe.

Understand how to choose a cloud region by evaluating compliance, latency, service availability, and pricing, ensuring data stays local and performance remains strong for your users.

Deploy your applications across multiple regions to reduce latency, expand your global footprint, and meet data residency requirements. Leverage regional deployment to improve availability and enable faster disaster recovery.

Explore zones, or availability zones, within a region to achieve high availability by deploying across London's zone A, zone B, zone C, with independent power, network, and low latency links.

Explore regions and zones, clarify misconceptions, and apply scenarios to design multi-zone and multi-region deployments for disaster recovery, low latency, data residency, and high availability.

Explore Google Cloud regions and zones with examples like us-west1 and us-west1-a, europe-north1 in Finland, and asia-south1 in Mumbai, and learn about naming conventions and high availability.

Explore virtualization basics and virtual machines, uncover why dedicated servers are inefficient, and see how the hypervisor enables multiple VMs on a single physical server.

Explore virtualization to run multiple virtual machines on a single physical server, enabling safe resource sharing, reducing waste and costs, and using hypervisors like VMware for centralized management and isolation.

Explore Google Cloud Compute Engine to provision and manage virtual machines, with pay-as-you-go scaling, auto-scaling, global regions, and managed instance groups offering load balancing.

Configure a compute engine virtual machine instance by selecting an image, choosing a machine family and type, and attaching block storage via Hyperdisk or Persistent Disk.

Learn how Google Cloud assigns internal and external IP addresses to VM instances, distinguish ephemeral from static external IPs, and manage static IPs to preserve connectivity and control costs.

Analyze scenarios about compute engine IP addresses for virtual machines, including static vs ephemeral external addresses, internal IPs for private network communication, and IP reassignment considerations.

Learn bootstrapping a compute engine VM with a startup script to automatically install software at startup, reducing manual setup. Compare custom image and instance template options to streamline deployment.

Explore configuring a VM startup script to bootstrap a Compute Engine, install Apache via apt, configure the index page, and ensure HTTP traffic on boot.

Create a pre-installed custom image to speed up virtual machine launches, shareable across projects, with deprecation and security hardening guidance.

Create a custom image from a stopped VM disk, set multi-regional availability, and launch a new VM from that image with a streamlined startup script to reduce launch time.

Explore instance templates to configure a VM once and reuse to launch multiple VMs or managed instance groups, noting that templates are immutable and can be copied to create versions.

Learn to create reusable vm configurations with instance templates using regional settings and a custom image, enable http traffic, configure a v2 startup script, and deploy single or grouped VMs.

Explore how to reduce costs for Compute Engine virtual machines by using sustained use discounts, committed use discounts, and spot VMs, with guidance on when to apply each option.

Discover how sustained use discounts automatically apply to eligible VMs without commitment when you run them for more than 25% of the billing month, with higher discounts for longer usage.

Use spot VMs to run non-urgent workloads at the lowest cost, benefiting from deep discounts, dynamic pricing, and a 30-second termination warning. Spot VMs require fault tolerant, cost sensitive workloads.

Discover how licensing costs affect VM OS in Google Cloud, including on-demand or pay-as-you-go models and bring your own license. Learn about complexities of using existing licenses for paid systems.

Create a custom machine type in Compute Engine when presets don't fit. Configure vCPUs, memory, and GPUs within G, N, or E families and deploy on common operating systems.

Explore how sole-tenant nodes reserve an entire host for a single customer, then use node groups with affinity labels and affinity rules to place virtual machines.

Identify prerequisites for creating a VM on Google Cloud: account, project, billing, and Compute Engine APIs; then use SSH, firewall rules, committed use discounts, and a custom hardened image.

Troubleshoot on your own to build resilience. Research with Google, consult ChatGPT, post details in Q&A when needed, give back, and take a break when stuck.

Explore instance groups to manage many VMs, using managed groups with instance templates, health checks, auto-scaling and auto-healing, or unmanaged groups, and regional instance groups across zones for higher availability.

Discover how a managed instance group uses identical VMs from an instance template, with health checks, self-healing, autoscaling, load balancing, regional MIGs, and rolling updates or canary deployments.

Explore creating and managing Google Cloud instance groups, including managed (stateless vs stateful) and unmanaged groups, with autoscaling, instance templates, multi-zone placement, health checks, and update options.

Define backend as the managed instance group receiving traffic and frontend as the load balancer's ip, port, and protocol; apply routing rules for path or host.

Learn to create a two-instance group from an instance template, set up an application load balancer with a front end and backend, and configure health checks and cpu utilization.

Compare IaaS and PaaS by illustrating app and database setup, showing how cloud providers handle infrastructure, scaling, backups, and maintenance, while you focus on code and data.

Explore Software as a service (saas), a centrally hosted, easy-to-use subscription-based model used by Gmail and Google Docs, where providers handle infrastructure while you focus on data and configuration.

Explore infrastructure as a service, platform as a service, and software as a service through practical scenarios, from deploying virtual machines to using prebuilt cloud apps.

Divide serverless services into two levels: level one charges per instance with auto scaling, level two charges per invocation, featuring Google App Engine, AWS Fargate, AWS Lambda, and Azure Functions.

Examine traditional, document-driven deployment and its slow, error-prone steps, then see how container images package the OS, runtime, code, and dependencies to streamline deployment across environments.

Explore how a container image packages an app and its dependencies, becomes immutable with tags, and moves through a container registry to be deployed by engines like Docker across environments.

Defines a monolith as a single large application with a single database and millions of lines of code, hosting movies and bookings. Highlights deployment, release cycles, scalability, and technology lock-in.

Learn the three pillars of microservices: API-based communication, small independently deployable units with clear boundaries, and dynamic scaling, demonstrated by decomposing a movie monolith into targeted services.

Explore microservices as small, independently deployable units that enable experimentation with new languages and frameworks, while dynamically scaling components like the booking service for faster releases and lower costs.

Understand the six challenges of microservices: standardized operations, auto-scaling, load balancing, service discovery, flexible release management with zero downtime and rolling updates, and resiliency with isolation and automatic recovery.

Explore Google Cloud's compute options, including IaaS and PaaS services such as Compute Engine, App Engine, Cloud Run, Cloud Run Functions, and Kubernetes Engine, plus serverless, containers, and container orchestration.

Explore compute service scenarios in Google Cloud, including creating virtual machines with Compute Engine, managed instance groups, load balancing, Cloud Run, App Engine, GKE, and Cloud Run functions.

Explore App Engine standard and flexible environments, comparing language-specific sandboxes and container-based deployments, with notes on scaling, pricing, and when to SSH into VMs.

Explore how App Engine operates as a regional service, deploying all services in a single region across zones, with a region that cannot be changed and standard or flexible options.

Compare App Engine with Compute Engine to minimize operations; App Engine Standard scales rapidly, supports scaling to zero, limits to one app per project, and structures versions under services.