Ultimate Google Cloud Certifications: All in one Bundle (4)
4.1 (2,100 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
100,585 students enrolled

Ultimate Google Cloud Certifications: All in one Bundle (4)

250,000+ GCP Students, 500+ Questions - Associate Cloud Engineer, Cloud Architect, Cloud Developer, Network Engineer
4.1 (2,100 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
100,585 students enrolled
Last updated 4/2020
English
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Current price: $69.99 Original price: $99.99 Discount: 30% off
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This course includes
  • 32 hours on-demand video
  • 96 articles
  • 9 downloadable resources
  • 2 Practice Tests
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • From Beginners to advanced - I would say from Zero to Hero Google Cloud Platform
  • Become Master in Google Cloud Platform
  • Prepare for Google Cloud Certifications - Cloud Engineer , Cloud Architect, Cloud Developer, Data Engineer, Cloud Network Engineer - TBD.
  • Save time in preparing Multiple Google Cloud Certification exams.
Requirements
  • Student should be computer science knowledgeable will help to understand and prepare for certification.
Description

Hi Cloud Professionals


We have 350,000+ Students & 250,000 Unique students for Google Cloud Platform Certifications makes us "No 1 Trainer for Google Cloud Platform on Udemy" 

7500+ Students informed us that they got certifications with our courses.


Did you know 85% of global IT professionals hold at least one certification, of which over half were earned in the past 12 months? Another 66% plan to attain a new certification this year. These findings are published in the Global Knowledge 2019 IT Skills and Salary Report.


Please check lecture 2 for Google cloud platform certification future promotions subscriptions!

You always have Free $300 Credit for Google Cloud Platform

Becoming Google Certified choice of your certification - Professional Cloud Architect, Associate Cloud Engineer, Professional Cloud Developer,  Professional Cloud Network Engineer (Beta), Upcoming -> Cloud Data Engineer, Cloud DevOps Engineer, Cloud Security Engineer.


This course is not for Lazy learners -  Course has comprehensive coverage of Google Cloud Platform and students need very long focus/attention to complete.

The course does not assume you have knowledge on Google Cloud Platform or any cloud Platform. We cover almost everything on GCP to become "Hero" from whatever your current GCP understanding (it may be Zero or Beginning or Intermediate)


Advance Students - Joining this course only for certification -> Please at least run through the foundation section once for you to understand the certification syllabus.


Why waste time learning the same foundation concepts again and again for each certification around the same technology. This course divided into the section where you learn all concepts in once course and then focus individually on each certification - Incrementally.    

Why Pay for Every Certifications course and some times you don't even appear for certification. This course will help you to pay only once and plan for any certification on Google Cloud Platform.   


Single Course FULLY Prepares you for all FOUR certifications below ->

  1. Associate Cloud Engineer,

  2. Professional Cloud Architect

  3. Professional Cloud Developer 

  4. Professional Cloud Data Engineer  - Expected in Jul 2020

  5. Professional DevOps Engineer - Expected in Dec 2020


Bonus: Other Certifications are upcoming ->

  1. Professional Cloud Network Engineer - in Beta expected to be completed in Nov 2020.

  2. Professional Security Engineer - Upcoming.   Tentative Aug 2020.


Each Certification

> 100 % Coverage for Certification.

> Section by Section mapping syllabus (after foundation) so that you don't have to hunt for any other options for syllabus coverage 

> One Practice Question set for each Certification - Besides Google Readiness Test

> Labs will help you understand each service in detail.

Our Target at the end of Dec to have 2 Questions Sets for each certification.


Time is Money nowadays - We all want to optimize our time to learn new things and add it in our profile in a smart way. This course will take out duplicate learning work which you may need to do if you are planning for more than 1 certification on Google Cloud Platform.


Each Certification gives additional dimension about Google Cloud Platform and this Course committed to giving you will give you 360 view of Google Cloud platform so - you don't have to refer any other course.


Thank You for your time and Stay connected!


Happy Learning !!


Google Cloud Gurus

Seattle, WA USA 

Who this course is for:
  • Who wants to learn Google Cloud Platform.
  • Students preparing for Google Cloud Certification
  • Students who wants to become master in Google Cloud Platform.
Course content
Expand all 435 lectures 32:01:23
+ Introduction
5 lectures 17:39
GCP Certifications Covered in this Course
01:18
Course Motivation
01:47
Course Structure
01:49
+ Getting around basics of Google Cloud Platform
19 lectures 01:05:20
Google Cloud Platform Overview
01:25
Getting Started ! - Login and $300 GCP Credit
01:11
Google Cloud Platform - Infrastructure Services
04:45
Getting Around : GCP Cloud Console
02:42
Google Cloud Platform Services
03:26
Google Cloud Platform interfaces
01:20
GCP Projects
02:11
GCP Resources
04:12
Identity and Access Management
03:37
Billing Account and Usage Alerts
05:28
Quota and Limits
03:36
GCP Infrastructure Services
01:50
Cloud Shell
05:01
Cloud SDK
02:21
Cloud SDK Installations and Setup
04:39
Cloud API
04:10
Cloud Launcher
08:53
GCP Tools
02:49
Stackdriver Applications
01:44
+ Google Cloud Platform Fundamentals : Core Concepts
216 lectures 17:40:11
Introduction
02:11
Section 1: Compute Services Overview
13:41
Compute Engine - Basics
10:26
Compute Engine - Machine Types
07:56
Compute Engine - GPU's - Graphic Processing Unit
03:45
Compute Engine - Disks & VM Storage
07:19
Compute Engine - VM Images
05:48
Compute Engine - Instance Templates
09:45
Compute Engine - Networking
01:28
Compute Engine - Startup Scripts
03:40
Compute Engine - Preemptible Virtual Machine
03:05
Compute Engine - Other Concepts !
06:02
Compute engine - Other Concepts in Console !
05:50
Compute Engine - Pricing & Discount
08:50
LAB : Compute Engine
00:07
Compute Engine
10 questions
Compute Engine in Summary
04:20
App Engine - Basics
08:50
App Engine - Services, Version & Instances
03:35
App Engine - Traffic Splitting
04:03
App Engine - Standard Environment
04:12
App Engine - Flexible Environment
08:52
App Engine - Deployment configuration app.yaml
02:49
App Engine - Security Scanner
04:11
Multiple Application Deployment
00:00
App Engine - Pricing
01:47
App Engine - Disable App and avoid cloud charges !
01:32
Lab : App Engine
00:07
App Engine in Summary
02:40
App engine
8 questions
Kubernetes Engine - Basics
08:11
Kubernetes in Google Cloud Platform.
03:08
Kubernetes Engine - Cluster
02:05
Kubernetes Engine - POD
05:16
Kubernetes Engine - Service
02:04
Kubernetes Engine - Deployments
02:39
Kubernetes Engine - Different Types of Clusters
00:00
Kubernetes Engine - Node Pools
07:01
Kubernetes Engine - Auto Scaling
05:17
Kubernetes Engine - Regional and Multizone Clusters
03:00
Kubernetes Engine - Load Balancing
03:10
Kubernetes Engine - Node Images
02:58
Kubernetes Engine - Node Repair
02:22
Kubernetes Engine - Networking
01:56
Kubernetes Engine - Labels & Selectors
02:33
Kubernetes Engine - Local SSD Support
02:01
Kubernetes Engine - GPU's Support
02:02
Kubernetes Engine - Other Concepts
04:43
Avoid Cloud Charges deleting cluster !
01:01
Cluster Creation : Other options in Summary !
07:10
Kubernetes - Hybrid Env - Anthos
02:02
Kubernetes Summary
01:58
LAB - Kubernetes Engine
00:07
Kubernetes Engine Quiz !
9 questions
Cloud Function- Basics
06:29
Google Cloud Function Questions
5 questions
Cloud Run (Beta) - Basics
07:46
Cloud Run - Service
01:29
Cloud Run - Revisions
02:22
Cloud Run - Container Instance
03:04
Cloud Run - Fully Managed
01:32
Cloud Run for Anthos
03:04
Cloud Run in Summary !
02:39
Load Balancer - Basics
07:25
Load Balancer in Cloud Console
01:29
Load Balancer - Health Check
03:08
Content Aware Load Balancing
03:09
Load Distribution Algorithm
02:14
Load Balancer - Session Affinity
02:28
Different Types of Load Balancers
02:38
Load Balancer - Auto Scaling and HA
02:13
HTTP Load Balancer
06:38
TCP/SSL Proxy Load Balancer
04:29
FYI - Network OSI - Simpler form.
02:14
Regional Internal/External Load Balancer
05:40
Load Balancer - Pricing
02:13
Optional - HTTP load Balancer Demo
33:59
Optional - Demo Clean up !
03:45

Please download attached file and go through LAB Exercise.


Lab Exercise is not tracked systematically and optional. Make sure you mark this lecture complete for your course completion certificate gets generated.


LAB : Load Balancer
00:07
Load Balancer Summary
02:49
GCE - Load Balancing & Auto Scaling
10 questions
Section 2 : Database Services Overview
03:43
Cloud SQL- Basics
03:57
Cloud SQL - New Changes
00:08
Cloud SQL - MYSQL
07:51
Cloud SQL -PostgreSQL
02:53
Cloud SQL - Performance
03:23
Cloud SQL - Backup and Restore
02:02
Cloud SQL : Logging and Point in time recovery !
02:23
Cloud SQL - High Availability
05:42
Cloud SQL - Read Replica and Performance
04:57
Cloud SQL - Pricing
03:22
LAB : Cloud SQL
00:07
Cloud SQL in Summary
02:21
Cleanup Reminder
00:30
Cloud Spanner - Basics
06:14
Cloud Spanner - Features
03:05
Cloud Spanner - Architecture (Global)
03:23
Cloud Spanner - Performance
01:41
Cloud Spanner - Interleaved Tables
02:52
Cloud Spanner - IAM
02:42
Cloud Spanner - Cleanup
00:33
LAB : Cloud Spanner
00:07
Cloud Spanner - Summary
02:14
Google Cloud SQL Spanner Persistent Disk Questions
28 questions
Cloud Storage- Basics
08:20
Cloud Storage - Consistency Model
02:16
Cloud Storage - Buckets
04:29
Cloud Storage - Objects
02:45
Cloud Storage - Storage Class Updates
00:09
Cloud Storage - Storage Classes
08:14
Cloud Storage - Object Life-cycle policies
06:03
Cloud Storage - Data Transfer Services
02:49
Data Encryption
01:24
Object Change Notification
03:32
Cloud Storage - Audit Logging
01:29
Cloud Storage - IAM
04:09
Cloud Storage Summary
03:09
Google Cloud Storage Questions
35 questions
Cloud Firestore
04:40
Cloud Firestore in Datastore mode
03:36
Cloud Firestore - Schema Design
02:24
Cloud Firestore - Features
00:53
Cloud Firestore - Pricing
01:06
Cloud Firestore - IAM
01:23
TBD - LAB : Cloud Datastore /Firestore
00:07
Cloud Firestore/Datastore Summary
01:08
Cloud BigTable - Basics
07:16
Cloud Bigtable - Architecture
02:41
Cloud Bigtable - Migration from HBASE
03:23
Cloud Bigtable - Schema Designing
02:18
Cloud Bigtable - Performance
01:19
Cloud BigTable - Application Profile
03:31
Cloud Bigtable - Quotas and Limits
01:21
Cloud BigTable - Pricing
01:18
Cloud Bigtable - IAM
00:52
BigData Services
04:09
Cloud BigQuery - Basics
10:05
Cloud BigQuery - Best Practices
04:46
Cloud BigQuery - IAM
00:49
Cloud BigQuery - Pricing and Others
01:03
LAB : Cloud BigQuery
00:07
Cloud BigQuery - Summary
03:17
Cloud Dataproc
09:37
Cloud Dataproc - Architecture
03:43
Cloud Dataproc - Additional Components
01:48
Cloud Dataproc - Storage Options
03:16
Cloud Dataproc - Jobs
02:52
Cloud Dataproc - Workflows
03:24
Cloud Dataproc - Quota and Limits
01:26
Cloud Dataproc - IAM
02:13
Cloud Dataproc - Pricing
01:33
Cloud Dataproc - Cleanup Reminder
00:27
LAB : Cloud Dataproc
00:07
Cloud Dataproc Summary
02:15
Cloud Dataflow - Basics
06:35
Cloud Dataflow - Pipeline
06:08
Cloud Dataflow vs Cloud Dataproc
02:09
Cloud Dataflow - Quota and Limits
03:38
Cloud Dataflow - IAM
01:46
Cloud Dataflow - Pricing
01:55
Cloud Dataflow - Summary
02:13
Cloud PubSub
16:48
Cloud Pub/Sub - Demo
17:38
Lab : Cloud PUB/SUB
00:07
Google Datalab/Data Studio
15:11
Only for Beginners - Networking Basics Part1
10:09
Only for Beginners - Networking Basics part 2
04:52
Section 3: Cloud Networking
08:00
Cloud VPC Basics
07:20
Types of VPC's
06:48
Project and VPCs
02:47
Cloud VPC - Subnetworks
07:50
Cloud VPC - Internal IP Addresses
05:20
Cloud VPC - External IP Address
04:59
Cloud VPC - Routes
05:22
Cloud VPC - Firewalls
06:46
Cloud VPC - Shared VPC
02:15
Cloud VPC - Peering
06:49
Cloud VPC - Quota and Limits
01:52
Cloud VPC - Flow Logs
04:05
Optional - Cloud VPC Demo
32:22
Security - Bastion Host
02:48
Optional - Bastion Host - Demo
03:30
Security : Nat Gateway
02:13
Cloud VPC - Pricing
02:49
Hybrid Connectivity
05:00
Cloud VPN
05:00
Cloud Router
04:04
Cloud Interconnect
05:57
Cloud CDN
15:07
Cloud DNS
06:03
Optional - Cloud DNS Demo
16:22
Cloud Armor
07:09
Section 4: Stackdriver Applications
03:11
Stackdriver Applications
02:47
Stackdriver Monitoring
26:53
Stackdriver Logging
20:47
Stackdriver Error Reporting
13:02
Stackdriver Trace
06:56
Stackdriver Debug
08:51
Section 5: Cloud Security
10:31
Cloud IAM
21:29
Service Account
09:11
Cloud Audit Logs
08:57
Cloud KMS
16:36
Cloud Security Scanner
03:44
Cloud CI/CD
02:49
Cloud Source Code Repository
10:29
Cloud Container Registry
02:24
Cloud Build - Basics
05:04
Cloud Build - Build Config
03:07
Cloud Build - Triggers
04:14
Cloud Build - Simple Build Demo
06:04
Cloud Build - CD Demo Introduction
05:24
Cloud Build - CD Demo Setup
07:10
Cloud Task
02:44
Cloud Scheduler
02:11
Deployment Manager
17:02
API Management - Overview
06:35
API Management - APIGEE Light Demo
07:40
Cloud Developer Tools - Eclipse
12:56
Cloud Developer Tools - IntelliJ
07:39
+ Associate Cloud Engineer Certifications
33 lectures 03:42:28
Introduction
00:47
Associate Cloud Engineer Syllabus & Exam Structure
04:44
Exam Focus and Strategy
04:02
What we achieved and What is that we are going to learn.
02:12
1. Setting up a cloud solution environment
01:08
1.1 Setting up cloud projects and accounts.
13:54
1.2 Managing billing configuration
10:54
1.3 Installing and configuring the command line interface (CLI) - Cloud SDK
00:01
Quiz: Setting up Environment.
5 questions
Section 2: Planning and configuring a cloud solution
03:48
2.1 Planning and estimating GCP product use using the Pricing Calculator.
06:30

2.2 Planning and configuring compute resources. Considerations include:

  • Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Kubernetes Engine, App Engine).

  • Using preemptible VMs and custom machine types as appropriate.

2.2 Planning and configuring compute resources.
00:01
TBD 2.3 Planning and configuring data storage options.
00:00
2.4 Planning and configuring network resources : Load Balancer
00:01
Quiz : Planning and Configuring Cloud.
10 questions
Section 3: Deploying and implementing a cloud solution
00:01
3.1 Deploying and implementing Compute Engine resources. - Recap
00:01
3.2 Deploying and implementing Kubernetes Engine resources - recap
00:01
3.3 Deploying and implementing App Engine and Cloud Functions resources. recap
00:01
3.4 Deploying and implementing data solutions.
00:01
3.5 Deploying and implementing networking resources - recap
00:01
3.6 Deploying a Solution using Cloud Launcher - recap
00:01
3.7 Deploying an Application using Deployment Manager - recap.
00:01
Section 4. Ensuring successful operation of a cloud solution
06:05
  • 4.1 Managing Compute Engine resources. Tasks include:

    • Managing a single VM instance (e.g., start, stop, edit configuration, or delete an instance).

    • SSH/RDP to the instance.

    • Attaching a GPU to a new instance and installing CUDA libraries.

    • Viewing current running VM Inventory (instance IDs, details).

    • Working with snapshots (e.g., create a snapshot from a VM, view snapshots, delete a snapshot).

    • Working with Images (e.g., create an image from a VM or a snapshot, view images, delete an image).

    • Working with Instance Groups (e.g., set auto scaling parameters, assign instance template, create an instance template, remove instance group).

    • Working with management interfaces (e.g., Cloud Console, Cloud Shell, GCloud SDK).

4.1 Managing Compute Engine resources.
37:28
Quiz Managing Compute Engine
10 questions
  • 4.2 Managing Kubernetes Engine resources. Tasks include:

    • Viewing current running cluster inventory (nodes, pods, services).

    • Browsing the container image repository and viewing container image details.

    • Working with nodes (e.g., add, edit, or remove a node).

    • Working with pods (e.g., add, edit, or remove pods).

    • Working with services (e.g., add, edit, or remove a service).

    • Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK).

4.2 Managing Kubernetes Engine resources.
34:38
Quiz : Managing Kubernetes Engine
6 questions
  • 4.3 Managing App Engine resources. Tasks include:

    • Adjusting application traffic splitting parameters.

    • Setting scaling parameters for autoscaling instances.

    • Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK).

4.3 Managing App Engine resources.
11:41
Quiz : Managing App Engine.
4 questions
  • 4.4 Managing data solutions. Tasks include:

    • Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Datastore, Cloud Bigtable, Cloud Dataproc).

    • Estimating costs of a BigQuery query.

    • Backing up and restoring data instances (e.g., Cloud SQL, Cloud Datastore, Cloud Dataproc).

    • Reviewing job status in Cloud Dataproc or BigQuery

    • Moving objects between Cloud Storage buckets.

    • Converting Cloud Storage buckets between storage classes.

    • Setting object lifecycle management policies for Cloud Storage buckets.

    • Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK).

4.4 Managing data solutions.- Cloud Spanner
09:12
Quiz : Managing Cloud Spanner
2 questions
4.4 Managing data solutions - Cloud Storage
24:59
  • 4.5 Managing networking resources. Tasks include:

    • Adding a subnet to an existing VPC.

    • Expanding a CIDR block subnet to have more IP addresses.

    • Reserving static external or internal IP addresses.

    • Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK).

TBD - 4.5 Managing networking resources.
00:00
  • 4.6 Monitoring and logging. Tasks include:

    • Creating Stackdriver alerts based on resource metrics.

    • Creating Stackdriver custom metrics.

    • Configuring log sinks to export logs to external systems (e.g., on premises or BigQuery).

    • Viewing and filtering logs in Stackdriver.

    • Viewing specific log message details in Stackdriver.

    • Using cloud diagnostics to research an application issue (e.g., viewing Cloud Trace data, using Cloud Debug to view an application point-in-time).

    • Viewing Google Cloud Platform status.

    • Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK).

4.6 Monitoring and logging.
00:01
Stackdriver
15 questions

5. Configuring access and security


  • 5.1 Managing Identity and Access Management (IAM). Tasks include:

    • Viewing account IAM assignments.

    • Assigning IAM roles to accounts or Google Groups.

    • Defining custom IAM roles.

    5.2 Managing service accounts. Tasks include:

    • Managing service accounts with limited scopes.

    • Assigning a service account to VM instances.

    • Granting access to a service account in another project.

    5.3 Viewing audit logs for project and managed services.

Section 5. Configuring access and security
10:31
Quiz : Configuring Access and Security
1 question
  • 5.1 Managing Identity and Access Management (IAM). Tasks include:

    • Viewing account IAM assignments.

    • Assigning IAM roles to accounts or Google Groups.

    • Defining custom IAM roles.

5.1 Managing Identity and Access Management (IAM).
21:29
  • 5.2 Managing service accounts. Tasks include:

    • Managing service accounts with limited scopes.

    • Assigning a service account to VM instances.

    • Granting access to a service account in another project.

5.2 Managing service accounts.
09:11
5.3 Viewing audit logs for project and managed services
08:57
Associate Cloud Engineer Practice Exam
50 questions
+ Professional Cloud Developer Certification
56 lectures 03:41:12
Introduction
00:39
Professional Cloud Developer Certification Details
04:44
Exam Focus and Strategy
04:14
Case Studies and its Importance
08:16
What we achieved and What is that we are going to learn.
02:11
Section 1. Designing highly scalable, available, and reliable cloud-native Apps
01:53
  • 1.1 Designing performant applications and APIs. Considerations include:

    • Infrastructure as a Service vs. Container as a Service vs. Platform as a Service (e.g., autoscaling implications)

    • Portability vs. platform-specific design

    • Evaluating different services and technologies

    • Operating system versions and base runtimes of services

    • Geographic distribution of Google Cloud services

    • Microservices

    • Defining a key structure for high write applications using Cloud Storage, Cloud Bigtable, Cloud Spanner, or Cloud SQL

    • Session management

    • Deploying and securing an API with cloud endpoints

    • Loosely coupled applications using asynchronous Cloud Pub/Sub events

    • Health checks

    • Google-recommended practices and documentation

1.1 Designing performant applications and APIs.
02:33
1.1 Designing performant Apps -Cloud IAAS CAAS PAAS Services overview
10:30
1.1 Designing performant apps - Platform Specific design
07:08
1.1 Designing performant apps - Geographic Distribution of GCP Services
08:47
1.1 Designing performant apps -Microservices
08:49
Bonus API Proxy : 1.1 -Designing performant apps -Microservices with API Proxy
04:46
Bonus REST API and GraphQL : 1.1 -Designing performant apps -Microservices
03:33
1.1 Designing performant apps - Database Keys
01:03
1.1 Designing performant apps - Session Persistence
02:09
1.1 Designing performant apps - Loose Coupling using Cloud Pub Sub
02:17
1.1 Designing performant apps - Health Check
02:13
1.1 Designing performant apps - Best Practices
04:56
  • 1.2 Designing secure applications. Considerations include:

    • Applicable regulatory requirements and legislation

    • Security mechanisms that protect services and resources

    • Storing and rotating secrets

    • IAM roles for users/groups/service accounts

    • HTTPs certificates

    • Google-recommended practices and documentation

1.2 Designing secure applications.
11:47

Already Covered as Part of Foundation.


1.3 Managing application data. Tasks include:

    • Defining database schemas for Google-managed databases (e.g., Cloud Datastore, Cloud Spanner, Cloud Bigtable, BigQuery)

    • Choosing data storage options based on use case considerations, such as:

      • Cloud Storage signed URLs for user-uploaded content

      • Using Cloud Storage to run a static website

      • Structured vs. unstructured data

      • ACID transactions vs. analytics processing

      • Data volume

      • Frequency of data access in Cloud Storage

    • Working with data ingestion systems (e.g., Cloud Pub/Sub, Storage Transfer Service)

    • Following Google-recommended practices and documentation


1.3 Managing application data.
03:58
  • 1.4 Re-architecting applications from local services to Google Cloud Platform. Tasks include:

    • Using managed services

    • Using the strangler pattern for migration

    • Google-recommended practices and documentation

1.4 Re-architecting applications from local services to Google Cloud Platform.
00:11
Section 2. Building and Testing Applications
01:30
  • 2.1 Setting up your development environment. Considerations include:

    • Emulating GCP services for local application development

    • Creating GCP projects

2.1 Setting up your development environment.
13:54
2.1 Setting up your development environment Part 2
10:54
  • 2.2 Building a continuous integration pipeline. Considerations include:

    • Creating a Cloud Source Repository and committing code to it

    • Creating container images from code

    • Developing unit tests for all code written

    • Developing an integration pipeline using services (e.g., Cloud Build, Container Registry) to deploy the application to the target environment (e.g., development, test, staging)

    • Reviewing test results of continuous integration pipeline

2.2 Building a continuous integration pipeline.
00:02
CI CD Exam Points
01:28
  • 2.3 Testing. Considerations include:

    • Performance testing

    • Integration testing

    • Load testing

2.3 Testing.
09:40
  • 2.4 Writing code. Considerations include:

    • Algorithm design

    • Modern application patterns

    • Efficiency

    • Agile methodology

2.4 Writing code.
05:21
CLI Assignments
01:49
Section 3. Deploying applications
01:44
  • 3.1 Implementing appropriate deployment strategies based on the target compute environment (Compute Engine, Google Kubernetes Engine, App Engine). Strategies include:

    • Blue/green deployments

    • Traffic-splitting deployments

    • Rolling deployments

    • Canary deployments

3.1 Implementing appropriate deployment strategies based on the target compute
08:56
  • 3.2 Deploying applications and services on Compute Engine. Tasks include:

    • Launching a compute instance using GCP Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)

    • Moving a persistent disk to different VM

    • Creating an autoscaled managed instance group using an instance template

    • Generating/uploading a custom SSH key for instances

    • Configuring a VM for Stackdriver monitoring and logging

    • Creating an instance with a startup script that installs software

    • Creating custom metadata tags

    • Creating a load balancer for Compute Engine instances

3.2 Deploying applications and services on Compute Engine.
00:01
  • 3.3 Deploying applications and services on Google Kubernetes Engine. Tasks include:

    • Deploying a GKE cluster

    • Deploying a containerized application to GKE

    • Configuring GKE application monitoring and logging

    • Creating a load balancer for GKE instances

    • Building a container image using Cloud Build

3.3 Deploying applications and services on Google Kubernetes Engine.
00:01
Kubernetes - Exam Bullets
00:17
  • 3.4 Deploying an application to App Engine. Considerations include:

    • Scaling configuration

    • Versions

    • Traffic splitting

    • Blue/green deployment

3.4 Deploying an application to App Engine.
00:01
3.5 Deploying a Cloud Function.
00:01
3.6 Creating data storage resources.
00:01
  • 3.7 Deploying and implementing networking resources. Tasks include:

    • Creating an auto mode VPC with subnets

    • Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, Tags, Service accounts)

    • Setting up a domain using Cloud DNS

3.7 Deploying and implementing networking resources.
00:01
3.8 Automating resource provisioning with Deployment Manager
00:01
  • 3.9 Managing Service accounts. Tasks include:

    • Creating a service account with a minimum number of scopes required

    • Downloading and using a service account private key file

3.9 Managing Service accounts.
00:02
Section 4. Integrating Google Cloud Platform Services
01:53
  • 4.1 Integrating an application with Data and Storage services. Tasks include:

    • Enabling BigQuery and setting permissions on a dataset

    • Writing an SQL query to retrieve data from relational databases

    • Analyzing data using BigQuery

    • Fetching data from various databases

    • Enabling Cloud SQL and configuring an instance

    • Connecting to a Cloud SQL instance

    • Enabling Cloud Spanner and configuring an instance

    • Creating an application that uses Cloud Spanner

    • Configuring a Cloud Pub/Sub push subscription to call an endpoint

    • Connecting to and running a CloudSQL query

    • Storing and retrieving objects from Google Storage

    • Publishing and consuming from Data Ingestion sources

    • Reading and updating an entity in a Cloud Datastore transaction from an application

    • Using the CLI tools

    • Provisioning and configuring networks

4.1 Integrating an application with Data and Storage services.
05:49
4.1 Integration with Database - Node JS and Cloud SQL - MySQL Application
14:34
4.1 Integration with Database - Node JS and Datastore application
09:11
Upcoming Lectures
00:05
4.1 Integration with DB- SQL Basics and Trade Offs - TBD
01:04
  • 4.2 Integrating an application with Compute services. Tasks include:

    • Implementing service discovery in Google Kubernetes Engine, App Engine, and Compute Engine

    • Writing an application that publishes/consumes from Cloud Pub/Sub

    • Reading instance metadata to obtain application configuration

    • Authenticating users by using Oauth2 Web Flow and Identity Aware Proxy

    • Using the CLI tools

    • Configuring Compute services network settings (e.g., subnet, firewall ingress/egress, public/private IPs)

4.2 Integrating an application with Compute services.
00:59
4.2 Integrating an application with Compute services - Service Discovery
13:50
4.2 Integrating an application with Compute services - Instance Metadata
04:39
  • 4.3 Integrating Google Cloud APIs with applications. Tasks include:

    • Enabling a GCP API

    • Using pre-trained Google ML APIs

    • Making API calls with a Cloud Client Library, the REST API, or the APIs Explorer, taking into consideration:

      • batching requests

      • restricting return data

      • paginating results

      • caching results

    • Using service accounts to make Google API calls

    • Using APIs to read/write to data services (BigQuery, Cloud Spanner)

    • Using the Cloud SDK to perform basic tasks

4.3 Integrating Google Cloud APIs with applications.
07:39

5.1 Installing the logging and monitoring agent

Section 5. Managing Application Performance Monitoring
01:11
5.1 Installing the logging and monitoring agent
00:00
  • 5.2 Managing VMs. Tasks include:

    • Debugging a custom VM image using the serial port

    • Analyzing a failed Compute Engine VM startup

    • Sending logs from a VM to Stackdriver

5.2 Managing VMs.
07:33
  • 5.3 Viewing application performance metrics using Stackdriver. Tasks include:

    • Creating a monitoring dashboard

    • Viewing syslogs from a VM

    • Writing custom metrics and creating metrics from logs

    • Graphing metrics

    • Using Stackdriver Debugger

    • Streaming logs from the GCP Console

    • Reviewing stack traces for error analysis

    • Setting up log sinks

    • Viewing logs in the GCP Console

    • Profiling performance of request-response

    • Profiling services

    • Reviewing application performance using Stackdriver Trace and Stackdriver Logging

    • Monitoring and profiling a running application

5.3 Viewing application performance metrics using Stackdriver.
00:16
  • 5.4 Diagnosing and resolving application performance issues. Tasks include:

    • Setting up time checks and other basic alerts

    • Setting up logging and tracing

    • Setting up resources monitoring

    • Troubleshooting network issues

    • Debugging/tracing cloud apps

    • Troubleshooting issues with the image/OS

    • Using documentation, forums and Google support

5.4 Diagnosing and resolving application performance issues.
00:01
Case Studies - Hiplocal - Upcoming Lectures
00:01
Cloud Developer - Practice Question Set - Still in review
50 questions
+ Professional Cloud Architect Certifications
32 lectures 02:30:45
Introduction
03:54
Professional Cloud Architect Syllabus & Exam Structure
06:19
Exam Focus and Strategy
05:24
Case Studies and its Importance
01:17
Syllabus Coverage Approach
01:05
TerramEarth - Case Study Introduction
11:48
Section 1. Designing and planning a cloud solution architecture
00:27
  • 1.1 Designing a solution infrastructure that meets business requirements. Considerations include:

    • business use cases and product strategy

    • cost optimization

    • supporting the application design

    • integration

    • movement of data

    • tradeoffs

    • build, buy or modify

    • success measurements (e.g., Key Performance Indicators (KPI), Return on Investment (ROI), metrics)

    • Compliance and observability

    • Provisioning one or more Stackdriver accounts.

1.1 Designing a solution infrastructure that meets business requirements.
04:02
  • 1.2 Designing a solution infrastructure that meets technical requirements. Considerations include:

    • high availability and failover design

    • elasticity of cloud resources

    • scalability to meet growth requirements

1.2 Designing a solution infrastructure that meets technical requirements
03:53
  • 1.3 Designing network, storage, and compute resources. Considerations include:

    • integration with on premises/multi-cloud environments

    • Cloud native networking (VPC, peering, firewalls, container networking)

    • identification of data processing pipeline

    • matching data characteristics to storage systems

    • data flow diagrams

    • storage system structure (e.g., Object, File, RDBMS, NoSQL, NewSQL)

    • mapping compute needs to platform products

1.3 Designing network, storage, and compute resources
07:30
  • 1.4 Creating a migration plan (i.e., documents and architectural diagrams). Considerations include:

    • integrating solution with existing systems

    • migrating systems and data to support the solution

    • licensing mapping

    • network and management planning

    • testing and proof-of-concept

1.4 Creating a migration plan (i.e., documents and architectural diagrams).
04:32
  • 1.5 Envisioning future solution improvements. Considerations include:

    • cloud and technology improvements

    • business needs evolution

    • evangelism and advocacy

1.5 Envisioning future solution improvements. Considerations include:
02:30
  • 2.1 Configuring network topologies. Considerations include:

    • extending to on-premise (hybrid networking)

    • extending to a multi-cloud environment which may include GCP to GCP communication

    • security

    • data protection

2.1 Configuring network topologies.
01:54
  • 2.2 Configuring individual storage systems. Considerations include:

    • data storage allocation

    • data processing/compute provisioning

    • security and access management

    • network configuration for data transfer and latency

    • data retention and data lifecycle management

    • data growth management

2.2 & 2.3 Configuring individual storage & Compute Systems
02:29
  • 3.1 Designing for security. Considerations include:

    • Identity and Access Management (IAM)

    • Resource hierarchy (organizations, folders, projects)

    • data security (key management, encryption)

    • penetration testing

    • Separation of Duties (SoD)

    • security controls

    • Managing customer-supplied encryption keys with Cloud KMS

Section 3 : Designing for security & Compliance
03:09
  • 3.2 Designing for legal compliance. Considerations include:

    • legislation (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children’s Online Privacy Protection Act (COPPA), etc.)

    • audits (including logs)

    • certification (e.g., Information Technology Infrastructure Library (ITIL) framework)

3. Applying Security and Compliance
04:46
4.1 Analyzing and defining technical processes
00:50
4.2 Analyzing and defining business processes.
03:49
4.3 Developing procedures to test resilience of solution in production
03:09
  • 5.1 Advising development/operation team(s) to ensure successful deployment of the solution. Considerations include:

    • application development

    • API best practices

    • testing frameworks (load/unit/integration)

    • data and system migration tooling

5.1 Advising development/operation team(s) to ensure successful deployment
01:21
  • 5.2 Interacting with Google Cloud using GCP SDK (gcloud, gsutil and bq). Considerations include:

    • local installation

    • Google Cloud Shell

5.2 Interacting with Google Cloud using GCP SDK (gcloud, gsutil and bq).
00:56
Section 6. Ensuring solution and operations reliability
01:47
Mountkirk Games - Case Study Introduction
07:20
Mountkirk Games - As is Architecture
02:22
MountKirk Games -Section 1. Designing and planning a cloud solution architecture
06:26
MountKirk Games -Section 1. Designing and planning a cloud solution arch Part2
07:49
MountKirk Games -Section 1. Designing and planning - Resiliency , Scalibility
13:07
MountKirk Games -Section 2. Managing and Provisioning a solution Infrastructure
11:10
MountKirk Games -Section 4. Analyzing and optimizing technical and business Proc
03:26
MountKirk Games -Section 5. Managing implementation
02:21
MountKirk Games -Section 6. Ensuring solution and operations reliability
04:54
Dress4Win
14:59
Practice Question Set 1 - Cloud Architect Certification
50 questions
Practice Question Set 2 - Cloud Architect Certification
50 questions
+ Upcoming Jul 2020 -> Professional Cloud Data Engineer Certifications
29 lectures 00:14
Introduction
00:00
Professional Cloud Data Engineer Syllabus & Exam Structure
00:00
Exam Focus and Strategy
00:00
Case Studies and Importance
00:00
Section 0: Data Engineer Foundation
00:00
Artificial Intelligence Fundamentals
00:00
AI in Google Cloud Platform.
00:00
Machine Learning Fundamentals
00:00
Machine Learning in Google Cloud Platform.
00:00
Section 1. Designing data processing systems
00:00
  • 1.1 Selecting the appropriate storage technologies. Considerations include:

    • Mapping storage systems to business requirements

    • Data modeling

    • Tradeoffs involving latency, throughput, transactions

    • Distributed systems

    • Schema design

1.1 Selecting the appropriate storage technologies.
00:00
  • 1.2 Designing data pipelines. Considerations include:

    • Data publishing and visualization (e.g., BigQuery)

    • Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)

    • Online (interactive) vs. batch predictions

    • Job automation and orchestration (e.g., Cloud Composer)

1.2 Designing data pipelines.
00:00
  • 1.3 Designing a data processing solution. Considerations include:

    • Choice of infrastructure

    • System availability and fault tolerance

    • Use of distributed systems

    • Capacity planning

    • Hybrid cloud and edge computing

    • Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)

    • At least once, in-order, and exactly once, etc., event processing

1.3 Designing a data processing solution.
00:00
  • 1.4 Migrating data warehousing and data processing. Considerations include:

    • Awareness of current state and how to migrate a design to a future state

    • Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)

    • Validating a migration

1.4 Migrating data warehousing and data processing.
00:00
Section 2. Building and Operationalizing Data Processing Systems
00:00
  • 2.1 Building and operationalizing storage systems. Considerations include:

    • effective use of managed services (Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Cloud Datastore, Cloud Memorystore)

    • storage costs and performance

    • lifecycle management of data

2.1 Building and operationalizing storage systems.
00:00
  • 2.2 Building and operationalizing pipelines. Considerations include:

    • data cleansing

    • batch and streaming

    • transformation

    • data acquisition and import

    • Integrating with new data sources

2.2 Building and operationalizing pipelines.
00:00
2.3 Building and operationalizing processing infrastructure.
00:00
Section 3. Operationalizing Machine Learning Models
00:00
  • 3.1 Leveraging pre-built ML models as a service. Considerations include:

    • ML APIs (e.g., Vision API, Speech API)

    • customizing ML APIs (e.g., AutoML Vision, Auto ML text)

    • conversational experiences (e.g., Dialogflow)

3.1 Leveraging pre-built ML models as a service.
00:00
3.2 Deploying an ML pipeline.
00:00
3.3 Choosing the appropriate training and serving infrastructure.
00:00
  • 3.4 Measuring, monitoring, and troubleshooting machine learning models. Considerations include:

    • Machine Learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)

    • Impact of dependencies of machine learning models

    • Common sources of error (e.g., assumptions about data)

3.4 Measuring, monitoring, and troubleshooting machine learning models.
00:00
Section 4. Ensuring Solution Quality
00:00
  • 4.1 Designing for security and compliance. Considerations include:

    • identity and access management (e.g., Cloud IAM)

    • data security (encryption, key management)

    • ensuring privacy (e.g., Data Loss Prevention API)

    • legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))

4.1 Designing for security and compliance.
00:00
  • 4.2 Ensuring scalability and efficiency. Considerations include:

    • building and running test suites

    • pipeline monitoring (e.g., Stackdriver)

    • assessing, troubleshooting, and improving data representations and data processing infrastructure

    • resizing and autoscaling resources

4.2 Ensuring scalability and efficiency.
00:00
  • 4.3 Ensuring reliability and fidelity. Considerations include:

    • performing data preparation and quality control (e.g., Cloud Dataprep)

    • verification and monitoring

    • planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)

    • choosing between ACID, idempotent, eventually consistent requirements

4.3 Ensuring reliability and fidelity.
00:00
  • 4.4 Ensuring flexibility and portability. Considerations include:

    • mapping to current and future business requirements

    • designing for data and application portability (e.g., multi-cloud, data residency requirements)

    • Data staging, cataloging and discovery

4.4 Ensuring flexibility and portability.
00:00
TBD - Practice Questions Set
00:00
+ Upcoming Cloud DevOps Engineer - Aug 2020.
1 lecture 00:03
Introduction to Cloud Devops Certifications
00:03
+ Bonus - Professional Cloud network Engineer Certifications
44 lectures 03:03:27
Introduction
02:03
Professional Network Engineer Certifications
12:08
Exam Focus and Strategy
00:00
Section 1. Designing, Planning, and Prototyping a GCP Network
08:38
  • 1.1 Designing the overall network architecture. Considerations include:

    • Failover and disaster recovery strategy

    • Options for high availability

    • DNS strategy (e.g., on-premises, Cloud DNS, GSLB)

    • Meeting business requirements

    • Choosing the appropriate load balancing options

    • Optimizing for latency (e.g., MTU size, caches, CDN)

    • Understanding how quotas are applied per project and per VPC

    • Hybrid connectivity (e.g., Google private access for hybrid connectivity)

    • Container networking

    • IAM and security

    • SaaS, PaaS, and IaaS services

    • Microsegmentation for security purposes (e.g., using metadata, tags)

1.1 Designing the overall network architecture.
05:18
Designing the overall network - Options for HA
05:12
Designing the overall network - Options for Load Balancer
04:39
Designing the overall network - CDN
02:39
Designing the overall network - Project and Network Quota
03:15
Designing the overall network - Hybrid Connection
02:49
Designing the overall network - SAAS PAAS IAAS
07:19
1.2 Designing a Virtual Private Cloud (VPC).
00:01
  • 1.3 Designing a hybrid network. Considerations include:

    • Using Interconnect (e.g., dedicated vs. partner)

    • Peering options (e.g., direct vs. carrier)

    • IPsec VPN

    • Cloud Router

    • Failover and disaster recovery strategy (e.g., building high availability with BGP using cloud router)

    • Shared vs. standalone VPC Interconnect access

    • Cross-organizational access

    • Bandwidth

1.3 Designing a hybrid network.
00:01
1.4 Designing a Container IP Addressing plan for Google Kubernetes Engine
04:38
Section 2. Implementing a GCP Virtual Private Cloud (VPC)
00:47
  • 2.1 Configuring VPCs. Considerations include:

    • Configuring GCP VPC resources (CIDR range, subnets, firewall rules, etc.)

    • Configuring VPC Peering

    • Creating a shared VPC and explaining how to share subnets with other projects

    • Configuring API access (Private, Public, NAT GW, Proxy)

    • Configuring VPC flow logs

2.1 Configuring VPCs.
11:37
VPC Peering
02:09
Configuring VPC - Share VPC
12:03
  • 2.2 Configuring routing. Tasks include:

    • Configuring internal static/dynamic routing

    • Configuring routing policies using tags and priority

    • Configuring NAT (e.g., CloudNAT, instance-based NAT)

2.2 Configuring routing.
12:53
  • 2.3 Configuring and maintaining Google Kubernetes Engine clusters. Considerations include:

    • VPC-native Clusters using Alias IPs

    • Clusters with Shared VPC

    • Private Clusters

    • Cluster Network policy

    • Adding authorized networks for Cluster Master Access

2.3 Configuring and maintaining Google Kubernetes Engine clusters.
21:45
2.3 Configuring and maintaining Google Kubernetes Engine clusters - Part 2
08:28
  • 2.4 Configuring and managing firewall rules. Considerations include:

    • Target network tags and service accounts

    • Priority

    • Network protocols

    • Ingress and egress rules

    • Firewall logs

2.4 Configuring and managing firewall rules.
20:36
Section 3. Configuring Network Services
00:01
  • 3.1 Configuring load balancing. Considerations include:

    • Creating backend services

    • Firewall and security rules

    • HTTP(S) load balancer: including changing URL maps, backend groups, health checks, CDN, and SSL certs

    • TCP and SSL Proxy Load Balancers

    • Network load balancer

    • Internal load balancer

    • Session affinity

    • Capacity scaling

3.1 Configuring load balancing.
00:01
  • 3.2 Configuring Cloud CDN. Considerations include:

    • Enabling and disabling Cloud CDN

    • Using cache keys

    • Cache invalidation

    • Signed URLs

3.2 Configuring Cloud CDN.
00:01
  • 3.3 Configuring and maintaining Cloud DNS. Considerations include:

    • Managing zones and records

    • Migrating to Cloud DNS

    • DNS Security (DNSSEC)

    • Global serving with Anycast

    • Cloud DNS

    • Internal DNS

    • Integrating on-premises DNS with GCP

3.3 Configuring and maintaining Cloud DNS.
00:01
  • 3.4 Enabling other network services. Considerations include:

    • Health checks for your instance groups

    • Canary (A/B) releases

    • Distributing backend instances using regional managed instance groups

    • Enabling private API access

3.4 Enabling other network services.
00:01
Section 4. Implementing Hybrid Interconnectivity
00:01

4.1 Configuring Interconnect. Considerations include:

    • Partner (e.g., Layer 2 vs. Layer 3 connectivity)

    • Virtualizing using Vlan attachments

    • Bulk storage uploads

    4.2 Configuring a site-to-site IPsec VPN (e.g., route-based, policy-based, dynamic or static routing).

    4.3 Configuring Cloud Router for reliability.

4.1 Configuring Interconnect.
00:02

4.2 Configuring a site-to-site IPsec VPN (e.g., route-based, policy-based, dynamic or static routing).

4.2 Configuring a site-to-site IPsec VPN
00:01
4.3 Configuring Cloud Router for reliability.
00:01
Section 5. Implementing Network Security
07:47
  • 5.1 Configuring Identity and Access Management (IAM). Tasks include:

    • Viewing account IAM assignments

    • Assigning IAM roles to accounts or Google Groups

    • Defining custom IAM roles

    • Using pre-defined IAM roles (e.g., network admin, network viewer, network user)

5.1 Configuring Identity and Access Management (IAM).
00:01
  • 5.2 Configuring Cloud Armor policies. Considerations include:

    • IP-based access control

5.2 Configuring Cloud Armor policies.
07:09
5.3 Configuring third-party device insertion into VPC using multi-nic (NGFW)
01:47
5.4 Managing keys for SSH access
05:19
Section 6. Managing and Monitoring Network Operations
00:01
6.1 Logging and monitoring with Stackdriver or GCP Console
00:01
  • 6.2 Managing and maintaining security. Considerations include:

    • Firewalls (e.g., cloud-based, private)

    • Diagnosing and resolving IAM issues (shared VPC, security/network admin)

6.2 Managing and maintaining security.
00:01
  • 6.3 Maintaining and troubleshooting connectivity issues. Considerations include:

    • Identifying traffic flow topology (e.g., load balancers, SSL offload, network endpoint groups)

    • Draining and redirecting traffic flows

    • Cross-connect handoff for Interconnect

    • Monitoring ingress and egress traffic using flow logs

    • Monitoring firewall logs

    • Managing and troubleshooting VPNs

    • Troubleshooting Cloud Router BGP peering issues

6.3 Maintaining and troubleshooting connectivity issues.
00:01
  • 6.4 Monitoring, maintaining, and troubleshooting latency and traffic flow. Considerations include:

    • Network throughput and latency testing

    • Routing issues

    • Tracing traffic flow

6.4 Monitoring, maintaining, and troubleshooting latency and traffic flow.
00:01
Section 7. Optimizing Network Resources
00:30
  • 7.1 Optimizing traffic flow. Considerations include:

    • Load balancer and CDN location

    • Global vs. Regional dynamic routing

    • Expanding subnet CIDR ranges in service

    • Accommodating workload increases (e.g., autoscaling vs. manual scaling)

7.1 Optimizing traffic flow.
05:45
  • 7.2 Optimizing for cost and efficiency. Considerations include:

    • Cost optimization (Network Service Tiers, Cloud CDN, autoscaler (max instances))

    • Automation

    • VPN vs. Interconnect

    • Bandwidth utilization (e.g., kernel sys tuning parameters)

7.2 Optimizing for cost and efficiency.
05:53