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.

Explore why enterprises need thousands of servers and how data centers, with web, file, email, and database servers, support scalable, reliable applications.

Discover what a data center is and its power, cooling, networking, and security needs. Learn the challenges of owning one—high upfront costs and capacity guessing—and how cloud enables instant servers.

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 how Google Cloud uses a private fiber optic network to deliver faster, secure data; learn its heritage, mission, and catalog across compute, storage, databases, analytics, AI, and machine learning.

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.

Choose cloud regions by balancing compliance, latency, service availability, and pricing to keep data local and close to users while ensuring needed services are available.

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 how regions and zones enable disaster recovery, low latency, and data residency. Learn multi-zone and multi-region deployment strategies, plus high availability concepts, common misconceptions, and practical scenarios.

Explore how regions and zones in Google Cloud are named and structured, with examples like us-west1 and us-west1-a. Learn how deploying across multiple zones or regions boosts 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.

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.

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.

Create a custom image with everything installed to reduce startup time, share across projects, deprecate outdated images, and harden images to meet security standards.

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.

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.

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.

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 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.

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.

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

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.

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.

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.

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.

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.