GCP Professional Cloud Architect: Google Cloud Certification

Explore cloud fundamentals and why enterprises and startups move from data centers to the cloud, with step-by-step visuals and real enterprise examples.

Learn why enterprises need thousands of servers and how data centers scale to avoid a single point of failure. Discover web, file, and email servers and other services.

Explore why data centers require infrastructure, power, cooling, networking, and security, and how peak load provisioning creates underutilized resources. See how latency, geographic expansion, and upfront costs push cloud adoption.

Discover how cloud computing replaces owned data centers by renting infrastructure on demand, with elasticity and pay-as-you-go pricing, unlocking scalable resources from cloud providers.

See how cloud converts CapEx to OpEx and delivers economies of scale and elastic capacity. Learn how cloud enables faster deployment, global reach, and avoids undifferentiated heavy lifting.

Explore elasticity, agility, geo-distribution, availability, and latency, and understand CapEx to OpEx and pay as you go cost concepts shaping cloud strategy.

Explore elasticity, OpEx and pay-as-you-go cost models, agility in provisioning, availability, geo-distribution, low latency, economies of scale, and avoiding undifferentiated heavy lifting across global cloud architectures.

Explore Google Cloud's private fiber optic network and its data-driven services, including analytics and machine learning, with step-by-step guidance through compute, storage, databases, and AI offerings.

Discover a structured, step-by-step path to learning cloud services without getting lost in details. Open a cloud account to gain global access, deploy resources, and use free beginner credits.

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

Maximize learning efficiency by using playback speed to accelerate videos, such as 1.25x to 2x, saving time. Balance speed with comprehension by starting at 1x and gradually increasing.

Learn how regions and zones create low-latency, highly available cloud deployments by distributing data centers across multiple regions worldwide.

Evaluate compliance requirements and keep data local to citizens' countries when choosing a deployment region; minimize latency, verify service availability, and review pricing to fit your cloud budget.

Deploy across multiple regions to lower latency, broaden global footprint, and meet data residency requirements while boosting availability and disaster-recovery resilience.

Understand how zones, or availability zones, provide high availability within a single region by deploying across multiple isolated zones with independent power, network, and low-latency connectivity.

Explore regions and zones, their roles in disaster recovery, data residency, and low latency, and test understanding with scenario-based questions.

Explore how Google Cloud regions and zones map global infrastructure, with examples like us-west1 and us-west1-a. Learn to deploy across multiple zones and regions for high availability.

Explore virtualization and how it enables multiple virtual machines on one server. Understand the move from dedicated servers to cloud services like EC2, Google Compute Engine, and Azure VMs.

Explore virtualization to run multiple applications on a single physical server by dividing it into virtual machines, sharing resources and isolating workloads, using a hypervisor such as VMware.

Explore cloud virtualization on demand, creating virtual machines with Amazon EC2, Azure VMs, and Google Compute Engine. Configure region, operating system, and hardware, and pay only for usage.

Learn to create your first Google Cloud virtual machine with Compute Engine by selecting region, zone, hardware, and Debian OS, then SSH and delete to save credits.

Deploy and manage virtual machines with Google Cloud Compute Engine, offering flexible CPU, memory, disk, and OS options, global regions, and managed instance groups with auto-scaling and pay-as-you-go.

Choose the machine family and type to balance performance and cost for web, analytics, gaming, ai/ml, or big data workloads, then select public or custom images to define operating system.

Create a Compute Engine vm, install apache2, enable http traffic, host a hello world page, then display the vm hostname and internal ip on the page before deleting the vm.

Debug a Google Cloud VM web server by verifying the external IP, allowing HTTP traffic, SSH access, and Apache startup, plus checking /var/www/html/index.html.

Select the machine family and type for your workload, interpret e2-standard-8 as eight vCPUs, choose an image, and attach storage with a boot disk, or create a custom image.

Explore internal, external ephemeral, and external static IPs for Google Cloud VMs in a VPC, and learn why internal IPs are permanent, ephemeral IPs change, and static IPs require reservation.

Explore Google Cloud IP addresses by creating a default VM to compare internal and external IPs, and learn how ephemeral IPs become static IPs and are released.

Explore compute engine IP address scenarios, including static external IPs to stay fixed across stops, restarts, and reassignments, when to use internal IPs, and keeping traffic inside the private network.

Learn how bootstrapping with a startup script enables a compute engine vm to automatically install software at startup, reducing manual setup.

This demo shows configuring a VM's startup script to run on boot, install Apache via apt, set the index page, and verify HTTP traffic on a Compute Engine VM.

Create a custom image with everything installed to reduce startup time, share across projects, deprecate outdated images, and harden images to meet security standards.

Learn to use instance templates to launch identical virtual machines with preset machine type, image, startup script, and labels; templates are immutable and support image families and managed instance groups.

Explore scenarios for launching Compute Engine VMs, including bootstrapping with startup scripts, using instance templates and managed instance groups, and applying custom and hardened images to secure, speedy deployments.

Explore the Google Cloud Console and view all products; learn to access Compute Engine, mark favorites, and create budgets with alerts to monitor costs.

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

Explore sustained use discounts in Google Cloud by understanding automatic, usage-based discounts on virtual machines; apply after 25% of a billing month and without other discounts, increasing with usage.

Explore Google Cloud committed use discounts for long-running workloads, choosing one- or three-year commitments to either minimum resource usage or minimum spend, with longer terms yielding greater discounts.

Use spot VMs to run non-urgent workloads at the lowest cost by leveraging spare Google Cloud capacity. Rely on dynamic pricing with a 30-second warning for fault-tolerant, cost-sensitive workloads.

Explore committed use discounts and Spot VMs in Google Cloud, including how sustained use discounts auto-apply and how to purchase one to three year commitments for VMs and licenses.

Understand Google Compute Engine billing, including per-second charges after the first minute, storage costs, and sustained or committed use discounts and spot VMs, and apply budget alerts and right-sizing.

Explore observability for Compute Engine VMs using metrics, logs, and traces as outputs. Default metrics exist in Cloud Monitoring; advanced metrics require Google Cloud Ops Agent and Cloud Logging.

Explore Compute Engine observability for VMs by viewing metrics and logs in the observability tab. Install the Cloud Ops Agent to collect metrics, logs, and traces with Cloud Monitoring, Logging.

Explore how compute engine resources vary by region, including machine types and pricing, and how you cannot change a running VM’s type without stopping it.

Enable vm-to-vm communication within a vpc using internal DNS names instead of IP addresses. The DNS name maps to the VM's internal IP and uses the format vm-name.zone.project-id.internal.

Learn how licensing costs affect VM OS in Google Cloud. Compare on-demand pay-as-you-go options and bring your own license for existing licenses.

Create a custom machine type when predefined VM options fall short, choosing a G, N, or E family and configuring vCPUs, memory, GPUs; supports Ubuntu, Red Hat, and Windows.

Sole-tenant nodes reserve an entire host for one customer, ensuring host-level isolation. Use node groups and affinity labels to place VMs and meet licensing, compliance, and availability needs.

Learn how to keep VM instances running during maintenance by enabling live migration in Compute Engine, migrating VMs within the same zone, and configuring on-host maintenance and automatic restart policies.

Learn the cloud best practice of attaching labels to resources, using simple key-value pairs. Apply labels for cost management, resource organization, and automation, whether during creation or after editing.

Explore compute engine concepts like machine types and custom configurations with vcpus, memory, and GPUs. Review images, instance templates, and discounts—sustained use, committed use, and spot VMs—for cost-effective workloads.

Choose the right zone and region for your virtual machines to balance cost, regulations, and latency, and distribute VMs across multiple zones or regions for high availability.

Identify prerequisites for VM creation in Google Cloud, including account, project, billing, and Compute Engine APIs, then configure firewall, consider committed-use discounts, and harden and share custom images.

Explore managed and unmanaged instance groups, using templates to create identical or varied VMs with auto-scaling, auto-healing, and health checks, and understand regional versus zonal availability.

Learn how a managed instance group uses a single instance template to run identical VMs, with health checks, self-healing, auto-scaling, load balancing, regional availability, and rolling or canary release strategies.

Explore creating and managing instance groups on Google Cloud, including managed (stateless and stateful) and unmanaged groups, using instance templates, autoscaling, zones, and health checks.

Configure a managed instance group by defining an instance template and auto-scaling with minimum and maximum instances, metrics from Cloud Monitoring, initialization period, and health checks.

Learn key configurations for managing a Google Cloud managed instance group, including rolling update, restart, and replace, with template changes, max surge, and max unavailable.

Explore advanced instance group scenarios in Google Cloud, including stateful managed groups for databases, rolling and selective updates, autoscaling, and health check timing controls to preserve capacity.

Explore how computers communicate by examining the network, transport, and application layers, and apply protocols like IP, TCP, TLS, UDP, HTTP/HTTPS, SMTP, and FTP.

Map applications to layers and protocols to fit needs: use UDP at the transport layer for gaming, and TCP/TLS for transfers; use HTTP, SMTP, or FTP at the application layer.

Compare layer four and layer seven load balancing, highlighting fast, low-overhead routing by IP and port versus application-layer routing by URL path, headers, and host for web apps and APIs.

Analyze load balancing scenarios to choose the right layer 4 or layer 7 and protocol, enabling ultra fast communication, latency sensitive gaming with UDP, and web traffic with HTTP/HTTPS.

Learn how cloud load balancing distributes traffic across multiple VMs with auto scaling and a 99.99% SLA, providing global Anycast IPs, internal load balancing, and health checks.

Explore cloud load balancing terminology by defining frontend and backend, configuring routing rules, and directing traffic from a frontend IP to multiple backends, with SSL and path or host-based routing.

Compare proxy and passthrough load balancers, detailing how proxy terminates client connections and opens a new backend connection, while passthrough forwards client packets unmodified to backends.

Compare application load balancers and network load balancers to choose layer 7 proxy-based balancing for HTTP/HTTPS or layer 4 routing with passthrough options, including anycast IP address.

Choose the right Google Cloud load balancer by comparing application versus network options. Learn when to use proxy or pass-through, and external, regional, and global configurations.

Explore ssl termination or ssl offloading at the load balancer, where client-to-load balancer uses https and load balancer to VM uses http within the Google Cloud internal network.

Select the right load balancer for each scenario: use application load balancer for path-based routing and TLS termination, or network load balancer for TCP/UDP workloads and ultra-low latency pass-through.

Configure https load balancing for microservices with shared frontends and backends, multiple versions, multi-region backends, and url maps routing, using premium versus standard networking for global routing.

Explore how an application load balancer routes requests to healthy backends using health checks, with URL maps for host, path, headers, and versioning, and apply weighted backends and session affinity.

Learn how network endpoint groups collect endpoints to load balance traffic across Kubernetes pods, serverless apps, and hybrid or external services, using zonal, internet, serverless, and private service connect NEGs.

Discover how to set up an application load balancer for serverless apps, including backend deployment, listener configuration, SSL, static IP, and serverless network endpoint groups with URL maps.

Discover key cloud load balancing integrations, including Cloud CDN with application load balancers, Cloud Armor for DDoS, WAF, and rate limiting, Cloud Logging exports, IAP authentication, and Private Service Connect.

Explore cloud load balancing scenarios, including health checks, layer 4 traffic, passthrough nlb, multi-region migs with a global app lb, URL maps for microservices, versioning, AB testing, and SSL encryption.

Learn how availability defines uptime as a percentage, with targets like 99.95% and 99.99% (four nines and five nines). Downtime impacts user trust and customer satisfaction.

Explore scalability and learn how to keep performance as traffic and data grow, and how bigger virtual machine instances or more app instances enable proportional growth.

Explore vertical scaling by increasing an instance's size to add cpu, ram, or disks, a simple approach without load balancers, yet limited and costly at peak sizes.

Master horizontal scaling by adding more instances and distributing data to boost scalability and availability for apps. Learn how load balancers, distributed data management, and service mesh enable this approach.

Learn resiliency as the system's ability to provide acceptable behavior during component failures, with multi-zone or multi-region deployments and health-checked VM groups.

Learn how to achieve high availability for Compute Engine VMs by using multiple regional instance groups, a global load balancer with a single anycast IP, health checks, and live migration.

Master vertical scaling by upgrading VM machine types for stateful workloads, then extend via horizontal scaling with managed instance groups across regions and global load balancers for high availability.

Explore architectural best practices for Compute Engine, focusing on performance, security, cost efficiency, and resiliency, including machine families, GPUs/TPUs, hardened images, internal IPs, auto scaling, and global load balancing.