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Google ACE Crash Course | Practice Q&A | Pass Google Associate Cloud Engineer Exam

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This content is a comprehensive crash course for the Google Associate Cloud Engineer certification exam, offering free training and 206 real exam questions to prepare individuals for managing and optimizing Google Cloud Platform (GCP) services.

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Hello and welcome to Tech with Shaping

Pixel. We are bringing you free

certification course. This time we are

bringing Google's associate cloud

engineer certification exam crash

course. We have also included 206 real

exam question answers with this crash course.

Are you ready to evaluate your cloud

skills? This learning path is designed

to prepare you for Google's associate

cloud engineer certification exam, but

it's also perfect for anyone looking to

enhance their cloud expertise. The exam

tests your knowledge in five key areas:

setting up a cloud environment, planning

and configuration solutions, deploying

and implementing those solutions,

maintaining operations, and securing

your environment with access policies.

We start with an overview of Google

Cloud Platform's main products and

services. You will learn how to set up a

development environment and install the

Google Cloud software development kit.

Next, dive into configuring networks and

creating virtual machines. Topics

include autoscaling, load balancing, and

network security. You will understand

concepts like network address

translation and configuring a cloud

virtual private network. Then explore

containers using Google Kubernetes

Engine, App Engine, and Cloud Run. Learn

to use identity and access management to

Cloud offers powerful compute options

from virtual machines to Kubernetes

engine. You can scale your application

seamlessly. These services ensure high

performance and flexibility for your workloads.

workloads.

Google Cloud provides robust storage

solutions whether you need object

storage, file storage or databases.

Their offering like cloud storage and

bigquery cater to diverse data needs efficiently.

efficiently.

Networking in cloud Google cloud is

designed for speed and security with

virtual private cloud cloud load

balancing and cloud CDN. You can

optimize traffic and ensure reliable

connectivity across the globe. Google

Cloud excels in AI and machine learning.

Tools like TensorFlow, AutoML, and AI

platform help you build, deploy, and

scale intelligent applications with

ease, leveraging Google's advanced AI capabilities.

capabilities.

Security and operations are paramount in

Google Cloud. Services like identity and

access management, cloud security,

command center, and operation suit

ensure your infrastructure is secure and

well managed. So stay connected, stay

updated as Google continuously innovates.

Google Cloud Platform or GCP is a public

cloud vendor offering a collection of

virtual non-demand services. It allows

anyone to build, host, and deliver

applications using the same hardware and

software that powers Google services

like search, Gmail, and Google Docs. One

of the main advantages of using GCP is

access to Google's global network and

vast experience in serving applications

to billions of users.

This means you can leverage their

infrastructure without the hustle and

cost of building and maintaining your

own data centers.

With GCP, resources are available on

demand wherever and whenever you need

them. This flexibility is complemented

by a wide range of services including

artificial intelligence, machine

learning, big data, internet of things,

healthcare, and gaming. The options are

almost endless. To make it easier to

navigate, GCP services are divided into

five main categories. compute, storage,

networking, artificial intelligence and

machine learning and security and

operations. In the coming up, we will

explore each category in more detail

giving you a comprehensive understanding

Google Cloud Platform offers a variety

of compute services to run your code.

Whether you need virtual machines,

containers, or serverless options, GCP

has you covered.

For virtual machines, Google's Compute

Engine is the go-to service. It supports

both Linux and Windows with predefined

and custom machine types. Compute Engine

is ideal for building from scratch or

migrating existing infrastructure.

Containers are lightweight alternatives

to virtual machines. Google Kubernetes

Engine RGke

simplifies deploying, maintaining, and

scaling containerized applications. It

includes features for logging,

monitoring, and health management.

For hybrid environments, Anthos allows

you to run containers across multiple

locations, including on premises, GCP,

and AWS. Anthos provides unified command

interface for seamless management.

App Engine is Google's platform as a

service offering. It lets you run web

and mobile applications without managing

the underlying infrastructure. Just

upload your code and GCP handles the

For single container applications, Cloud

Run offers a serverless solution. Upload

your container and cloud run deploys it

as a stateless autoscaling service.

Cloud functions are perfect for small

singlepurpose functions that responds to

events. They add extra functionality

without the complexity of larger

applications. Choose Compute Engine for

Windows applications, App Engine for

Java or Python apps, Cloud Run for

single containers, JKE for multiple

containers, Anthos for hybrid

environments, and Cloud Functions for

Let's explore the main storage services

available on Google Cloud Platform or GCP.

GCP.

Data can be structured like names and

dates or unstructured like music and

photos. Different types of data require

different storage solutions. For

unstructured data, Google Cloud Storage

is ideal. It's fast, secure, and has

almost unlimited capacity. Perfect for

web pages, log files, or data links.

Google Cloud Storage offers four classes.

classes.

Standard for frequently accessed data,

nearline for monthly access, code line

for quarterly access and archive for

annual access. All provide immediate

life file access. Cloud storage uses

object storage meaning no directories

just buckets. For traditional file

systems with block level access, use

file store which supports NFS

compatibility file shares. For

structured data, cloud SQL supports

MySQL, PostgresSQL, and Microsoft SQL

Server for higher performance. Use cloud

spanner for big data analytics. BigQuery

is the go-to solution. In summary,

choose cloud storage for files, file

store for editable files, cloud SQL for

standard databases, cloud spanner for

large workloads, and BigQuery for analytics.

Google Cloud Platform offers virtual

private clouds or VPCs which allow you

to organize and share resources. VPCs

are logically isolated networks that can

group or separate virtual machines and

containers. You can also divide a VPC

into sub networks and define traffic

rules. By default, all incoming traffic

to a VPC is blocked and all outgoing

traffic is allowed. You can create

firewall rules to override this

behavior, blocking outbound traffic or

allowing external access to a public web

server. To connect VPC to an external

network, you can use CloudVPN for secure

encrypted traffic over the internet. For

higher security and reliability, cloud

interconnect provides a direct dedicated

connection to Google. Direct peering is

another option coordinated

with your local internet service

provider. Load balancers distribute

network traffic among resources to

prevent any single part from being

overwhelmed. Cloud Armor works with load

balancers to defend against application

and denial of service attacks, ensuring

Cloud DNS manages millions of DNS

records for both public and private

domains. Cloud CDN accelerates web and

applications. Content delivery using

Google's globally distributed catches

enhancing performance and user

experience. These are the key networking

services on Google Cloud Platform

designed to keep your resources

Google Cloud Platform or GCP offers some

of the most exciting services in

artificial intelligence and machine

learning. Let's dive into what makes

these services stand out. Artificial

intelligence or AI aims to give machine

humanlike intelligence. Machine learning

or ML is a branch of AI focused on

systems that learn from data to improve

over time. On the side, GCP offers the

vision API to detect objects and faces

in images, the video intelligence API to

recognize actions in videos and document

AI to pass data in documents. Language

services include the translation API

which supports over 100 languages and

the natural language API which performs

sentiment analysis to classify messages

as positive, negative or neutral.

Conversation services feature text to to

speech and uh speechtoext APIs and

dialogue flow which generates realistic

dialogue for chat bots and voice bots

perfect for customer support. Structured

data services like recommendations, AI

suggest products based on past purchases

while cloud talent solutions helps match

JS job seekers with the right

opportunities for specific needs. GCP

offers AutoML to train custom models

without deep ML knowledge. For more

advanced requirements, Vortex AI

provides tool for building and deploying

Security services on Google Cloud

Platform or GCP help protect your data.

Privacy is crucial and security is the

method to achieve it. Policies pres

essential to safeguard your customers

and company often shaped by compliance

requirements. GCP offers several

security services. Security command

center provides a centralized control

panel for discovering vulnerabilities

and detecting threats. Secret manager

stores passwords, API keys, and

certificates securely. Data loss

prevention or DLP identifies and scrubs

sensitive data such as credit card

numbers from user records before

responding to database queries.

Operation services on GCP focuses on

monitoring and maintaining your

infrastructure. These tools ensure your

systems run smoothly and efficiently

providing insights and auto automation

to manage your resources effectively.

The Google cloud operation suit include

cloud logging for centralized log

management and cloud monitoring for

tracking metrics like CPU utilization

and network traffic.

Cloud debugger helps find software bugs

while cloud profiler and cloud trace

identify latency issues. Cloud

deployment manager automates resources

provisioning. Cloud build automates code

deployment. Age design secure APIs and

cloud composer manages workflows across

Let's do a quick recap on what we have

learned so far. So, Google Cloud

Platform offers powerful compute

services. Compute Engine manages virtual

machines while Kubernetes engine handles

containers. For hybrid environments,

Anthos is the go-to preferred managed

serverless options.

Use app engines for web apps, cloud run

for single containers, and cloud

functions for event-driven functions.

For storage, Google cloud has you

covered. Cloud storage is the perfect

for file storage. Needs SQL databases,

choose cloudsql, cloud spanner or

bigquery. For NoSQL databases, fire

store, firebase and big table are the

best options. Network is crucial. So,

private network clouds or VPC isolate or

connect your virtual machines. CloudVPN

interconnect and peering link your

company network to Google Cloud

Platform. Load balancer distributes

traffic and cloud armor protects against

Google Cloud excels in AI and machine

learning. Use AutoML to train custom

models. An AI hub for plug-in and play

components. services cover site,

language, conversation, and structured

data, making it easier to integrate AI

into your applications.

Security and operations are vital.

Security Manager stores passwords and

keys securely. Cloud Debugger inspects

running applications while cloud

profiler and cloud trays identify

latency issues. Age helps build

scalable, secure APIs. That's a wrap on

cloud Google cloud platform from compute

to AI. It offers comprehensive

solutions. Explore more courses on our

YouTube channel and enhance your cloud

skills. Thanks for watching.

So before you can start building on

Google Cloud Platform, you need a

project. Projects help organize all your

resources including users, APIs, and

billing information. To create a

project, you log into your Google Cloud

Console, click the project selector

drop-down, and then new project. Name

your project like photo blog and let

Google generate a unique project ID.

Once your project is created, you can

add resources for a photo blog. You

might add a compute engine instance for

WordPress, a cloud SQL database for

post, and a cloud storage bucket for

photos. Organizing resources into

projects prevents confusion and enhances

security. It ensures you won't mix up

production and development databases and

simplifies resources management.

Deleting a project removes all

associated resources. To delete P

project go to IM and admin then manage

resources. Select the project. Click

delete and confirm by entering the

project ID. Projects has marked for

deletion for 30 days allowing recovery

So managing user accounts and roles in

Google cloud platform is essential for

any organization. Different users have

different needs and is crucial to assign

the right permission to ensure smooth

operations. Each project in Google cloud

platform has its own set of users each

with unique permissions. Some users need

full access while others need only need

to view or make changes specific

changes. You can manually create user

accounts or automate the process using

tools like Google Cloud Direct Directory

Sync. This is especially useful for

large companies with hundreds of

thousands of users.

So permissions are managed by assigning

roles to users. Instead of assigning

individual permissions, you group them

into roles. These saves time and ensures

users have the necessary permissions to

perform their tasks. There are three

main types of roles. basic, predefined,

and custom. Basic roles offer broad

permissions. Predefined roles are more

specific, and custom roles allow you to

tailor permissions to your exact needs.

So, understanding and managing your

permissions is crucial. Start by

assigning minimal permission and adjust

as needed. These ensure security and

efficiency in your Google Cloud Platform projects.

To access certain Google Cloud

resources, you need to enable the

corresponding API. Google Cloud APIs

provide access to various services, but

many are disabled by default. Suppose

you want to interact with the users

Google Calendar. First, ensure you have

the correct project selected. Navigate

to APIs and services and select

dashboard. Click enable APIs and

services. Search for Google Calendar API

and click enable. Some APIs require

extra steps beyond enabling. For

instance, you might need to accept terms

of service or create credentials. Verify

the API is enabled by checking the

dashboard. When you no longer need an

API, you can disable it. Select the API

and click disable API at the top of the

page. Confirm it was disabled by

checking the dashboard again. Only

enable the APIs you need to avoid

unnecessary costs. Disabling unused APIs

ensures you don't accidentally use them,

helping you manage your resources efficiently.

Managing billing on Google Cloud

Platform is crucial. You start with a

$300 free trial for 90 days, but

eventually you will need to pay for services.

services.

To add a new billing account, click

billing in the navigation menu, then

manage billing accounts. Click create

account. Assign a name. Select a country

and submit. Now you have multiple

billing accounts. To link a project to a

new billing account, go to account

management. Select the project. Then

modify it to use the new billing

account. Confirm the changes. To disable

billing for a project, click the action

buttons next to the project. Select

disable billing and confirm. Remember,

you are still responsible for

outstanding charges. Creating a budget

helps monitor spending. For the billing

page, click budgets and alerts. Then

create budget. Set a name, scope, and

amount. Defin define uh notification

thresholds to receive alerts when

spending exceed certain percentages.

So to generate a billing export, select

billing export from build the billing

page. Choose to export all cost, confirm

the project and create a new bigquery

data set. These help in detailed analysis.

Let's review how to set up a Google

Cloud Platform environment. First,

create and delete projects to manage and

organize your Google Cloud Platform

accounts. Projects are essential for

structuring your resources. Next, create

user accounts and design permissions via

roles. Remember the three types, basic,

predefined, and custom. Basic roles like

viewer and editor are simple but not

secure. Predefined roles are more

granular. If none fit, create custom

roles. Avoid using basic roles in real environment.

environment.

Then enable APIs to access various

Google services like compute, storage,

and networking. Control project

resources by enabling or disabling the

associated API. Finally, add a billing

account to specify payment methods for

services. Projects can share billing

accounts or have a separate ones. Set

spending alerts by creating a budget and

analyze spending with billing exports.

That's a quick review of setting up your

The Google Cloud Software Development

Kit or Cloud SDK lets you manage your

Google Cloud Platform account through

terminal commands. It simplifies tasks

and automates repeatable process. To get

started, use CloudShell, an online

terminal in the Google Cloud Console. It

comes pre-installed with Cloud SDK. Just

you're ready to go. Cloud SDK includes

several key commands. G G-Cloud for

common cloud tasks. Gsil for Google

storage and BQ for BigQuery. These

commands streamline your workflow significantly.

significantly.

G-Cloud is the main utility for task

like installing components, spinning up

comput engine instances, and deploying

apps to App Engine. It's your go-to for

most cloud operations. GSUTIL

GSUTIL

or Google storage utility helps manage

cloud storage buckets and objects. It's

essential for handling your storage

needs efficiently.

BQ is used for interacting with

BigQuery. Run queries and manipulate

data sets effortlessly with this command.

Installing the Google Cloud SDK on your

machine can be more convenient than

using the integrated CloudShell. Let's

walk through the process of downloading,

installing, and setting up the SDK.

First, visit cloud.google.com/dk/doccks/install

for detailed instructions.

Download the installer for your

operating system, run it, and follow the

prompts. Choose the installation method

that best suits your needs.

After installation, verify it by running

G-Cloud help in your terminal. If you

see the help screen, you're good to go.

If not, revisit the installation

instructions to troubleshoot. Next, run

G-Cloud in it to authorize access to

your Google account. Follow the prompts,

If you are behind a proxy, configure

your proxy settings as needed. The SDK

comes with default components, but you

can install additional ones. Use G-Cloud

components list to see available

components. For example, install the

Google app engine Java component with

G-Cloud components. Install app/ engine/ java.

Google Compute Engine on Google Cloud

Platform lets you design and build

custom data centers in the cloud.

With Compute Engine, you have almost

complete control. Choose your hardware

operating system and install any

applications you need. It offers deep

customization and control. There are

various preconfigured machine types.

General purpose for website compute

optimized for performance tasks. Memory

optimized for large databases and

accelerator optimized for graphic

rendering and machine learning. Compute

engine can save you money.

You only pay for what you use and there

there are discounts for sustained and

committed use. Spot VMs offers

short-term savings for fall tolerant

workloads. Compute Engine is a versatile

and cost effective making it a great

step for moving to the cloud. Start by

Creating and managing virtual machines

with Google Compute Engine can seem

overwhelming. Let's focus on the main

features to get you started quickly and

efficiently. First, log into the Google

Cloud Platform console. Navigate to

Compute Engine by either using the

navigation menu or the search bar. You

will see a list of your current VMs. To

create a new VM instance, click on

create instance. You can create it from

scratch, a template, or a machine engine.

engine.

So, we will focus on creating one from

scratch. Fill out the form with details

like the instance name, region, and

zone. Choose your machine configuration,

including the type and amount of memory.

Adjust the boot disk and firewall

settings as needed. Once your VM is

running, Google provides a detailed logs

and monitoring tools. These help you

track metrics like CPU utilization and

network traffic. For advanced metrics,

install the ops agent. And that's it.

You have created and configured a VM

instance on Google Compute Engine. With

these basics, you are ready to explore

more advanced features and optimize your machine

machine

Now that you know how to create a basic

virtual machine, let's explore some

advanced options to enhance your next step.

step.

In the networking section, you can

customize your networking interfaces.

Choose the virtual private cloud or VPC

and a sub network for your instance.

These allows for better network

management and segmentation. You can set

your internal IP address to be dynamic

or static. Empiral

IPS change when an instance is stopped

or deleted. For a consistent IP, reserve

a static one. The same options apply to

external IP addresses, including the

option to have one for added security.

In the disk section, you can add and

attach additional disk drives. The

security section offers various options

to enhance your VM security. You can

also add your own secure shell or SSH

keys for custom access. Under

management, you can handle committed use

discounts and switch to spot instances.

Spot instances are cheaper but less

reliable, suitable for specific

workloads. They can save you money if

used correctly. Finally, you can create

a VM using a command line. Click to get

the exact command. paste it into your

terminal with the cloud software

development kit or SDK installed and

Managing a few virtual machines manually

is fine, but what if you need hundreds

of thousands? Let's explore how

templates and machine images can

simplify this process. Start by creating

a VM template. Click create instance

template and fill out the form with your

desired settings. This template saves

all your VM configuration making it easy

to replicate.

Once your template is ready, use it to

create new instances. Select your

template, make any necessary

arrangements, adjustments, and click

create. This method ensures consistency

across multiple VMs. A machine image

goes a step further. It captures the

entire state of a VM including installed

software. Create a machine image by

selecting an existing VM and clicking

create new machine image. To use a

machine image, create a new instance and

create select create from machine image.

These replicates the original VM

including all software and

configurations saving you time and

effort. To delete VM, select the

instances, click more actions and choose

delete. You can delete multiple

instances simultaneously. Streamlining

your management process.

Using templates and machine images makes

Before creating virtual machine

instances on Google Cloud Platform, it's

crucial to understand quotas. Kotas

prevent excessive resources consumption

and cap spending to avoid unexpected

bills. Let's explore how to view and

manage your quotas.

First, log into your GCP console. Search

for quotas and click on all quotas. This

page displays all quotas for your

project, including compute engine and

API gateway. You can filter to view

specific services.

To focus on a particular service, use

the filter option. For example, filter

by compute engine to see related

quoters. These help you monitor your

usage and identify if you're nearing any

limits. If you need to exceed a kota,

request a change, filter for your kota

like the number of virtual machine

instances per region. Select the kota to

change. Then click edit quotas. Fill out

the form specifying the new limit and justification.

justification.

After providing your contact details,

submit the request. Google will review

and respond which might take a day or

two. Now you know how to manage kas

Google Cloud Platform allows you to

build virtual data centers in the cloud.

One crucial component is the underlaying

network. Since you can't physically

access Google's hardware, connectivity

is essential for everything you build in

Google Cloud Platform. With many

customers using Google Cloud Platform,

isolation is key. Company A and Company

B, for example, need separate networks

to avoid conflicts like IP collisions.

Virtual private cloud solves these by

allowing complete isolation while

accessing the same resources.

VPCs let you create private virtual

networks broken down into subn networks

or subnets. You can keep things simple

with one VPC or get complex with

multiple VPCs and subnets.

You have the option to manually manage

settings or let Google handle them.

One standout feature of VPC is their

global nature. Servers across different

regions like the United States, United

Kingdom and China can communicate within

the same VPC.

Alternatively, you can isolate them by

creating a separate VPCs.

Google VPCs balance connectivity with

security. You can create open VPCs for

public servers or lock down VPCs for

private applications.

Using Google private access, you can

disable internet access while

maintaining connectivity to other Google

As your networking needs evolve, you

might need to modify your existing

virtual private cloud or VPC. Let's see

how. First, go to the VPC network page.

Ensure the VPC network option is

selected on the left. Click the network

name you wish to modify, then hit edit.

To edit roots, go to the roots tab,

select a region, then click on the

specific route to modify it. For new

roots, use root management.

In the firewalls tab, you can add,

delete, or edit firewall rules. Click

add firewall rule to create a new one or

select an existing rule to modify or

delete it. The subnets tab allows you to

add, edit, or delete subnets. Click on

the subnet name, then choose edit or

delete to make changes.

To expand a subnet IP range, click edit

and modify the CID range. Remember, the

new range must be a supererset of the

old one and cannot overlap with other

subnets. For example, changing a /16 to

a /15 doubles, the IBS must but must

follow CID rules.

Proper planning is crucial to avoid

issues. Expanding subnets can be done

without downtime, but always ensure your

addressing scheme accommodates future growth.

Google creates multiple copies of

everything. All data is duplicated and

stored in multiple locations. Servers

are replicated across multiple instances

by having redundant copies of

everything. Their services can survive

hardware failure, software glitches, and

even network outages without losing data

or functionality.

Having multiple copies isn't useful

unless you can access one of them.

Google spreads its copies across

different geographic regions. So even

when an entire country goes offline,

Google services are still accessible to

everyone else.

Google has failover mechanisms to

automatically handle most problems. When

a server or data center becomes

unavailable, traffic is instantaneously

redirected to another location. These

ensures uninterrupted service

because its services are distributed.

Google can easily adjust the number of

instances as required. When traffic

increases, servers are added to handle

the additional load. When traffic

decreases, servers are removed to lower costs.

costs.

Cloud load balancers provide a single

point of entry for resources.

They intelligently distribute request

based on server health, capacity, and

location. These ensures no part of your

infrastructure gets overwhelmed.

Optimizing performance and reducing latency.

Google Cloud Platform offers various

load balancers tailored for specific workloads.

workloads.

Let's break them down using four main attributes.

attributes.

Access type.

Load balances can be internal or

external. Internal load balancers use

private IP addresses accessible only

within Google Cloud. External load

balancers use public IP addresses

accessible from anywhere on the

internet. Choose based on whether your

service is internal or public facing.

Next scope load balances can be regional

or global.

Regional load balancers distribute

traffic across multiple jones ensuring

servicing service during jonal outages.

Global load balancers distribute traffic

across multiple regions providing

resonance against both jonal and

regional outages.

Third traffic type. Load balances handle

specific network traffic types. For web

servers, use HTTP or HTTPS load

balances. For V servers, use UDP load balances.

balances.

Understanding your traffic type is

crucial for selecting the right load

balancer. Finally, termination. Proxy

load balancers terminate client

connections allowing advanced

configurations like single SSL certificates.

certificates.

pass through load balances forward

packets directly preserving client IP information.

information.

By understanding these four attributes,

you can select the right Google Cloud

Platform load balancers for any application.

To troubleshoot load balancers, start

with logging. Logs provide detailed

insights into issues. Remember, logging

is not enabled by default. Enable it

during creation or by editing the load

balancer under backend configuration.

Set a sample rate to control log volume.

Use logs explorer to filter and view

specific log entries like http load

balancer. Next, monitoring. Accessing.

Access the monitoring dashboard from the

load balancer page. Click on the load

balancer. Then the monitoring tab for a

high level overview. For detailed

insights, go to the cloud monitoring

page and select Google Cloud load

balances. These dashboards track errors,

latency, and more, helping you identify

patterns and issues.

Finally, create a custom dashboards. On

the cloud monitoring page, click create

dashboard. Add charts and graphs to

track specific metrics like load

balancer backend utilization. Customize

these dashboards to suit your needs and

set up alerts to notify you when metrics

exceed thresholds. This combination of

logging and monitoring ensures

Ever wondered what a VPN is? Let's break

it down. A VPN, a virtual private

network, creates a secure connection

between private networks using the

public internet. A VPN acts like a

single seamless network allowing

resources in different networks to

connect as if they were in the same

network. It keeps your networks private

and secure through encryption.

Modern VPNs use encryption to securely

exchange data over the public internet.

These means your private networks remain

inaccessible to the general public,

ensuring your data stays safe.

VPNs can make your device appear to be

in a different country by changing your

IP addresses. They also allow remote

employees to securely access corporate

networks and connect multiple data

centers across vast instances.

VPNs are cost effective and easy to set

up but rely on internet connectivity.

Slow or unstable internet can affect VPN

performance. While encryption adds

security, older methods can be

vulnerable. For highly sensitive data,

VPNs might not be secure enough. VPNs

offer a practical solution for secure

private connections. However, for higher

reliability and security, consider

alternatives like cloud interconnect or

CloudVPN is a Google Cloud Platform

service that links an external network

with your virtual private cloud. Many

companies have resources spread across

on premises, Google Cloud and other

public clouds. CloudVPN ensures seamless

communication between these environments.

environments.

ClassicVPN was the original offering. It

uses a single interface and external IP

address. While it supports static

routing, a tunnel failure disrupts activities.

activities.

Classic VPN is mostly depra decapricated

as of March 31, 2022, but it's still

useful for older gateways without border

gateway protocol support.

High availability VPN introduced in 2019

offers multiple interfaces and IPs.

If one tunnel fails, another takes over

and shows 99.99%

uptime. This makes it more reliable than

classic VPN. However, it only supports

dynamic routing, not static.

Google encourages migration to high

availability VPN due to its reliability.

Classic VPN is only recommended if your

external network uses an old gateway

that doesn't support border gateway

protocol. For everyone else, high

availability VPN is the better choice.

CloudVPN supports only the IPAC

protocol, making it incompatible with

SSLR wire guard. It's designed for side

to side connections nor client to

gateway or remote access scenarios.

Despite these limitations, it's

excellent for hybrid and multicloud environments.

Google Cloud DNS is a global domain name

service that simplifies domain

management. It allows you to map address

public IP addresses to public domain

names and create private domain names.

One standout feature is the ability to

use internal DNS names instead of hard

coding IP addresses. These flexibility

is invaluable for managing complex

infrastructure, making testing and

deployment much easier across multiple

environments like development, testing,

staging, and production.

With Google Cloud DNS, you don't need to

maintain your own DNS servers or software.

software.

The service is fully managed and highly

scalable, capable of handling millions

of records. It offers 100% availability

and low latency access from anywhere in

the world. Additionally, you can

generate detailed logs for monitoring

and troubleshooting.

Google Cloud DNS ensures high

scalability and reliability. It can

manage millions of records effortlessly,

providing low latency and 100%

availability globally. This makes it a

roadest choice for any business.

If you already have a Google Cloud

Platform account, using Google Cloud DNS

is no barrier. It streamlines domain

management and enhances your

infrastructure flexibility and reliability.

Before diving into cloud DNS, it's

crucial to understand DNS zones.

A DNS zone is a container for DNS

records sharing the same name suffix.

These zones automatically generate

essential records like NS and S SOA.

Cloud DNS offers two types of jones

public and private. Public jones are

visible to the entire internet while

private jones are restricted to

specified virtual private cloud or VPC networks.

networks.

Sometimes you may need both public and

private jones for the same domain. This

setup known as split horizont

allows different results for the same

domain name based on the source IP address.

address.

To set up split DNS, create both the

public and private jone for the same

domain and add the appropriate records.

This way internet users get the public

IP while internal

resources get the private IP.

Public DNS Jones can enforce DNS

security extension or DNS SSC.

DN SSEC authenticates responses for

domain name lookups, ensuring data

integrity and preventing redirection to

harmful servers. DNS forwarding allows

requests for certain domains to be

resolved by another DNS server. DNS

pairing on the other hand forwards

request between VPCs enabling internal

to internal routting. Understanding

these concepts is key to effectively

managing cloud DNS. Whether it's public,

private or split jones, each has its

To fully utilize cloud DNS,

understanding DNS policies is crucial.

These policies allow you to override

default settings, enabling both simple

and advanced configurations.

On premises DNS resolution. Handling all

DNS resolutions on premises involves

adding a cloud DNS policy specifying an

alternative name server.

These bypasses cloud DNS but increases

latency and risks disruptions if the

on-prim connection fails. Using cloud

DNS for all DNS resolution requires a

policy for inbound query forwarding.

This setup shares name resolution

services across networks but also

suffers from higher latency and

potential disruptions if the GCP

connection fails.

A hybrid DNS environment combines both

on-prim and cloud DNS. Set up a

forwarding zone for on-prim resources

and enable inbound DNS forwarding for

GCP access. These approach balances

flexibility and reliability.

While onprim and cloud only strategies

have drawbacks, a hybrid DNS environment

offers the best of both worlds. It's a

recommended practice by Google for

optimal performance and minimal headache.

Securing cloud resources can be challenging.

challenging.

As your systems grow and become more

complex, the total number of potential

vulnerabilities increases.

Minimizing your attack surface is

crucial to maintaining security.

Physically securing a room with a single

door is much easier than securing an

entire building with many entrances.

Similarly, securing a private network is

easier than a public one. Assigning

public IPs only when absolutely

necessary. Cutting of VMs and Kubernetes

clusters from the internet can limit

updates and patches.

Network address translation or NAT

allows you to assign a single IP address

to a group of computers. These enables

internal network request to reach the

internet while blocking incoming requests.

requests.

Setting up NAT in Google Cloud Platform

is straightforward with Google CloudNet.

It works with both compute engine VMs

and cloud Kubernetes engine. Fully

managed, it requires no maintenance of

NAT gateways and is highly scalable and reliable.

reliable.

Google CloudNat offers flexibility with

manual and auto modes. In auto mode,

CloudNat manages everything for you.

Even if a zone goes down, CloudNat

remains available across the region,

ensuring your VM stays secure and upto-date.

CloudNet allows your private virtual

machines to access the internet without

exposing them to public IP addresses.

Let's walk through setting it up. First,

ensure you have two virtual machines, a

public VM with both internal and

external IP addresses and a private VM

with only an internal IP address. Both

should be in the same virtual private

cloud or VPC but different subnets.

Verify the public VM internet access

using the curl method. It should return

your public IP address and load

websites. For the private VM, the curl

command will time out indicating no

internet access.

Navigate to cloudnat and click get

started. Name your gateway. Select your

VPC network and region and create a new

router. The default settings will map

all subnets to the NAT gateway and

assign NAT IP addresses automatically.

Click create. Once the gateway is

created, test the private VMs internet

access again using curl.

It should now connect successfully

showing the NAD public IP address.

Explore advanced configurations like

setting manual IP addresses, enabling

logging and adjusting connection

settings. These options provide greater

control and customization for your

Google Kubernetes Engine, GKE, is a

fully managed Kubernetes service. No

need to manually install Kubernetes.

It's all set up and ready to go,

simplifying your operations.

GKE handles most system management

tasks, offering advanced features like

automatic node scaling, repairing, and

upgrading. This means you can focus on

your applications while GKE takes care

of the heavy lifting.

Kubernetes is an open-source container

orchestration system ideal for running

many containerized applications. It's

especially useful for complex micro

service architectures requiring hundreds

of thousands of containers.

Kubernetes uses a distributed system

deploying containers onto virtual

machines called nodes grouped into

clusters. This setup ensures high

availability and easy scaling as nodes

can take over if one fails.

A Kubernetes cluster has two main

components. The control plane and worker

nodes. The control plane orchestrates

tasks and manages node health while

worker node run the containerized

application. In summary, JKE simplifies

Kubernetes management allowing you to

create cluster with control plane and a

worker node. This setup ensures

efficient, scalable and reliable

Kubernetes is designed to run

containerized applications. While you

might think of containers, Kubernetes

focuses on parts and workloads. Let's

break down what these terms mean. In

Kubernetes, a pod is the closest thing

to a container. A pod can contain one or

more containers bundled together sharing

storage and network resources.

Most pods have a single container making

pod and a container almost

interchangeable. However, multiple

containers in a pod can work together seamlessly.

seamlessly.

You don't directly create pods in

Kubernetes. Instead, you define

workloads which then create the pods.

The workload represents an application

and sets deployment rules for pods.

These includes how many parts to deploy

these hardware requirements and how they

should run workloads ensures flexibility

and scalability in your application.

Initially you will likely create

workloads with a single pod in a

container but Kubernetes allows you to

run pods on multiple nodes providing

redundancy and scalability.

These abstraction helps Kubernetes

manage complex applications efficiently.

When working with Kubernetes, remember

you are deploying workloads. These

workload consist of pods which contain

containers. This structure offers the

flexibility and scalability needed for

So, let's explore how to create and

manage Google Kubernetes Engine clusters.

First, log into the Google Cloud Console

and navigate to the Kubernetes Engine

page. Click on the create button to

start a new cluster. Choose a standard

cluster for more control over configurations.

configurations.

Name your cluster and configure the

worker node, selecting machine types and

the number of nodes.

Node pools allow you to have different

types of nodes within the same cluster.

You can create multiple node pools to

support various workloads. For example,

one pool can have generalpurpose

machines while another can have compute

optimized machines.

These flexibility helps in managing

diverse workloads efficiently.

Google communities engine supports

autoscaling to handle varying workloads.

Vertical pod autoscaling adjusts CPU and

memory resources for your pods.

Horizontal pod autoscaling changes the

number of pods based on resource consumption.

consumption.

Node autoscaling adjusts the number of

nodes in your cluster, ensuring

efficient resource use and cost management.

To troubleshoot your Google Kubernetes

Engine, start by checking the logs. This

is the first step to identify and fixing

any issues with Kubernetes.

Log into the web console and navigate to

the Kubernetes engine page. Click on the

cluster name and then the logs tab. Here

you can filter by severity and search

for the specific test strings.

For more detailed information, click on

the log logs explorer link. This tool

provides an expanded set of records and

filters, allowing you to drill down into

the details and locate error messages.

Monitoring helps identify issues that

aren't immediately obvious on the

clusters page. Click the operations

button. These pop-up includes logs,

metrics, events, and alerts. For more

details, use the cloud monitoring

dashboard. Set up alerts by clicking on

alerting. Choose the metrics to monitor

and set thresholds for notifications.

For example, get notified if memory

usage spikes or if a pod generates many errors.

errors.

By combining logs, monitoring and

alerts, you can effectively troubleshoot

Developing microservices on Kubernetes

involves more than just building and

deploying containers. Effective

communication between containers is crucial.

crucial.

An unreachable

API is useless and failures can cascade

through dependent services.

Name spaces in Kubernetes help organize

your containers. Think of them like

folders in a file system but not

hierarchical. Every pod in a Kubernetes

cluster is assigned to a namespace with

default being the fallback if none is specified.

specified.

In smaller environments, the default

name space might suffice, but in longer

setups, managing hundreds of thousands

of containers in one name space can be chotic.

chotic.

Name spaces help avoid conflicts and

accidental deletions by dividing the

cluster into virtual clusters for

different teams.

Name spaces do not provide isolation.

Containers in different name spaces can

still communicate.

Kubernetes clusters like those in Google

Cities engine come with predefined name

spaces like default cube-

system cube public and cube node

release. It's best to leave the cube

dash name spaces alone. To demonstrate, create a j cluster and a couple of name

create a j cluster and a couple of name spaces. deploy a simple app to each

spaces. deploy a simple app to each namespace.

namespace. This shows how name spaces prevent

This shows how name spaces prevent naming conflicts and help manage

naming conflicts and help manage resources efficiently.

resources efficiently. You can also manage namespaces via the

You can also manage namespaces via the Google cloud console. Name spaces are

Google cloud console. Name spaces are essential for organizing and managing

essential for organizing and managing microservices on Kubernetes, especially

microservices on Kubernetes, especially in large environments.

you have a containerized web server running in a Kubernetes cluster. Each

running in a Kubernetes cluster. Each pod gets an IP address, but these IPs

pod gets an IP address, but these IPs change as parts are created and

change as parts are created and destroyed. These makes direct traffic

destroyed. These makes direct traffic rooting unreliable.

rooting unreliable. Kubernetes services solve this problem

Kubernetes services solve this problem by defining a set of pods and setting a

by defining a set of pods and setting a policy to access them.

policy to access them. Think of services as internal load

Think of services as internal load balances mapping a single IP address to

balances mapping a single IP address to a group of parts ensuring reliable

a group of parts ensuring reliable connectivity.

connectivity. There are five types of Kubernetes

There are five types of Kubernetes services. Cluster IP, headless, node

services. Cluster IP, headless, node port, load balancer, and external name.

port, load balancer, and external name. Cluster IP is the default. Mapping an

Cluster IP is the default. Mapping an internal IP to ports. Load balancer uses

internal IP to ports. Load balancer uses a cloud providers load balancer for

a cloud providers load balancer for external access.

external access. To create a load balancer service, use a

To create a load balancer service, use a command specifying the service type and

command specifying the service type and name space. This service maps to an

name space. This service maps to an external IP allowing public access.

external IP allowing public access. Verify it works by connecting to the

Verify it works by connecting to the external IP with the curl command.

external IP with the curl command. Creating a cluster IP service is similar

Creating a cluster IP service is similar but for internal access only. It doesn't

but for internal access only. It doesn't get an external IP. To test it, connect

get an external IP. To test it, connect from a pod inside the cluster using a

from a pod inside the cluster using a shell command. These ensures internal

shell command. These ensures internal connectivity is working.

Kubernetes network policies are essential for controlling traffic at the

essential for controlling traffic at the IP address and port level. They help

IP address and port level. They help secure your cluster by simplifying what

secure your cluster by simplifying what types of access are allowed for each

types of access are allowed for each board or name space. Cluster IP and load

board or name space. Cluster IP and load balancer services

balancer services enable internal access within the

enable internal access within the cluster while load balancer services

cluster while load balancer services allow external access. But what if you

allow external access. But what if you need more control over these

need more control over these connections? That's where network

connections? That's where network policies come in. By default, Kubernetes

policies come in. By default, Kubernetes allows all traffic. However, once you

allows all traffic. However, once you create a network policy, any connection

create a network policy, any connection not explicitly allowed will be denied.

not explicitly allowed will be denied. This is crucial for securing a

This is crucial for securing a production environment.

production environment. Network policies are defined using YAML

Network policies are defined using YAML files. You can specify policies for

files. You can specify policies for ingress and egress traffic. These

ingress and egress traffic. These policies are addictive, meaning they act

policies are addictive, meaning they act like a white list, not a block list. For

like a white list, not a block list. For example, you could allow all incoming

example, you could allow all incoming connections but deny all outgoing

connections but deny all outgoing connections or allow connections only

connections or allow connections only for certain IPs.

for certain IPs. These flexibility helps tailor security

These flexibility helps tailor security to your specific needs. Imagine you have

to your specific needs. Imagine you have a web server container. You could set a

a web server container. You could set a policy to allow ingress on ports 80 and

policy to allow ingress on ports 80 and 443 automatically denying all other

443 automatically denying all other parts ports. This ensures only necessary

parts ports. This ensures only necessary traffic reaches your server.

Creating a new cluster in Google communities engine can be overwhelming.

communities engine can be overwhelming. With so many options, it's crucial to

With so many options, it's crucial to understand the difference between JKE

understand the difference between JKE standard and JKE autopilot.

standard and JKE autopilot. JK standard offers maximum control you

JK standard offers maximum control you decide on clusterwide settings, node

decide on clusterwide settings, node pool size, machine types, and operating

pool size, machine types, and operating systems. This hands-on approach requires

systems. This hands-on approach requires you to monitor node health and compute

you to monitor node health and compute capacity making it ideal for those who

capacity making it ideal for those who need detailed customization.

need detailed customization. JKE autopilot simplifies the process by

JKE autopilot simplifies the process by preconfiguring optimized settings. It

preconfiguring optimized settings. It handles maintenance, autoscaling and

handles maintenance, autoscaling and repairs automatically.

repairs automatically. This approach is perfect for those who

This approach is perfect for those who prefer hasslefree setup leveraging

prefer hasslefree setup leveraging Google's best practices without the need

Google's best practices without the need for extensive research.

for extensive research. Autopilot can also save you money. You

Autopilot can also save you money. You pay for board instead of per node. This

pay for board instead of per node. This means you only pay for the resource you

means you only pay for the resource you use, unlike standard clusters where you

use, unlike standard clusters where you pay for provisioned nodes regardless of

pay for provisioned nodes regardless of usage.

To create a cluster, log into the Google Cloud Platform console. Choose either

Cloud Platform console. Choose either standard or autopilot based on your

standard or autopilot based on your needs. Autopilot requires minimal input

needs. Autopilot requires minimal input while standard offers extensive

while standard offers extensive customization options. Both types

customization options. Both types provide tutorials to guide you through

provide tutorials to guide you through the setup process. Autopilot suits most

the setup process. Autopilot suits most use cases with its ease and efficiency.

use cases with its ease and efficiency. Standard is best for advanced needs.

Standard is best for advanced needs. Remember, you can't convert between

Remember, you can't convert between types, so choose wisely. Experiment with

types, so choose wisely. Experiment with both to find what works best for you.

When creating a Google Kubernetes Engine cluster, you can choose between public

cluster, you can choose between public and private. Public clusters assign

and private. Public clusters assign nodes both private and public IP

nodes both private and public IP addresses allowing direct internet

addresses allowing direct internet access. This is useful for microservices

access. This is useful for microservices needing external access but comes with

needing external access but comes with security risks. Private cluster assign

security risks. Private cluster assign nodes only private IP addresses

nodes only private IP addresses isolating them from direct internet

isolating them from direct internet communication. These enhances security

communication. These enhances security but limits connectivity. Nodes can't

but limits connectivity. Nodes can't connect to the internet unless

connect to the internet unless configured with cloud network address

configured with cloud network address translation or cloudnat. This step is

translation or cloudnat. This step is more secure but less flexible.

more secure but less flexible. Both public and private clusters have a

Both public and private clusters have a public endpoint for the control plan

public endpoint for the control plan used for cluster management. Private

used for cluster management. Private clusters also have a private endpoint

clusters also have a private endpoint which can be used if the public endpoint

which can be used if the public endpoint is disabled. enhancing security but

is disabled. enhancing security but limiting management options. You can

limiting management options. You can restrict access to the public endpoint

restrict access to the public endpoint by configuring an authorized network.

by configuring an authorized network. These allows only pre-approved networks

These allows only pre-approved networks to connect, balancing remote

to connect, balancing remote administration with security. Disabling

administration with security. Disabling authorized networks allow management

authorized networks allow management from anywhere but increase risk. In

from anywhere but increase risk. In summary, public clusters offer

summary, public clusters offer accessibility but less security. Private

accessibility but less security. Private clusters provide better security by

clusters provide better security by isolating nodes. You can enhance

isolating nodes. You can enhance security further by disabling the public

security further by disabling the public endpoint or using authorized networks.

endpoint or using authorized networks. Choose based on your specific needs for

Choose based on your specific needs for connectivity and security.

When creating a Google Kubernetes Engine cluster, you need to consider your

cluster, you need to consider your availability requirements. Google offers

availability requirements. Google offers two types of clusters, journal and

two types of clusters, journal and regional. Let's explore the differences.

regional. Let's explore the differences. Jonal clusters have a single control

Jonal clusters have a single control plan in one jone. If that jone goes

plan in one jone. If that jone goes down, your cluster becomes unreachable.

down, your cluster becomes unreachable. Nodes can be spread across multiple

Nodes can be spread across multiple jones, but the control plan remains a

jones, but the control plan remains a single point of failure. Regional

single point of failure. Regional clusters run multiple copies of the

clusters run multiple copies of the control plane across multiple jones.

control plane across multiple jones. These setup ensures high availability as

These setup ensures high availability as the cluster remains operational even if

the cluster remains operational even if one or two jones fails. Regional

one or two jones fails. Regional clusters also avoid downtime during

clusters also avoid downtime during upgrades. Regional clusters are ideal

upgrades. Regional clusters are ideal for production environments due to their

for production environments due to their resilence. Jonal clusters while less

resilence. Jonal clusters while less expensive and faster to configure are

expensive and faster to configure are better suited for non-critical

better suited for non-critical operations like development or testing.

operations like development or testing. To create a regional cluster, select

To create a regional cluster, select autopilot in the GCP console. For a

autopilot in the GCP console. For a journal cluster, choose standard and

journal cluster, choose standard and configure your jones. Remember the

configure your jones. Remember the default for standard is journal but you

default for standard is journal but you can distribute nodes across multiple

can distribute nodes across multiple jones

in Google Kubernetes Engine. Traffic routting between pods can be managed

routting between pods can be managed using allies IPIs or Google cloud roots.

using allies IPIs or Google cloud roots. Let's break down these two methods and

Let's break down these two methods and their benefits.

their benefits. Allies IPs involve assigning multiple IP

Allies IPs involve assigning multiple IP addresses to a network interface.

addresses to a network interface. In GKE, this means allocating a range of

In GKE, this means allocating a range of IPs for nodes, parts, and services. GKE

IPs for nodes, parts, and services. GKE then distributes these IPs as needed,

then distributes these IPs as needed, making it a seamless process. Google

making it a seamless process. Google Cloud roots on the other hand are custom

Cloud roots on the other hand are custom static root roots defined in a virtual

static root roots defined in a virtual private cloud or VPC. This method

private cloud or VPC. This method requires manual management of roots

requires manual management of roots similar to setting up static roots for

similar to setting up static roots for virtual machines. Clusters using allies

virtual machines. Clusters using allies IPs are called VPC native clusters. They

IPs are called VPC native clusters. They allocate three IP ranges for nodes, pods

allocate three IP ranges for nodes, pods and services. This method is best

and services. This method is best practice offering benefits like native

practice offering benefits like native rootability within the VPC and avoiding

rootability within the VPC and avoiding IP conflicts.

IP conflicts. Roots based clusters handle IP

Roots based clusters handle IP allocation differently requiring minimal

allocation differently requiring minimal creation of IP ranges for parts and

creation of IP ranges for parts and services. This method uses the

services. This method uses the Kubernetes control plan to maintain

Kubernetes control plan to maintain static roots to each node. In most

static roots to each node. In most cases, VPC native mode is recommended

cases, VPC native mode is recommended for its simplicity and efficiency.

for its simplicity and efficiency. Choose rootsbased clusters only for

Choose rootsbased clusters only for specific requirements.

Google Cloud Platform is a powerful tool for building almost anything. But

for building almost anything. But sometimes you don't need a custom

sometimes you don't need a custom solution. Google Cloud Marketplace

solution. Google Cloud Marketplace offers a wide array of commercial and

offers a wide array of commercial and open-source software packages to meet

open-source software packages to meet your needs. With Google Cloud

your needs. With Google Cloud Marketplace, deploying applications is

Marketplace, deploying applications is simple. No need to manually provisions

simple. No need to manually provisions resources or configure software. Just

resources or configure software. Just pick a package, review cost and click

pick a package, review cost and click launch. It's that easy to start. Log

launch. It's that easy to start. Log into the Google Cloud Platform console,

into the Google Cloud Platform console, search for marketplace and click the

search for marketplace and click the link. Browse the catalog or search for a

link. Browse the catalog or search for a specific product. You can filter by

specific product. You can filter by categorize categories to find exactly

categorize categories to find exactly what you need. Google Cloud Marketplace

what you need. Google Cloud Marketplace offers various types of software

offers various types of software packages, virtual machines, Kubernetes

packages, virtual machines, Kubernetes apps, software as a service and

apps, software as a service and application programming interfaces and

application programming interfaces and container images. Each type has

container images. Each type has different deployment and cost

different deployment and cost implications.

implications. Let's deploy Drupal using virtual

Let's deploy Drupal using virtual machine. Search for Drupal. Select the

machine. Search for Drupal. Select the correct type. Review details and cost

correct type. Review details and cost and click launch. Customize settings if

and click launch. Customize settings if needed. Accept the terms and condition

needed. Accept the terms and condition terms of services and deploy. Once

terms of services and deploy. Once complete, manage your new VM from the

complete, manage your new VM from the compute engine page.

are fantastic. They are easy to build, deploy, and are highly portable. They

deploy, and are highly portable. They start up faster and are smaller than

start up faster and are smaller than virtual machines, but managing them can

virtual machines, but managing them can be a hassle. Manually scaling and

be a hassle. Manually scaling and maintaining containers is labor

maintaining containers is labor intensive. What happens when a container

intensive. What happens when a container crashes or gets overwhelmed with

crashes or gets overwhelmed with request? Kubernetes can help, but it

request? Kubernetes can help, but it adds complexity with clusters, nodes,

adds complexity with clusters, nodes, boards, and controllers.

boards, and controllers. Enter Google Cloud Run. It allows you to

Enter Google Cloud Run. It allows you to run containers in a serverless

run containers in a serverless environment, eliminating the need for to

environment, eliminating the need for to manage infrastructure. Request based

manage infrastructure. Request based autoscaling handles memory and CPU needs

autoscaling handles memory and CPU needs automatically.

automatically. Start with a single instant. As demand

Start with a single instant. As demand increases, Cloud Run creates additional

increases, Cloud Run creates additional instances. When demand drops, it

instances. When demand drops, it terminates those extra in instances,

terminates those extra in instances, saving you money. If a container

saving you money. If a container crashes, Cloud Run seamlessly replaces

crashes, Cloud Run seamlessly replaces it. Cloud Run supports almost

it. Cloud Run supports almost everything. If you can build a container

everything. If you can build a container image, you can deploy it. The Google

image, you can deploy it. The Google Cloud SDK can even deploy your container

Cloud SDK can even deploy your container from source for languages like Java,

from source for languages like Java, Python, or NodeJS.

Python, or NodeJS. It supports hybrid and multi cloud

It supports hybrid and multi cloud environments including AWS and Azure.

Google Cloud Function simplifies your cloud workflow by allowing you to

cloud workflow by allowing you to trigger small bits of code based on

trigger small bits of code based on events. This makes it easier to connect

events. This makes it easier to connect and orchestrate multiple Google Cloud

and orchestrate multiple Google Cloud services.

services. Imagine a company wants customer to

Imagine a company wants customer to upload document images. Cloud storage

upload document images. Cloud storage stores the images. documents AI passes

stores the images. documents AI passes them and cloud SQL stores the data.

them and cloud SQL stores the data. Cloud functions acts as the glue code to

Cloud functions acts as the glue code to automate these workflows seamlessly.

automate these workflows seamlessly. First, it requires less code spending up

First, it requires less code spending up development and testing. Second, it

development and testing. Second, it offers flexibility enabling complex

offers flexibility enabling complex workflows with multiple entry points in

workflows with multiple entry points in exist. Third, it cost effective and

exist. Third, it cost effective and scalable as you only pay when functions

scalable as you only pay when functions run avoiding expensive always on

run avoiding expensive always on applications.

applications. While cloud run is more powerful and

While cloud run is more powerful and flexible, supporting multiple languages

flexible, supporting multiple languages and better scaling, it requires more

and better scaling, it requires more code and setup. Cloud functions, though

code and setup. Cloud functions, though less flexible, are simpler and optimized

less flexible, are simpler and optimized for connecting cloud services like

for connecting cloud services like building blocks, making them ideal for

building blocks, making them ideal for straightforward, event-driven tasks.

straightforward, event-driven tasks. Google Cloud Functions allows you to

Google Cloud Functions allows you to build powerful event-driven systems with

build powerful event-driven systems with minimal code, making it easier to

minimal code, making it easier to connect to various Google Cloud products

connect to various Google Cloud products and even third party services.

Let's explore the basics of identity and access management in Google cloud.

access management in Google cloud. We will also cover for practices for

We will also cover for practices for applying IM to your Google cloud

applying IM to your Google cloud platform projects. So security in the

platform projects. So security in the cloud means not every employee should

cloud means not every employee should have access. For instance, system

have access. For instance, system administrator can create and delete

administrator can create and delete virtual machines while developers use

virtual machines while developers use existing ones. Each role needs different

existing ones. Each role needs different permissions. Google Cloud Identity and

permissions. Google Cloud Identity and Access Management or IM is a managed

Access Management or IM is a managed service that enforces security for your

service that enforces security for your Google Cloud Platform resources. It

Google Cloud Platform resources. It offers a single dashboard to view

offers a single dashboard to view identities and their access levels

identities and their access levels across various services.

across various services. Google Cloud resources are organized

Google Cloud resources are organized hierarchically. Policies applied at a

hierarchically. Policies applied at a higher level like the organization level

higher level like the organization level propagate down to folders, projects and

propagate down to folders, projects and resources. These allow for flexible

resources. These allow for flexible companywide protections and specific

companywide protections and specific overrides. The core principle of IM is

overrides. The core principle of IM is lease privilege. These means limiting

lease privilege. These means limiting permissions to the minimum necessary for

permissions to the minimum necessary for each user or application. By using cloud

each user or application. By using cloud IM you ensure strong platform security

IM you ensure strong platform security allowing only authorized users to access

allowing only authorized users to access your resources.

Let's explore how to use cloud identity and access management IM effectively.

and access management IM effectively. To access the IM dashboard, navigate to

To access the IM dashboard, navigate to IM and admin from the menu or search for

IM and admin from the menu or search for it. This brings you to the IM page where

it. This brings you to the IM page where you can manage project principles and

you can manage project principles and roles. Principles are accounts with

roles. Principles are accounts with access to your project where roles are

access to your project where roles are groups of permissions assigned to these

groups of permissions assigned to these accounts. For example, the owner role

accounts. For example, the owner role grants full access but not every user

grants full access but not every user should have these. To assign roles,

should have these. To assign roles, click the IM, then add, enter the user's

click the IM, then add, enter the user's email and select roles like basic viewer

email and select roles like basic viewer or readonly access or app engine creator

or readonly access or app engine creator for creating applications. Save to

for creating applications. Save to finalize. For custom roles, go to roles

finalize. For custom roles, go to roles and click create role. Name your role,

and click create role. Name your role, set a launch stage, and add specific

set a launch stage, and add specific permissions. These allows you to tailor

permissions. These allows you to tailor access preciously

access preciously to your needs. Now you know how to

to your needs. Now you know how to navigate the IM dashboard, understand

navigate the IM dashboard, understand principles and roles, assign roles, and

principles and roles, assign roles, and create custom roles. These ensure secure

create custom roles. These ensure secure and efficient management of your cloud

and efficient management of your cloud resources.

Now let's explore what a service account is and how to use them in the Google

is and how to use them in the Google Cloud Platform project. A service

Cloud Platform project. A service account is a similar to your user

account is a similar to your user account but while user accounts are for

account but while user accounts are for people, service accounts are for

people, service accounts are for computers. For example, if software

computers. For example, if software needs to write a file to cloud storage,

needs to write a file to cloud storage, it uses a service account.

it uses a service account. Service accounts are essential for

Service accounts are essential for scenarios where virtual machines or

scenarios where virtual machines or containers need to access other GCP

containers need to access other GCP resources. Any authentication using RSA

resources. Any authentication using RSA key pairs and must have the correct

key pairs and must have the correct permissions to perform tasks like

permissions to perform tasks like calling an API or accessing a database.

calling an API or accessing a database. Though service accounts and user

Though service accounts and user accounts seem almost identical, they

accounts seem almost identical, they differ in key ways. Service accounts do

differ in key ways. Service accounts do not use real email addresses or

not use real email addresses or passwords. Instead, they use RSA key

passwords. Instead, they use RSA key pairs for authentication but are managed

pairs for authentication but are managed similarly to user accounts. By creating

similarly to user accounts. By creating and assigning service accounts, you can

and assigning service accounts, you can prevent unauthorized programs from

prevent unauthorized programs from accessing your GCP resources. This

accessing your GCP resources. This separation ensures that test systems

separation ensures that test systems cannot connect to production systems and

cannot connect to production systems and allows you to control resource access

allows you to control resource access between different teams.

Managing service accounts in Google Cloud Platform or GCP is essential for

Cloud Platform or GCP is essential for controlling permissions. So let's create

controlling permissions. So let's create a service account, assign roles and link

a service account, assign roles and link it to your virtual mission. First

it to your virtual mission. First navigate to the IM and admin page and

navigate to the IM and admin page and select service accounts. Click create

select service accounts. Click create service account. Enter a name and

service account. Enter a name and optionally add a description. These

optionally add a description. These generates a service account ID

generates a service account ID resembling an email address. To assign

resembling an email address. To assign roles, click create and continue. You

roles, click create and continue. You can search for roles or scroll through

can search for roles or scroll through the list. For instance, to allow reading

the list. For instance, to allow reading from cloud storage, select storage

from cloud storage, select storage object viewer. Click done to finish.

object viewer. Click done to finish. Next, create a new virtual machine in

Next, create a new virtual machine in Compute Engine. Name it and change the

Compute Engine. Name it and change the default service accounts to the one you

default service accounts to the one you just created. Confirm the VM creation

just created. Confirm the VM creation and it will inheritions.

and it will inheritions. If you need to change the service

If you need to change the service account later, stop the VM first. Edit

account later, stop the VM first. Edit the VM settings. Select the new service

the VM settings. Select the new service account. Save and restart the VM for

account. Save and restart the VM for changes to take effect. Service accounts

changes to take effect. Service accounts offer flexibility and can be used across

offer flexibility and can be used across projects.

projects. Now you know how to create, assign roles

Now you know how to create, assign roles and manage service accounts in GCP.

In a production environment, numerous users, applications, and resources

users, applications, and resources interact constantly. When something goes

interact constantly. When something goes wrong like a deleted virtual machine are

wrong like a deleted virtual machine are denied access, detailed logs are

denied access, detailed logs are essential to figure out the issue.

essential to figure out the issue. Google Cloud Platform maintains audit

Google Cloud Platform maintains audit logs that record all activity and access

logs that record all activity and access to your resources. These logs answer

to your resources. These logs answer critical questions. Which resource was

critical questions. Which resource was accessed? Who accessed it? What action

accessed? Who accessed it? What action was attempted? When did it occur? These

was attempted? When did it occur? These helps in troubleshooting and maintaining

helps in troubleshooting and maintaining security.

security. Google Cloud's audit logs are divided

Google Cloud's audit logs are divided into four main categories. Admin

into four main categories. Admin activity, data access, system event, and

activity, data access, system event, and policy denied. Each category serves a

policy denied. Each category serves a specific purpose, making it easier to

specific purpose, making it easier to track and manage different types of

track and manage different types of activities within your cloud

activities within your cloud environment.

environment. Admin activity logs record attempts to

Admin activity logs record attempts to create, delete, or modify resources like

create, delete, or modify resources like provisioning a new CloudSQL database.

provisioning a new CloudSQL database. Data access logs capture entries for

Data access logs capture entries for reading or writing data to resources

reading or writing data to resources such as accessing a CloudSQL database.

such as accessing a CloudSQL database. System event logs contain entries for

System event logs contain entries for Google initiated actions that modify

Google initiated actions that modify resource configurations. Policy denial

resource configurations. Policy denial logs record every instance where access

logs record every instance where access to a resource is denied, helping you

to a resource is denied, helping you identify suspicious activities or

identify suspicious activities or potential issues.

Now let's explore how to access audit logs for your Google Cloud Platform

logs for your Google Cloud Platform project using the Google Cloud operation

project using the Google Cloud operation suit.

suit. This suit provides a centralized logging

This suit provides a centralized logging interface for all your GCP resources.

interface for all your GCP resources. To access the logging interface, use the

To access the logging interface, use the navigation menu or search for logging.

navigation menu or search for logging. Here you can view various logs from

Here you can view various logs from different GCP services in one place. You

different GCP services in one place. You can filter logs using drop- down menus.

can filter logs using drop- down menus. Filter by resource, log name, or error

Filter by resource, log name, or error severity.

severity. These filters help you quickly find the

These filters help you quickly find the logs you need. Once you find the logs

logs you need. Once you find the logs you are interested in, click the zoom

you are interested in, click the zoom icon. Scroll through entries and expand

icon. Scroll through entries and expand sections to read detailed information.

sections to read detailed information. By default, logs from the last hour are

By default, logs from the last hour are shown. To change these, click edit time

shown. To change these, click edit time and set your desired time period. For

and set your desired time period. For example, select records from the last 7

example, select records from the last 7 days from the main console. Click the

days from the main console. Click the activity tab for a simplified summary of

activity tab for a simplified summary of activity logs.

activity logs. Filter by country, activity type,

Filter by country, activity type, resource type to see specific entries

resource type to see specific entries like building or configuration changes.

like building or configuration changes. Now you know how to find and read logs

Now you know how to find and read logs using Google Cloud Operation Suit,

using Google Cloud Operation Suit, making trouble shooting and auditing

making trouble shooting and auditing easier.

Google CloudSQL is a powerful relational database service on Google Cloud

database service on Google Cloud Platform. It helps you store and

Platform. It helps you store and organize large amounts of structured

organize large amounts of structured data efficiently, making it perfect for

data efficiently, making it perfect for various applications.

various applications. Google CloudSQL organizes data into

Google CloudSQL organizes data into tables. rows and columns make it ideal

tables. rows and columns make it ideal for storing customers list or product

for storing customers list or product catalogs.

catalogs. It supports MySQL, PostgresSQL and

It supports MySQL, PostgresSQL and Microsoft SQL Server offering industry

Microsoft SQL Server offering industry standard databasees

standard databasees without the hustle of setup. CloudSQL is

without the hustle of setup. CloudSQL is commonly used for applications running

commonly used for applications running on Google Cloud services like compute

on Google Cloud services like compute engine, communities engine and cloud

engine, communities engine and cloud functions. It can also be accessed by

functions. It can also be accessed by external applications whether on

external applications whether on premises or on other cloud providers.

premises or on other cloud providers. While cloudSQL is a drop in replacement

While cloudSQL is a drop in replacement for MySQL or SQL server, Cloud Spanner

for MySQL or SQL server, Cloud Spanner is more powerful and suited for high

is more powerful and suited for high demand scenarios.

demand scenarios. BigQuery on the other hand is designed

BigQuery on the other hand is designed for analytics and big data storing

for analytics and big data storing terabytes of information for data

terabytes of information for data scientists.

scientists. CloudSQL offers automated backups,

CloudSQL offers automated backups, replication and storage management. It

replication and storage management. It ensures data encryption at rest and in

ensures data encryption at rest and in transit, providing a secure, reliable

transit, providing a secure, reliable and highly available database solution

and highly available database solution without the headaches of manual

without the headaches of manual management.

Let's cover creating a server instance, importing an external database, and

importing an external database, and managing users.

managing users. This is about setup, not SQL queries.

This is about setup, not SQL queries. First, log into your Google Cloud

First, log into your Google Cloud Platform account and search for SQL.

Platform account and search for SQL. Click to create a new instance. Choose

Click to create a new instance. Choose your database engine, MySQL, PostgresSQL

your database engine, MySQL, PostgresSQL or Microsoft SQL Server. Each has its

or Microsoft SQL Server. Each has its own benefits and costs. Name your

own benefits and costs. Name your instance and set a password for the root

instance and set a password for the root user. Choose between production and

user. Choose between production and developer configurations. Select your

developer configurations. Select your region and zone for data residency.

region and zone for data residency. Customize machine type, storage, and

Customize machine type, storage, and connection settings. Review everything

connection settings. Review everything and click create instance. Once your

and click create instance. Once your instance is ready, import data by

instance is ready, import data by clicking the import button. You can use

clicking the import button. You can use SQL or CSV files. For example, import

SQL or CSV files. For example, import SQL file to create a database or

SQL file to create a database or populate it with records.

populate it with records. Manage your instance from the overview

Manage your instance from the overview page. Edit settings. Import. export

page. Edit settings. Import. export data, restart, stop, or clone your

data, restart, stop, or clone your instance. Use the connect to these

instance. Use the connect to these instance section to verify your data.

instance section to verify your data. Export data by clicking the export

Export data by clicking the export button and choosing your format. And

button and choosing your format. And that's a quick guide to using Google

that's a quick guide to using Google Cloud SQL.

Bitquery storage charges are incredibly cheap. It costs 2 cents per gigabyte per

cheap. It costs 2 cents per gigabyte per month, the same as cloud storage

month, the same as cloud storage standard. If you don't edit a table for

standard. If you don't edit a table for 90 days, the price drops to 1 cent per

90 days, the price drops to 1 cent per gigabyte per month. Plus, there's no

gigabyte per month. Plus, there's no charge for reading data from BigQuery

charge for reading data from BigQuery storage. The only other charge is for

storage. The only other charge is for queries. The first terabyte per month is

queries. The first terabyte per month is free. After that, it cost $6.25 per

free. After that, it cost $6.25 per terabyte, which is about 2/3 of a cent

terabyte, which is about 2/3 of a cent per gigabyte. Bitquery charges query

per gigabyte. Bitquery charges query fees regardless of where the data is

fees regardless of where the data is stored. The charge is for the

stored. The charge is for the processing, not for reading the data.

processing, not for reading the data. For customers with the steady volume of

For customers with the steady volume of queries, there's capacity based billing.

queries, there's capacity based billing. These option provides more predictable

These option provides more predictable cost, but only applies to query cost,

cost, but only applies to query cost, not storage. Storage charges remain

not storage. Storage charges remain separate.

separate. To see how much data will be processed

To see how much data will be processed by a query, you can check and query

by a query, you can check and query details. For example, a query processing

details. For example, a query processing 163 mgabytes won't cost anything if you

163 mgabytes won't cost anything if you are under the free 1 TBTE limit. Even if

are under the free 1 TBTE limit. Even if you exceed it, the cost is less than a

you exceed it, the cost is less than a tenth of a cent.

Google Cloud Pub/SUB is a scalable message query service

is a scalable message query service designed for communication between

designed for communication between different applications or services. It's

different applications or services. It's not for emails or chats, but for

not for emails or chats, but for tracking numerous changes and sharing

tracking numerous changes and sharing updates across systems. Think of it as a

updates across systems. Think of it as a tool for asynchronous messaging between

tool for asynchronous messaging between applications. Pub/sub doesn't directly

applications. Pub/sub doesn't directly deliver messages from one app to

deliver messages from one app to another. Instead, app A post updates

another. Instead, app A post updates which pub/sub stores. Later, app B can

which pub/sub stores. Later, app B can retrieve these updates. It functions

retrieve these updates. It functions more like a blog or forum where messages

more like a blog or forum where messages are published and anyone interested can

are published and anyone interested can read them later.

read them later. Pub/sub supports various communication

Pub/sub supports various communication models one to many, many to one, many to

models one to many, many to one, many to many and one to one. This flexibility

many and one to one. This flexibility allows it to cater to different

allows it to cater to different messaging needs. For instance, one

messaging needs. For instance, one sender can reach multiple receipts or

sender can reach multiple receipts or multiple senders can communicate with a

multiple senders can communicate with a single receipt. Google Cloud Pub/Sub can

single receipt. Google Cloud Pub/Sub can handle immense data volumes sending over

handle immense data volumes sending over 5 million messages per second equivalent

5 million messages per second equivalent to over 1 TBTE of data. It's a global

to over 1 TBTE of data. It's a global service ensuring messages are delivered

service ensuring messages are delivered with consistent latency regardless of

with consistent latency regardless of location without manual replication.

location without manual replication. These makes it highly scalable and

These makes it highly scalable and reliable for modern applications.

Cloud pub/sub supports the publisher subscriber model. It involves publishing

subscriber model. It involves publishing messages to a topic, subscribing to a

messages to a topic, subscribing to a topic, and receiving messages from a

topic, and receiving messages from a topic. A message is data exchanged

topic. A message is data exchanged between services stored as a text or

between services stored as a text or byte string. Publishers add messages to

byte string. Publishers add messages to topics which acts as a cues for related

topics which acts as a cues for related messages. Topics can have one or

messages. Topics can have one or multiple publishers. Subscribers are

multiple publishers. Subscribers are services that wish to receive messages

services that wish to receive messages from topics. Each subscriber needs a

from topics. Each subscriber needs a separate subscription for each topic.

separate subscription for each topic. Subscriptions ensure that messages are

Subscriptions ensure that messages are delivered to the right subscriber.

delivered to the right subscriber. Subscribers can receive messages by

Subscribers can receive messages by pulling them manually or having them

pulling them manually or having them pushed to an end point. Pull

pushed to an end point. Pull subscriptions allow control over when

subscriptions allow control over when messages are received while push

messages are received while push subscription notify subscribers or as

subscription notify subscribers or as messages arrive. Subscribers must

messages arrive. Subscribers must acknowledge or ACK each message to res

acknowledge or ACK each message to res confirm receipt.

confirm receipt. Acknowledged messages are resent until

Acknowledged messages are resent until acknowledged, ensuring no messages are

acknowledged, ensuring no messages are lost, even if a subscriber crashes.

lost, even if a subscriber crashes. Cloud sub/pub/slub

offers flexibility and resilency in message delivery, making it easier to

message delivery, making it easier to manage changes and ensure reliable

manage changes and ensure reliable communication between services.

Cloud pub/sub offers two services pub/sub

pub/sub and a pub/sub light.

and a pub/sub light. Pub/sub is a more powerful option

Pub/sub is a more powerful option providing high reliability global

providing high reliability global routting and automated capacity scaling.

routting and automated capacity scaling. It supports per message parallelism and

It supports per message parallelism and replicates messages across multiple

replicates messages across multiple jones making it the default choice for

jones making it the default choice for most users.

most users. Pub/sub

Pub/sub light is more affordable alternative

light is more affordable alternative with lower availability and durability.

with lower availability and durability. It requires manual resource management

It requires manual resource management and is limited to a single jone. Despite

and is limited to a single jone. Despite these limitations, it can be

these limitations, it can be significantly cheaper making it suitable

significantly cheaper making it suitable for costsensitive applications.

for costsensitive applications. Pub/sub automatically scales capacity

Pub/sub automatically scales capacity and offers unlimited message storage

and offers unlimited message storage with a 7-day retention limit.

with a 7-day retention limit. In contrast, pub/ sublight requires

In contrast, pub/ sublight requires manual capacity management, offers over

manual capacity management, offers over 10 terabytes per topic, and allows

10 terabytes per topic, and allows unlimited message retention.

unlimited message retention. Pub/sub routts messages globally, while

Pub/sub routts messages globally, while pub/sublight

pub/sublight is restricted to a single jone.

Pub/sub operates on a pay for what you use model ensuring you only pay for the

use model ensuring you only pay for the resources you consume and the light

resources you consume and the light version however follows a pay for what

version however follows a pay for what you provision model which can lead to

you provision model which can lead to higher cost if you overprovision

higher cost if you overprovision capacity. Choose based on your specific

capacity. Choose based on your specific needs and budget.

Cloud pub/sub is perfect for realtime event processing. It can create an

event processing. It can create an enterprisewide data sharing bus tracking

enterprisewide data sharing bus tracking business events, user interactions, and

business events, user interactions, and system failures as they happen. These

system failures as they happen. These allows for immediate responses to

allows for immediate responses to critical events. Pub/ sub excels in

critical events. Pub/ sub excels in parallel processing.

parallel processing. Imagine a website like YouTube. When a

Imagine a website like YouTube. When a user uploads a video, multiple tasks can

user uploads a video, multiple tasks can run simultaneously. One process

run simultaneously. One process re-encodes the video, other scans for

re-encodes the video, other scans for copyright issues and the third generates

closed captions. All these tasks can be autoscaled using microservices.

autoscaled using microservices. Pub/sub is also great for tracking

Pub/sub is also great for tracking database changes. It notifies interested

database changes. It notifies interested services when records are added, edited

services when records are added, edited or deleted. These can synchronize

or deleted. These can synchronize multiple databases creating incremental

multiple databases creating incremental backups or log changes for big data

backups or log changes for big data analysis. Internet of thing devices

analysis. Internet of thing devices generate massive amounts of data.

generate massive amounts of data. Pubs/sub captures, stores and filters

Pubs/sub captures, stores and filters these data preventing services from

these data preventing services from being overwhelmed by unnecessary

being overwhelmed by unnecessary notifications.

notifications. These ensures efficient data management

These ensures efficient data management and processing.

Managing data growth is crucial to avoid runaway costs. Even with Google Cloud's

runaway costs. Even with Google Cloud's vast storage, object life cycle

vast storage, object life cycle management helps control these cost

management helps control these cost effectively.

effectively. You can manage cost by deleting old

You can manage cost by deleting old objects or moving them to cheaper

objects or moving them to cheaper storage classes like nearline or

storage classes like nearline or coldline storage. These can be done

coldline storage. These can be done through the cloud storage console, the

through the cloud storage console, the gcloud storage command or Google API

gcloud storage command or Google API client libraries. First create a life

client libraries. First create a life cycle configuration file with rules. For

cycle configuration file with rules. For example, delete any live object older

example, delete any live object older than 365 days. Test these rules on

than 365 days. Test these rules on non-production data to avoid accidental

non-production data to avoid accidental data loss.

data loss. If versioning is enabled, old objects

If versioning is enabled, old objects become non-current instead of being

become non-current instead of being deleted. Use the command G-Cloud storage

deleted. Use the command G-Cloud storage bucket describe to check if versioning

bucket describe to check if versioning is enabled. Enabling enable it with

is enabled. Enabling enable it with G-Cloud storage buckets update.

G-Cloud storage buckets update. Instead of deleting, you can move

Instead of deleting, you can move objects older than one year to nearline

objects older than one year to nearline storage. Objects in nearline storage

storage. Objects in nearline storage older than 3 years can be moved to

older than 3 years can be moved to coldline storage. Apply these rules

coldline storage. Apply these rules using G-Cloud storage buckets update.

using G-Cloud storage buckets update. Monitor life cycle policies through

Monitor life cycle policies through expiration time metadata and usage logs.

expiration time metadata and usage logs. Set up a logging bucket and enable

Set up a logging bucket and enable logging with G-Cloud storage buckets

logging with G-Cloud storage buckets update. Always test life cycle rules on

update. Always test life cycle rules on non-production data first.

data is the lifeblood of any business. Marketing data reveals trends. Customer

Marketing data reveals trends. Customer data improves offerings and operational

data improves offerings and operational data optimizes processes. But using this

data optimizes processes. But using this data efficiently effectively is often

data efficiently effectively is often challenging. Data can be stored in

challenging. Data can be stored in various formats and locations from SQL

various formats and locations from SQL databases to text files. Consolidating

databases to text files. Consolidating and standardizing this data is crucial

and standardizing this data is crucial but complex. The this is where data

but complex. The this is where data pipelines come in. A data pipeline is an

pipelines come in. A data pipeline is an automated workflow that moves and

automated workflow that moves and reformates data. It copies data from one

reformates data. It copies data from one location, transforms it and writes the

location, transforms it and writes the results to another. Pipelines can

results to another. Pipelines can consolidate multiple sources into a

consolidate multiple sources into a single data lake or warehouse.

single data lake or warehouse. Data pipelines have three main phases.

Data pipelines have three main phases. Reading data from a source, transforming

Reading data from a source, transforming it and writing it to a sync. The

it and writing it to a sync. The transformation phase can involve

transformation phase can involve reformatting, filtering or joining data

reformatting, filtering or joining data sets. Each transformation generates a

sets. Each transformation generates a new immutable data set.

new immutable data set. Data pipelines break down data silos and

Data pipelines break down data silos and handle repetitive task like extraction,

handle repetitive task like extraction, cleaning and formatting. They ensure

cleaning and formatting. They ensure data remains clean, consistent and ready

data remains clean, consistent and ready for analysis, making information more

for analysis, making information more accessible and useful.

Building and managing data pipelines can be challenging. Google Cloud Dataf Flow

be challenging. Google Cloud Dataf Flow simplifies this process by offering a

simplifies this process by offering a managed service for executing and

managed service for executing and maintaining data pipelines on Google

maintaining data pipelines on Google Cloud Platform.

Cloud Platform. Dataf flow is serverless, automatically

Dataf flow is serverless, automatically allocating and scaling resources. It

allocating and scaling resources. It handles workloads for any size, ensuring

handles workloads for any size, ensuring performance remains unaffected even

performance remains unaffected even during sudden spikes in data value.

during sudden spikes in data value. Dataf flow manages jobuling, fall

Dataf flow manages jobuling, fall tolerance and monitoring. It builds in

tolerance and monitoring. It builds in built-in tools help visualize pipeline

built-in tools help visualize pipeline execution, identify errors, and optimize

execution, identify errors, and optimize performance, allowing you to focus on

performance, allowing you to focus on developing pipeline logic. Unlike many

developing pipeline logic. Unlike many services, dataf flow supports both batch

services, dataf flow supports both batch and streaming jobs with the unified

and streaming jobs with the unified programming model, offering flexibility

programming model, offering flexibility and simplifying workflows.

and simplifying workflows. Batch pipelines process large finite

Batch pipelines process large finite data sets at specific times while stream

data sets at specific times while stream streaming pipeline handles real time

streaming pipeline handles real time unlimited data.

unlimited data. Dataflow uses Windows and triggers to

Dataflow uses Windows and triggers to manage and process streaming data

manage and process streaming data efficiently. To build pipelines, use

efficiently. To build pipelines, use Apache Beam, an open-source framework

Apache Beam, an open-source framework supporting multiple languages. Beam acts

supporting multiple languages. Beam acts as a blueprint and data flow executes

as a blueprint and data flow executes the pipeline managing the environment

the pipeline managing the environment and monitoring results.

After setting up your infrastructure on Google Cloud Platform, form. The next

Google Cloud Platform, form. The next step is to establish a monitoring system

step is to establish a monitoring system to alert you to major issues. Use cloud

to alert you to major issues. Use cloud operations, formerly known as stack

operations, formerly known as stack driver for monitoring and logging.

driver for monitoring and logging. Access it by selecting monitoring from

Access it by selecting monitoring from the menu or typing monitoring in the

the menu or typing monitoring in the search bar. You can install an agent on

search bar. You can install an agent on a virtual machine for more detailed

a virtual machine for more detailed information, but it's not necessary to

information, but it's not necessary to start. To monitor a web server, create

start. To monitor a web server, create an uptime check. Leave the protocol as

an uptime check. Leave the protocol as HTTP and resource type as URL. Enter the

HTTP and resource type as URL. Enter the IP address of your web server instance.

IP address of your web server instance. Set the check frequency to 1 minute and

Set the check frequency to 1 minute and response time time out to 10 seconds.

response time time out to 10 seconds. Enable logging for failures. Set up an

Enable logging for failures. Set up an alert for uptime check failures. Name

alert for uptime check failures. Name the alert and specify the failure

the alert and specify the failure duration before triggering an alert.

duration before triggering an alert. Choose how to receive notifications such

Choose how to receive notifications such as email. Add your email address and

as email. Add your email address and name. Then refresh and select your email

name. Then refresh and select your email for notification.

for notification. Title the uptime check and test it. If

Title the uptime check and test it. If the web server is down, you will receive

the web server is down, you will receive an email notification. View uptime data

an email notification. View uptime data and latency graphs to monitor server

and latency graphs to monitor server performance. Create custom dash

performance. Create custom dash dashboards for additional metrics like

dashboards for additional metrics like CPU and memory utilization by installing

CPU and memory utilization by installing the ops agent.

Realtime monitoring is great, but sometimes you need to look back at

sometimes you need to look back at past events. That's where Google Cloud

past events. That's where Google Cloud audit logs come in handy. They track who

audit logs come in handy. They track who did what, where, and when. There are

did what, where, and when. There are four types of audit logs. Admin activity

four types of audit logs. Admin activity logs track actions that modify resources

logs track actions that modify resources like shutting down virtual machines.

like shutting down virtual machines. System events logs monitor Google's

System events logs monitor Google's cloud action such as maintenance data

cloud action such as maintenance data access logs track data request including

access logs track data request including read request on configurations policy

read request on configurations policy denied logs record access denials due to

denied logs record access denials due to security policy violations to find when

security policy violations to find when a virtual machine was shut down. Search

a virtual machine was shut down. Search for logging in the console. Filter by

for logging in the console. Filter by the specific virtual machine instance

the specific virtual machine instance and select the activity log in the cloud

and select the activity log in the cloud audit log section. Search for entries

audit log section. Search for entries containing the word stop to see shutdown

containing the word stop to see shutdown events. For in-depth analysis, export

events. For in-depth analysis, export logs to BigQuery. Create a sync in the

logs to BigQuery. Create a sync in the more actions menu. Name it and choose

more actions menu. Name it and choose BigQuery as the sync service. Create a

BigQuery as the sync service. Create a data set if needed. Once set up,

data set if needed. Once set up, generate log entries and check BigQuery

generate log entries and check BigQuery for the data. Use SQL statements to

for the data. Use SQL statements to search through the logs efficiently.

Let's explore how to get error information from your applications using

information from your applications using Google Cloud's error reporting service.

Google Cloud's error reporting service. We will use Google's Hello World

We will use Google's Hello World application in App Engine to

application in App Engine to demonstrate. First, open CloudShell,

demonstrate. First, open CloudShell, which has all necessary packages

which has all necessary packages pre-installed. Clone the Hello World

pre-installed. Clone the Hello World application using the git clone command

application using the git clone command and navigate to the app directory. Run

and navigate to the app directory. Run the local development server to ensure

the local development server to ensure the app works. Click the web preview

the app works. Click the web preview icon and select preview on port 8080.

icon and select preview on port 8080. You should see a hello world message.

You should see a hello world message. Stop the server and deploy the app to

Stop the server and deploy the app to app engine using the G-Cloud app deploy

app engine using the G-Cloud app deploy command. To generate an error, edit the

command. To generate an error, edit the code to introduce a problem such as

code to introduce a problem such as dividing by zero. Save the file and

dividing by zero. Save the file and redeploy the application with G-Cloud

redeploy the application with G-Cloud app deploy. This will trigger an

app deploy. This will trigger an exception. Check the Google Cloud

exception. Check the Google Cloud console for errors. Click on the error

console for errors. Click on the error to see details including a stack trace.

to see details including a stack trace. To get notification for errors, go to

To get notification for errors, go to the error reporting page and click

the error reporting page and click configure notifications. Select our

configure notifications. Select our create a notification channel. That's it

create a notification channel. That's it for error reporting.

Is your application running but performing too slow? Cloud trace and

performing too slow? Cloud trace and cloud profiler can help. These tools

cloud profiler can help. These tools from Google Cloud provide insights into

from Google Cloud provide insights into latency and resource usage, optimizing

latency and resource usage, optimizing your app's performance. Cloud Trace

your app's performance. Cloud Trace shows the latency of each application

shows the latency of each application request, helping you identify slow

request, helping you identify slow request. The trace list displays all

request. The trace list displays all traces over a specific period visualized

traces over a specific period visualized in an interactive graph. Clicking on a

in an interactive graph. Clicking on a track trace dot reveals a waterfall view

track trace dot reveals a waterfall view showing the total end to end time and

showing the total end to end time and the time taken by each call. These helps

the time taken by each call. These helps pinpoint which cause are slowing down

pinpoint which cause are slowing down your application.

your application. Analysis reports in cloud trace show

Analysis reports in cloud trace show latency distribution and identity

latency distribution and identity performance bottlenecks. You need at

performance bottlenecks. You need at least 1000 traces to generate a report,

least 1000 traces to generate a report, providing a comprehensive view of your

providing a comprehensive view of your app's performance.

app's performance. Cloud profiler analyzes which parts of

Cloud profiler analyzes which parts of your code use the most CPU and memory.

your code use the most CPU and memory. Even if your app runs in app engine, you

Even if your app runs in app engine, you need to add instrumentation code to use

need to add instrumentation code to use cloud profiler. In cloud profiler, a

cloud profiler. In cloud profiler, a flame graph shows CPU time taken by each

flame graph shows CPU time taken by each function. For example, in the shakes app

function. For example, in the shakes app sample, one function took 58% of CPU

sample, one function took 58% of CPU time, highlighting areas for

time, highlighting areas for optimization.

Now, let's dive into the latest real exam questions and answers for the

exam questions and answers for the Google Cloud Certified Associate Cloud

Google Cloud Certified Associate Cloud Engineer. If you haven't subscribed to

Engineer. If you haven't subscribed to our YouTube channel yet, we'd love for

our YouTube channel yet, we'd love for you to join our growing community. Just

you to join our growing community. Just hit that subscribe button. Want a

hit that subscribe button. Want a downloadable PDF of these questions and

downloadable PDF of these questions and answers? You can grab it from our

answers? You can grab it from our website, www.shapingpixel.com.

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YouTube Transcript:Google ACE Crash Course | Practice Q&A | Pass Google Associate Cloud Engineer Exam