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GCPPCA-T - Google Cloud Certified Professional Cloud Architect

Overview

Duration: 10 days

This Track includes : 

  • Google Cloud Platform Fundamentals: Core Infrastructure - GCPCIN- 1 Day
  • Architecting with Google Compute Engine - GCPGCE - 3 Days
  • Architecting with Google Kubernetes Engine - GCPGKE - 3 Days
  • Architecting with Google Cloud Platform: Design and Process -GCPDNPS - 2 Days
  • Preparing for the Professional Cloud Architect Examination -GCPPCA - E - 1 Day

Google Cloud Platform Fundamentals: Core Infrastructure – GCPCIN

This one-day instructor-led class provides an overview of GoogleCloud Platform products and services. Through a combination of presentations, demos, and hands-on labs, participants learn the value of Google Cloud Platform and how to incorporate cloud-based solutions into business strategies.

Architecting with Google Compute Engine – GCPGCE

This three-day instructor-led class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.

Architecting with Google Kubernetes Engine – GCPGKE

This three-day instructor-led class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine(GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring.

Architecting with Google Cloud Platform: Design and Process –GCPDNPS

This two-day instructor-led class equips students to build highly reliable and efficient solutions on Google Cloud Platform, using proven design patterns and the principles of Google Site Reliability Engineering(SRE). It is a continuation of the Architecting with Google Cloud Platform: Infrastructure course and assumes hands-on experience with the technologies covered in that course. 

Through a combination of presentations, demos, and hands-on labs, participants learn to design GCP deployments that are highly reliable and secure; and how to operate GCP deployments in a highly available and cost-effective manner.

Preparing for the Professional Cloud Architect Examination -GCPPCA - E 

The purpose of this course is to help those who are qualified develop the confidence to attempt the exam and to help those not yet qualified to develop their own plan for preparation.

Objectives

Google Cloud Platform Fundamentals: Core Infrastructure teaches participants the following skills:

  • Identify the purpose and value of Google Cloud Platform products and services
  • Interact with Google Cloud Platform services
  • Describe ways in which customers have used Google Cloud Platform
  • Choose among and use application deployment environments on Google Cloud Platform: Google App Engine, Google Kubernetes Engine, and Google Compute Engine
  • Choose among and use Google Cloud Platform storage options: Google Cloud Storage, Google Cloud SQL, Google Cloud Big table, and Google Cloud Datastore
  • Make basic use of Big Query, Google’s managed data warehouse for analytics
  • Make basic use of Cloud Deployment Manager, Google’s tool for creating and managing cloud resources through templates
  • Make basic use of Google Stack driver, Google’s monitoring, logging, and diagnostics system 

Architecting with Google Compute Engine Consider the entire range of Google Cloud Platform technologies in their plans Learn methods to develop, implement, and deploy solutions Distinguish between features of similar or related products and technologies Recognize a wide variety of solution domains, use cases, and applications Develop essential skills for managing and administering solutions Develop knowledge of solution patterns - methods,technologies, and designs that are used to implement security, scalability, high availability, and other desired qualities

Architectingwith Google Kubernetes Engine teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and Config Maps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine

Architecting with Google Cloud Platform: Design and Process teaches participants the following skills:

  • Design for high availability, scalability, and maintainability.
  • Assess trade offs and make sound choices among Google Cloud Platform products.
  • Integrate on-premises and cloud resources.
  • Identify ways to optimize resources and minimize cost.
  • Implement processes that minimize downtime, such as monitoring and alarming, unit and integration testing, production resilience testing, and incident post-mortem analysis.
  • Implement policies that minimize security risks, such as auditing, separation of duties and least privilege.
  • Implement technologies and processes that assure business continuity in the event of a disaster.

Preparing for the Professional Cloud Architect Examination (GCPPCA-E) course teaches participants the following skills:

  • Position the Professional Cloud Architect Certification
  • Provide information, tips, and advice on taking the exam
  • Review the sample case studies
  • Review each section of the exam covering highest-level concepts sufficient to build confidence in what is known by the candidate and indicate skill gaps/areas of study if not known by the candidate
  • Connect candidates to appropriate target learning.

Audience

  • Individuals planning to deploy applications and create application environments on Google Cloud Platform.
  • Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform.
  • Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs.
  • Cloud Solutions Architects, DevOps Engineers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with a focus on Google Compute Engine.
  • Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform
  • Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers.
  • Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform.
  • Cloud professionals who intend to take the Professional Cloud Architect certification exam Must have attended Architecting with GCP: Infrastructure course or equivalent on demand courses. Knowledge and experience with GCP, equivalent to GCP Architecting Infrastructure Knowledge of cloud solutions, equivalent to GCP Design and Process Industry experience with cloud computing.

Content

In Google Cloud Platform Fundamentals: Core Infrastructure, you will learn

Module 1: Introducing Google Cloud Platform

  • Explain the advantages of Google Cloud Platform.
  • Define the components of Google’s network infrastructure, including: Points of presence, data centers, regions, and zones.
  • Understand the difference between Infrastructure-as-a- Service (IaaS) and Platform-as-a-Service (PaaS).

Module 2: Getting Started with Google Cloud Platform

  • Identify the purpose of projects on Google Cloud Platform.
  • Understand the purpose of and use cases for Identity and Access Management.
  • List the methods of interacting with Google Cloud Platform.
  • Lab: Getting Started with Google Cloud Platform.

Module 3: Virtual Machines and Networks in the Cloud

  • Identify the purpose of and use cases for Google Compute Engine.
  • Understand the various Google Cloud Platform networking and operational tools and services.
  • Lab: Compute Engine

Module 4: Storage in the Cloud

  • Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, Google Cloud Big table, and Google Cloud Datastore.
  • Learn how to choose between the various storage options on Google Cloud Platform.
  • Lab: Cloud Storage and Cloud SQL

Module 5: Containers in the Cloud

  • Define the concept of a container and identify uses for containers.
  • Identify the purpose of and use cases for Google Kubernetes Engine and Kubernetes.
  • Lab: Kubernetes Engine

Module 6: Applications in the Cloud

  • Understand the purpose of and use cases for Google App Engine.
  • Contrast the App Engine Standard environment with the App Engine Flexible environment.
  • Understand the purpose of and use cases for Google Cloud Endpoints.
  • Lab: App Engine

Module 7: Developing, Deploying, and Monitoring in the Cloud

  • Understand options for software developers to host their source code.
  • Understand the purpose of template-based creation and management of resources.
  • Understand the purpose of integrated monitoring, alerting, and debugging.
  • Lab: Deployment Manager and Stackdriver

Module 8: Big Data and Machine Learning in the Cloud

  • Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms.
  • Lab: BigQuery

Architecting with Google Compute Engine includes presentations, demonstrations, and hands-on labs.

Module 1: Introduction to Google Cloud Platform

  • Google Cloud Platform (GCP) Infrastructure
  • Using GCP
  • Lab: Console and Cloud Shell
  • Demo: Projects
  • Lab: Infrastructure Preview

Module 2: Virtual Networks

  • Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, Firewall rules
  • Subnetworks for resource management instead of physical network topology
  • Lab: Virtual Networking
  • Lab: Bastion Host

Module 3: Virtual Machines

  • Compute Engine
  • Lab: Creating Virtual Machines
  • Compute options (vCPU and Memory)
  • Images
  • Common Compute Engine actions
  • Lab: Working with Virtual Machines

Module 4: Cloud IAM

  • Organizations, Roles, Members, Service accounts, Cloud IAM best practices
  • Lab: Cloud IAM

Module 5: Data Storage Services

  • Cloud Storage
  • Lab: Cloud Storage
  • Cloud SQL
  • Lab: Cloud SQL
  • Cloud Spanner, Cloud Datastore
  • Lab: Cloud Datastore
  • Cloud Bigtable

Module 6: Resource Management

  • Cloud Resource Manager, Quotas, Labels, Names, Billing
  • Demo: Billing Administration
  • Lab: Examining Billing Data with BigQuery

Module 7: Resource Monitoring

  • Stackdriver, Monitoring
  • Lab: Resource Monitoring (Stackdriver)
  • Logging, Error Reporting, Tracing, Debugging
  • Lab: Error Reporting and Debugging (Stackdriver)

Module 8: Interconnecting Networks

  • Cloud Virtual Private Network (VPN)
  • Lab: Virtual Private Networks (VPN)
  • Cloud Router, Cloud Interconnect, External Peering, Cloud DNS

Module 9: Load Balancing

  • Managed Instance Groups, HTTPS load balancing, Cross-region and content-based load balancing, SSL proxy/TCP proxy load balancing, Network load balancing
  • Lab: VM Automation and Load Balancing

Module 10: Autoscaling

  • Autoscaling, Policies, Configuration
  • Lab: Autoscaling

Module 11: Infrastructure Automation with Google Cloud Platform APIs

  • Infrastructure automation, Images, Metadata, Scripts, Google Cloud API
  • Lab: Google Cloud Platform API Infrastructure Automation

Module 12: Infrastructure Automation with Deployment Manager

  • Deployment Manager, Configuration, Cloud Launcher
  • Lab: Deployment Manager

Module 13: Managed Services

  • Cloud Dataproc, Cloud Dataflow, BigQuery, Cloud Datalab

Module 14: Application Infrastructure Services

  • Cloud Pub/Sub, API Management, Cloud Functions, Cloud Source Repositories, Specialty APIs

Module 15: Application Development Services

  • App Engine

Module 16: Containers

  • Containers, Kubernetes Engine, Container Registry
  • Lab: Kubernetes Load Balancing
  • Kubernetes Engine, App Engine, or Containers on Compute Engine?

Architecting with Google Kubernetes Engine teaches you :

Module 1: Introduction to Google Cloud Platform

  • Use the Google Cloud Platform Console
  • Use Cloud Shell
  • Define cloud computing
  • Identify GCPs compute services
  • Understand regions and zones
  • Understand the cloud resource hierarchy
  • Administer your GCP resources

Module 2, Containers and Kubernetes in GCP

  • Create a container using Cloud Build
  • Store a container in Container Registry
  • Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE)
  • Understand how to choose among GCP compute platforms

Module 3: Kubernetes Architecture

  • Understand the architecture of Kubernetes: pods, namespaces
  • Understand the control-plane components of Kubernetes
  • Create container images using Google Cloud Build
  • Store container images in Google Container Registry
  • Create a Kubernetes Engine cluster

Module 4: Kubernetes Operations

  • Work with the kubectl command
  • Inspect the cluster and Pods
  • View a Pods console output
  • Sign in to a Pod interactively

Module 5: Deployments, Jobs, and Scaling

  • Create and use Deployments
  • Create and run Jobs and CronJobs
  • Scale clusters manually and automatically
  • Configure Node and Pod affinity
  • Get software into your cluster with Helm charts and Kubernetes Marketplace

Module 6: GKE Networking

  • Create Services to expose applications that are running within Pods
  • Use load balancers to expose Services to external clients
  • Create Ingress resources for HTTP(S) load balancing
  • Leverage container-native load balancing to improve Pod load balancing
  • Define Kubernetes network policies to allow and block traffic to pods

Module 7: Persistent Data and Storage

  • Use Secrets to isolate security credentials
  • Use ConfigMaps to isolate configuration artifacts
  • Push out and roll back updates to Secrets and ConfigMaps
  • Configure Persistent Storage Volumes for Kubernetes Pods
  • Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts

Module 8: Access Control and Security in Kubernetes and Kubernetes Engine

  • Understand Kubernetes authentication and authorization
  • Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces
  • Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources
  • Define Kubernetes pod security policies
  • Understand the structure of GCP IAM
  • Define IAM roles and policies for Kubernetes Engine cluster administration

Module 9: Logging and Monitoring

  • Use Stackdriver to monitor and manage availability and performance
  • Locate and inspect Kubernetes logs
  • Create probes for wellness checks on live applications

Module 10: Using GCP Managed Storage Services from Kubernetes Applications

  • Understand pros and cons for using a managed storage service versus self managed containerized storage
  • Enable applications running in GKE to access GCP storage services
  • Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application

Architecting with Google Cloud Platform: Design and Process teaches you

Module 1: Defining the Service

  • Design in this class.
  • State and solution.
  • Measurement.
  • Gathering requirements, SLOs, SLAs, and SLIs (key performance indicators).

Module 2: Business-logic layer design

  • Microservices architecture.
  • GCP 12-factor support.
  • Mapping compute needs to Google Cloud Platform processing services.
  • Compute system provisioning.

Module 3: Data layer design

  • Classifying and characterizing data.
  • Data ingest and data migration.
  • Identification of storage needs and mapping to Google Cloud Platform storage systems.

Module 4: Network layer design

  • Network edge configuration.
  • Network configuration for data transfer within the service, including load balancing and network location.
  • Network integration with other environments, including on premise and multi-cloud.

Module 5: Design for resiliency, scalability, and disaster recovery

  • Failure due to loss of resources.
  • Failure due to overload.
  • Strategies for coping with failure.
  • Business continuity and disaster recovery, including restore strategy and data lifecycle management.
  • Scalable and resilient design.

Module 6: Design for security

  • Google Cloud Platform security.
  • Network access control and firewalls.
  • Protections against denial of service.
  • Resource sharing and isolation.
  • Data encryption and key management.
  • Identity access and auditing.

Module 7: Capacity planning and cost optimization

  • Capacity planning.
  • Pricing.

Module 8: Deployment, monitoring and alerting, and incident response

  • Deployment.
  • Monitoring and alerting.
  • Incident response.

In Preparing for the Professional Cloud Architect Examination, you will learn

Module 1: Understanding the Professional Cloud Architect Certification

  • Position the Professional Cloud Architect certification among the offerings
  • Distinguish between Associate and Professional
  • Provide guidance between Professional Cloud Architect and Associate Cloud Engineer
  • Describe how the exam is administered and the exam rules
  • Provide general advice about taking the exam

Module 2: Sample Case Studies

  • MountKirk Games
  • Dress4Win
  • TerramEarth

Module 3: Designing and Implementing

  • Review the layered model from Design and Process
  • Provide exam tips focused on business and technical design
  • Designing a solution infrastructure that meets business requirements
  • Designing a solution infrastructure that meets technical requirements
  • Design network, storage, and compute resources
  • Creating a migration plan
  • Envisioning future solution improvements
  • Resources for learning more about designing and planning
  • Configuring network topologies
  • Configuring individual storage systems
  • Configuring compute systems
  • Resources for learning more about managing and provisioning
  • Designing for security
  • Designing for legal compliance
  • Resources for learning more about security and compliance

Module 4: Optimizing and Operating

  • Analyzing and defining technical processes
  • Analyzing and defining business processes
  • Resources for learning more about analyzing and optimizing processes
  • Designing for security
  • Designing for legal compliance
  • Resources for learning more about security and compliance
  • Advising development/operation teams to ensure successful deployment of the solution
  • Resources for learning more about managing implementation
  • Easy buttons
  • Playbooks
  • Developing a resilient culture
  • Resources for learning more about ensuring reliability

Module 5: Next Steps

  • Present Qwiklabs Challenge Quest for the Professional CA
  • Identify Instructor Led Training courses and what they cover that will be helpful based on skills that might be on the exam
  • Connect candidates to individual Qwiklabs, and to Coursera individual courses and specializations.
  • Review/feedback of course

Prerequisites

  • Familiarity with the Linux command line, web servers, and text editors. 
  • Completion of Google Cloud Platform Fundamentals or equivalent experience Basic proficiency with command-line tools and Linux operating system environments Systems operations experience, including deploying and managing applications, either on-premises or in a public cloud environment
  • Completed Google Cloud Platform Fundamentals: Core Infrastructure or have equivalent experience Basic proficiency with command-line tools and Linux operating system environments
  • Completed Architecting with Google Cloud Platform: Infrastructure or have equivalent experience
  • Basic proficiency with command-line tools and Linux operating system environments
  • Systems Operations experience including deploying and managing applications, either on-premises or in a public cloud environment 
  • Knowledge and experience with GCP,equivalent to GCP Architecting Infrastructure
  • Knowledge of cloud solutions,equivalent to GCP Design and Process
  • Industry experience with cloud computing

Certification

Google Cloud Certified Professional Cloud Architect

Schedule

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