GCP-ARCH: Professional Cloud Architect


  • Duration: 5 Days
  • Mode of Delivery: Online -Instructor-led training
  • Job role: Cloud Architect
  • Preparation for exam: Google certification exam
  • Cost: USD$2,750.00

This course instructs participants about the flexible infrastructure and platform services provided by Google Cloud Platform. In this course, you will learn how to analyze and deploy infrastructure components such as networks, storage systems, and application services.

20 in stock

SKU: AZ-303-1 Categories: , , ,


This Google Cloud Platform Architect course is well-suited for: Software developers, Cloud solutions architects, Systems operators, DevOps engineers


  • Knowledge of Google Cloud Platform fundamentals or any cloud platform is beneficial
  • Basic knowledge of command-line tools and Linux operating system environments

Skills Gained

  • In depth Understanding on Google Cloud Platform
  • GCP Services – Networking , Storage , Databases, Containers, Virtual Machines, App Engine, Security etc
  • GCP Compute Service : Virtual Machine (GCE), App Engine (GAE), Container Service (GKE), Google Cloud Function
  • GCP Networking VPC, CDN, Interconnect, DNS
  • GCP Management Tools – Stackdriver Monitoring, Logging, Trace, Error Reporting, Deployment Manager, Shell, Console, Cloud SDK
  • GCP Storage & Database Service : Cloud Storage, Cloud SQL, Cloud BigQuery, Cloud Spanner, Cloud DataStore, Cloud Spanner
  • GCP IAM and Security : Cloud IAM, KMS, Resource Manager, Security Scanner

Course outline

Section 1: Introduction to GCP
Module 1: GCP Cloud Architect Professional
• The benefits of being a certified architect
• Registering for the exam
• What to expect from the exam?
• Some tips

Module 2: Getting Started with Google Cloud Platform
Introducing the cloud
Understanding GCP
• GCP differentiators
• GCP locations
• Resource manager
• Organizations
• Folders
• Projects
• Resource scope
• Global resources
• Regional resources
• Zonal resources
• Managing projects
• Granting permissions
• Billing
• Managing billing accounts
• Assigning a project to a billing account
• Exporting billing
• Budgets and alerts
• Billing account roles

Module 3: Google Cloud Platform Core Services
• Computing and hosting services
• Storage services
• Networking services
• Big data services
• ML services
• Identity services

Section 2: Managing, Designing, and Planning a Cloud Solution Architecture
Module 4: Working with Google Compute Engine
Deploying our first GCE instance
Deployment options
• Region
• Zone
• Boot disk
• Application images
• Snapshots
• Existing disks
• Management | Labels
• Management | Deletion protection
• Management | Metadata
• Management | Startup scripts
• Management | Preemptibilty
• Management | Availability policy
• Management | Automatic restart
• Security | Shielded VM
• Disks | Deletion rule
• Sole tenancy | Node affinity labels
• GPUs and TPUs
Instance templates and instance groups
• Setting the location
• Port name mapping
Quotas and limits
IAM roles

Module 5: Managing Kubernetes Clusters with Google Kubernetes Engine
An introduction to microservices
• Kubernetes architecture
• The master node
• Worker nodes
• Kubernetes objects
• Pods
• Replica sets
• Deployments
• Namespaces
• Services
• Types of services
Google Kubernetes Engine
• Node pools
• Container-Optimized OS
• Storage
• GKE cluster management
• Creating a GKE cluster
• Advanced configuration
• Networking
• Security
• Stackdriver
Additional features
• Deploying our first application
• Cluster second-day operations
• Upgrading the cluster
• Auto-upgrades
• Auto-repair
• Resizing the cluster
• Autoscaling a cluster
• Rotating the master IP
Kubernetes role-based access control
• Container Registry
• Cloud Build
• Quotas and limits
• Pricing

Module 6: Exploring Google App Engine as a Compute Option
App Engine components
Choosing the right location
Working with App Engine
Environment types
• App Engine Standard environment
• Flexible environment
Deploying an App Engine application
Splitting traffic
Migrating traffic
Firewall rules
• Custom domain
• SSL certificates
Cron jobs
Quotas and limits

Module 7: Running Serverless Functions with Google Cloud
Main Cloud Functions characteristics
Use cases
• Application backends
• Real-time data processing systems
• Smart applications
Runtime environments
Types of Cloud Functions
• HTTP functions
• Background functions
Other considerations
• Cloud SQL connectivity
• Connecting to internal resources in a VPC network
• Environmental variables
• Cold start
• Local emulator
Deploying Cloud Functions
• Deploying Cloud Functions with the Google Cloud Console
• Deploying functions with the gcloud command
• Triggers
Quotas and limits
Cloud Run

Module 8: Networking Options in GCP
Exploring GCP networking
Understanding Virtual Private Cloud
• Connectivity
• Cost
• VPC Flow Logs
• Cross-VPC connectivity
• Shared VPC
• VPC peering
• Choosing between shared VPC and VPC peering
Load balancing
• Global versus regional load balancing
• External versus internal
• Proxy versus load balancer
• Load balancer types
• Comparison
• Choosing the right load balancer
• NAT gateway
• Cloud NAT
Hybrid connectivity
• Interconnects
• Peering
• Choosing the right connectivity method
• DNS resolution
• Cloud DNS
Firewall rules
• Default rules
• Implied rules
• Always allowed traffic rules
• Always denied rules
• User-defined rules
• Firewall logging
• Private access

Module 9: Exploring Storage Options in GCP 
Choosing the right storage option
• Data consistency
Understanding Cloud Storage
• Storage classes
• Data consistency
• Cloud Storage FUSE
• Creating and using a bucket
• Versioning and lifecycle management
• Versioning
• Lifecycle management
• Transferring data
• Cloud Storage Transfer Service
• Google Transfer Appliance
• Understanding IAM
• Quotas and limits
Understanding Cloud Datastore
• Data consistency
• Creating and using Cloud Datastore
• Datastore versus Firestore
• Quotas and limits
Understanding Cloud SQL
• Data consistency
• Creating and managing Cloud SQL
• Read Replicas
• Failover Replica
• Backup and recovery
• Migrating data
• Instance cloning
• Quotas and limits

Module 10: Exploring Storage Options in GCP 
• Instances configuration
• Node count
• Replication
• TrueTime
• Data consistency
• Creating a Cloud Spanner instance
• Quotas and limits
• Pricing
• Bigtable configuration
• Instances
• Clusters
• Nodes
• Schema
• Replication
• Application profiles
• Data consistency
• Creating a Bigtable instance and table
• Quotas and limits
• Pricing

Module 11: Analyzing Big Data Options
End-to-end big data solution
Cloud Pub/Sub
• Creating a topic and subscription
• Quotas and limits
• Pricing
Cloud Dataflow
• Quotas and limits
• Pricing
• BigQuery features
• Datasets
• Tables
• Using BigQuery
• Importing and exporting data
• Storage
• Quotas and limits
• Architecture
• Quotas and limits
Cloud IoT Core
• Quotas and limits
• Pricing

Module 12: Putting Machine Learning to Work
An introduction to AI and ML
The seven steps of ML
• Gathering and preparing the data
• Choosing a model
• Training
• Evaluation
• Hyperparameter tuning
• Prediction
Learning models
GCP ML options
Cloud ML Engine
• Using ML Engine
• Interacting with ML Engine
• ML Engine scale tiers
• Cloud Tensor Processing Units (TPUs)
• Submitting a training job
• Deploying the model
• Predictions
• Submitting predictions
Pretrained ML models
• The Cloud Speech-to-Text API
• The Cloud Text-To-Speech API
• The Cloud Translation API
• The Cloud Natural Language API
• The Cloud Vision API
• The Google Cloud Video Intelligence API

Section 3: Designing for Security and Compliance
Module 13: Security and Compliance
Introduction to security
Cloud Identity
Resource Manager
Identity and Access Management (IAM)
• Service accounts
• Cloud Storage access management
Firewall rules and load balancers
Cloud Security Scanner
Monitoring and logging
• Data encryption keys versus key encryption keys
• CMEKs versus CSEKs
Industry regulations
• PCI compliance
• Shared responsibility model
• Data Loss Prevention (DLP)
• Penetration testing in GCP
Additional security services
• Cloud Identity-Aware Proxy (IAP)
• Security Command Center (SCC)
• Forseti
• Cloud Armor

Section 4: Managing Implementation
Module 14: Google Cloud Management Options
Using APIs
Google Cloud Shell
• gcloud
• gsutil
• bq
• cbt
Cloud Deployment Manager
Pricing Calculator
Additional things to consider

Section 5: Ensuring Solution and Operations Reliability
Module 15: Monitoring Your Infrastructure 
Technical requirements
Introduction to Stackdriver
Configuring Stackdriver
Stackdriver Monitoring
• Groups
• Dashboards
• Alerting policies
• Uptime checks
• Monitoring agents
Stackdriver Logging
• Logs Viewer
• Basic log filtering
• Advanced filtering
• Exporting logs
• Logging agent
• Log-based metrics
• Cloud audit logs
• Trace
• Debugger
• Profiler
Error Reporting

Section 6: Exam Focus
Module 16: Case Studies
Understanding how to approach exam case studies
What are they looking for in the case studies?
Company overview
• Solution concept
• Business requirements
• Technical requirements
• Executive summary
• Forming a solution
• The analytics platform
• The backend platform


Click on the following link to see the current Course Schedule
Our minimum class-size is 3 for this course.
If there are no scheduled dates for this course, it can be customized to suit the time and skill needs of clients and it can be held online, at a rented location or at your premises.
Click on the following link below to arrange for a custom course: Enquire about a course date

Product Information

It is true—there is no cloud: it’s just someone else’s computer. With the cloud, what we are actually doing is accessing resources and consuming services that are hosted on someone else’s computer. If we want to be more precise, the cloud is a pool of computers. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (for example, networks,
servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics, three service models, and four deployment models.
The five essential characteristics of the cloud are as follows:
• On-demand self-service: Services are provisioned automatically without manual provider intervention.
• Broad network access: Resources are available through the network.
• Resource pooling: Resources are pooled from a shared pool, giving the user a sense of location independence. For some of the resources, the location might be restricted.
• Rapid elasticity: Services can be elastically provisioned and deprovisioned with capacity being managed by the provider.
• Measured service: Resource usage is monitored and can be reported on.
The four deployment models are as follows:
• Private cloud: Used by specific organizations, but can be managed by third parties
• Public cloud: Used by the general public
• Community cloud: Used by specific communities
• Hybrid cloud: Composed of two or more different clouds
When we look at GCP, it fulfills all of the five characteristics and fits into the public cloud deployment model. In the next section, we will have a look at GCP itself.
Google has been developing its own tools to deliver services such as Gmail, YouTube, Google Drive, and Google+ for years. These tools have been converted into services that can be consumed by others. Consumers are given the amazing scalability that Google has to use for their own purposes. Google Cloud Platform (GCP) lets you choose from computing, storage, networking, big data, and machine learning (ML) services to build your application on top of them. The number of services is growing constantly, and new announcements are made on an almost weekly basis. New services and features are released, first as alpha then as beta versions, and finally, are made available globally. The early releases are available even earlier for selected customers and partners. This allows the services to be tested by external parties even before the official release.
We are given a variety of options when it comes to computing in GCP. Depending on our requirements and flexibility, we can choose from one of the following service models:
• Infrastructure as a Service (IaaS): Google Compute Engine (GCE)
• Container as a Service (CaaS): Google Kubernetes Engine (GKE)
• Platform as a Service (PaaS): Google App Engine (GAE)
• Function as a Service (FaaS): Cloud Functions

Professional Cloud Architects enable organizations to leverage Google Cloud technologies. With a thorough understanding of cloud architecture and Google Cloud, they design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives. Cloud architects often benefit from high job security due to the significance and growth of cloud computing. Their skills are invaluable and necessary within many sectors, like technology, business, finance, education, health and government.


CERTFICATE OF COMPLETION: Participants will receive a certificate of completion at the end of a course. This is not an official certification for the product and/or software. Our courses do indicate the appropriate certification exam(s) that the participant can sit. Data Vision Systems does not provide certification or deliver the certification exams. Participants are responsible for arranging and paying for the certification exams on the appropriate certification body.

CANCELLATION POLICY: There is never a fee for cancelling seven business days before a class for any reason. Data Vision Systems reserves the right to cancel any course due to insufficient registration or other extenuating circumstances. Participants will be advised prior to doing so.


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