[MUSIC PLAYING]
PAUL RAVINDRANATH:
Namaste, [NON-ENGLISH]..
Hello, India.
Paul, here, and welcome
to the fourth episode
of #AskGoogleDevsIndia series.
You can view the
previous episodes
on Kotlin Android 11 and
web by following the links
in the description.
In this video, we bring
answers to your questions
on Google Cloud.
And we have Google Developer
Advocate, Priyanka Vergadia,
and Partner Engineer,
Romin Irani,
to answer your questions.
Before you hear from them,
here are the top updates
on India's developer ecosystem.
India's TensorFlow communities
are organizing TFUG India
Summit, which is a four
day event to bring together
the curious, machine-learning
enthusiasts, developers,
and researchers.
You'll learn from domain
experts and also see
the latest projects
that are built
by TensorFlow practitioners.
To register for
this event, you can
look at the link in
the description below.
We are really
excited to announce
that we have onboarded a total
of 269 brand new Developer
Student Club Leads.
While we're really sad to see
the previous batch of Leads
leave us, we want to
congratulate you, thank you
for your hard work, and wish
you the best for the future.
The new Leads will create
learning opportunities
on Google tech for
students on their campuses
and will also build
solutions for their community
and local businesses.
Learn more about this
program at the link below.
Now, the pandemic
has been relentless,
and it's raised a lot of
questions in developers' minds,
such as identifying
new sources of income
or dealing with the
uncertainty of work.
Working closely with our
Google Developer Experts--
GDES-- we've created
a GDEs' guide
to navigate COVID-19, where
Google Developer Experts share
their tips to help you on
the most pressing issues
caused by the pandemic.
You can check out
these tips that
feature twice a week on our
Twitter handle, @GoogleDevsIN.
Eleven GDE
communities from India
have come together to celebrate
Google Cloud Next OnAir
Extended event.
This will give you a
detailed understanding
of Google Cloud with talks,
demos, partner connects,
and a lot more.
Spread out over
nine weeks, you will
hear from speakers
from all over the world
on cutting edge topics
for all skill levels.
Check out the link in the
description below on how
you can be a part of this.
To ensure that aspiring
developers are learning
the latest in tech,
we've partnered
with multiple
universities across India
to train faculty on our
latest course, Android
Development with Kotlin.
This course will empower and
enable university faculty
to teach Android
development in Kotlin
to their students in an
online setting through hands
on, practical labs.
Now, those were the
top updates for you.
Here are Priyanka and Romin with
their answers to your questions
on Google Cloud.
PRIYANKA VERGADIA: I
am Priyanka Vergadia.
I am a developer
advocate at Google Cloud.
ROMIN IRANI: I'm Romin Irani.
I'm a partner engineer
at Google Cloud.
PRIYANKA VERGADIA: All right, so
let's jump into the questions.
Romin, let's start with one
of the most common questions,
right.
If somebody wants to
learn Google Cloud,
where do they get started?
ROMIN IRANI: Yeah.
So when it comes to
learning Google Cloud,
we have multiple resources.
But I would suggest that--
the way you would
look at it is to see
which particular area
or particular expertise
you come with.
So for example, if you're into
infrastructure, or if you're
into app development, or data
analytics-- so what we have,
if you go to our learn
Google Cloud page,
you will have different tracks
that are set for everyone.
So you can look at what
each of the track offers.
It gives you a list of
suggestions, a list of courses,
that you can complete.
And also keep in mind that we
have very generous, free tiers,
so you can actually get started
and experience these services.
And what you would find
in our learning track
are multiple resources.
They will point you
out to Qwiklabs,
which is our online
learning environment where
you can get firsthand experience
of different services.
We've also got
multiple resources,
if you're coming from
another cloud provider,
as to what the mappings are from
one cloud provider to Google
Cloud.
Plus, the DevRel team
has created a great set
of resources, including sketch
notes, which you have made,
which are very useful
to get started.
So just as a first step, come
to the learn Google Cloud page,
pick a particular track or
area that you're familiar with,
look at the various
suggestions that
could range from articles,
YouTube video lists, Qwiklabs,
and also our Google courses.
PRIYANKA VERGADIA: Yep.
Awesome.
So find what you're interested
in, what your expertise is in,
and then start from there is
always the best way to do it.
Great.
So next question
we have is, what
is the recommended way to
study for the associate Cloud
engineering exam?
And how do you prepare
for these exams?
So I think we can
bundle up maybe more
questions in their own
certification in general,
and then maybe we can answer
specifically about associate.
But that has also been
a very common question.
ROMIN IRANI: Yeah.
So I guess a Google
Cloud certification,
I've seen a surge in popularity.
But now, if we come to
the specific question
around different exams or
different certifications,
which are out there.
So whether it's the associate
Cloud engineer or the data
engineer, Cloud architect, and
many others that we have now.
So the first stop
I would suggest
is to go to our
certification page
because that lists out the
different certifications you
are interested in.
And if I just step
back a bit and look
at the different certifications,
the associate Cloud engineer
exam is for folks who are
responsible for deploying
and running Google Cloud
projects in production.
And then we've got
another one called
the professional architect
exam, that sort of goes
across the set of
services, gives you
a much more broader
perspective in terms
of the pros and cons,
which services to use,
when, et cetera.
Then you've got a bunch of
very specialized, I would say,
offerings in the
certification space.
If you are in the data analytics
space, or, we've even got
certifications for
networking, security.
Recently we've even opened up
and [INAUDIBLE] the machine
learning certification.
So what I suggest is,
pick a certification
that you would like to go for,
go to our certification page
and navigate into that
particular certification.
There, what you would
find is, not just
the topics that are going to
be there for the certification,
but there's also
a mock exam which
you can take, maybe to
see how many questions you
could answer.
It just gives you a feel for the
kind of exam that's out there.
Then, of course, we've
got a list of resources
we have listed down.
For example, you could do
a Google Coursera course,
a Qwiklabs quest to
get familiar with it.
And there are multiple
resources on the web, also.
So to summarize, go to
our certification page,
pick a certification
you are interested in.
I would say focus on the topics
that are going to be there,
in that certification,
because that's
what you would be tested for.
Take a look at our mock exams.
Complete a few resources--
or Google courses,
which have been
mentioned over there.
That would be a good
start, over there.
And nothing beats
focused preparation.
So give it some time.
These exams do test you out
well in real life situations.
So be well prepared,
and good luck of course.
PRIYANKA VERGADIA: Yeah.
I found the mock exams to
be really, really helpful.
So do make sure that you
look at the mock exams
to understand how prepared
you are, and then go back
and maybe reassess
the situation.
Somewhere in the middle, don't
try to just take the mock exam
right away.
Maybe try and take it after a
certain level of preparation
to assess where you are.
That's how I would use the
mock exams because there
are only a few
questions, and you
want to make sure that
you see them that way.
ROMIN IRANI: So
Priyanka, there's
a question for you
on machine learning.
How does one get started using
machine learning services
in GCP?
Maybe, a case
study walk-through.
But just, how does
one get started,
and how does one get problem
solving with the [? MLM ?]
specifically in Google Cloud?
PRIYANKA VERGADIA: So
it's a very good question
because there are
lots of us who will
want to just dabble
into machine learning
and have no experience with it.
And then there are some
who have the experience
and want to want to create
something that they already
have a problem in
mind for, right.
So given where
you are, there are
lots of tools
within Google Cloud
to understand how to get
started with machine learning.
I've done a Twitter series
called #13DaysofGCP where I've
broken down two days where--
were specifically
about machine learning.
And I'll give an example.
We'll include the link for
that in the description below.
But I'll use that
as an example, here.
I've taken one example on, I
think, day 11, where I said,
if you are very
new to it, right,
just imagine a
use case where you
have a website, or some
site, or a mobile app, that's
collecting user information, in
a way that it's either images,
or text of certain
comments, and you
want to apply machine
learning to it.
The best way to get started is
to use our ML API [? stage. ?]
So you take the data of
whatever the user is giving you,
for example, it's an image.
You got it into
Google Cloud storage,
and from there you
just triggered a call
through Cloud Functions to
the machine learning API.
And then the machine learning
API would respond back.
In this case, the vision
API would respond back
with whatever it is
that's in the image.
For example, you're looking for
whether it's a dog or a cat,
right.
And that responded back
with whatever was in there,
and then you take more
action based on that.
So that's the easiest example.
If you haven't done anything
in machine learning,
I would maybe start from there.
But if you are more advanced,
and you have a specific use
case, like you're looking
for specific types of logos,
and it's a very specific use
case to you that might require
more examples and more
samples to be applied,
then I would say
use auto ML, where
you can provide your own
examples and train a model
and have your custom API
deployed on Google Cloud
and use that in your app.
Further down, if you want
to create your own machine
learning models with your own
data, just right from scratch,
you could do that
in the AI platform.
So there are lots
of different tools
as to where you are in your
journey from machine learning.
And also it depends
on the use case.
If the use case does not require
you to build a machine learning
model, you should not.
And you should just use
what is available to you
with the already
available ML APIs.
So we'll include the links
for some of these things
in the description below.
I think we can have an entire
session just on machine
learning so I'm not going
to take much time on this
and just include some links that
you can go to to learn more.
ROMIN IRANI: So
that's interesting,
Priyanka, because it allows even
those who are just starting off
with machine learning, and to
the other side of the spectrum,
if you're already familiar
with some of the other tools
and frameworks,
you could utilize
which or wherever you are.
Yeah.
PRIYANKA VERGADIA: Exactly.
So the next question, Romin,
is, does Google Cloud platform
have anything to offer for
maintaining and processing
geospatial data workloads?
I think this is an
interesting one, because--
they also ask if
BigQuery-- they've
heard that BigQueryGIS offers
this, but have never used it.
What would you suggest to
people in the GIS domain?
So I guess they're just
interested in learning
more about what
are their options
when it comes to
geospatial data?
ROMIN IRANI: All right, so
this is an interesting question
because spatial
location data is there
across various applications
that we've come across.
So if you want to track
any sort of objects that
are moving around, or even if
you want to combine, let's say,
some purchases that have
happened in your stores,
and where the stores are.
So spatial data is
there in applications
that we know about.
Now specifically, if you look
at BigQuery and the support
for GIS, it's an
excellent platform
by which you can get started.
But first, if you
look at BigQuery,
primarily that's
enterprise data warehouse.
And there, you could look at,
I would say, data pipeline.
So you've got to first
ingest data, then
once it's transformed and
stored, and ready for analysis,
you could do your
analysis right there.
And then, obviously,
the last step
would be to visualize
that data and try
with the downstream
applications.
And all of this happens at
scale and it's serverless.
So you have the entire
power of BigQuery that's
available at your disposal.
And what BigQueryGIS has done
is something interesting,
in a sense that it lets
you work with spatial data
and makes it available
for analysis.
And it does a few other things
extra that makes this easier.
So A, it supports
various data sets,
or data structures that
you're familiar with in GIS.
It could be a point, could be a
line point, could be a polygon,
could be a region.
So all of these data structures
are available in BigQueryGIS.
They also give you various
geography functions
that make it easier for you
to work with spatial data.
It could be distance, could be
whether a point is in a region,
or not.
So if you look at
it, it gives you
analysis function, the
geography functions,
right within BigQuery analysis.
And finally, it lets you
visualize all of that.
So we've got a [? GeoVIS ?]
BigQuery application where you
could take the results of your
BigQuery analysis and actually
visualize it, [? where ?]
maps, regions.
Drill down, and more
importantly, share this.
So in summary, I would say,
take a look at BigQueryGIS.
It enables the entire
pipeline, right from injection,
to storage, to analysis.
It gives you lots of
utility geography functions
that make it easy to work
with GIS data, and, of course,
lets you visualize too.
So check out the link
below that gives you
a quick start to how you
can familiarize yourself
with BigQueryGIS.
PRIYANKA VERGADIA: Awesome.
That's great.
I am not very
familiar with GIS so I
am so glad that you were
able to answer that one.
How can a candidate join
Google as a Cloud engineer?
Oh, I love this one.
What things are looked
for in a candidate
while they're recruiting for
a position of Google Cloud
engineer?
ROMIN IRANI: So, yeah.
If you look at joining Google
Cloud as a Cloud engineer,
of course, a few things that
I would probably add over here
are that, focus on the area
that you are familiar with,
that's where your strengths are.
And most importantly,
I think you
will need to be able to tell
us what you've been doing
with the technology, what sort
of contributions you've made,
maybe even any open
source contributions.
So we look at, I would say,
an all-around perspective
over here that looks at
your technical skills,
problem-solving skills, how
do you approach a problem?
So some of those
things, I would say,
are very important for
you to even focus on.
And additionally, always being
able to articulate technology,
talk about it, are some of the
things that I could talk about.
Yeah.
PRIYANKA VERGADIA: Cool.
OK.
So I started at Google
as a customer engineer,
so that is why the question
is very interesting to me.
I just want to touch
on the fact that I
have a blog that I've written--
I think about a year or
two ago-- where I said,
what's it like to be a
customer engineer at Google?
And I think the question
alludes to a lot of what
it would be like,
because that could help
you prepare for what
the interview also
looks for in a candidate.
So we'll just include the
link to the blog, as well.
So if you are interested
in learning more about what
do you do on the job, that
could help you prepare yourself
for what you should
study or prepare for
in order to appear
for the interviews.
But all the things that
Romin has mentioned
are all the things
that you need to do.
But the blog can
give you an idea
of what the job is like,
which is actually fun.
ROMIN IRANI: OK.
So the next question
for you, Priyanka,
is an interesting one.
Because everyone wants to get
started with Google Cloud,
but they may already be
having some applications
that there's running elsewhere.
Or they want to migrate from
one cloud provider to another,
maybe they've got lots of
data, also, to migrate.
So how does one go about
taking those first steps?
And I guess you've been making
some interesting videos,
so there's also
a request, maybe,
for you to create a few
nice migration videos
so people could get started.
So any thoughts on that?
PRIYANKA VERGADIA: Awesome.
Yeah, no.
We've received
this request a lot.
So based on that request, we've
created a migration series.
We'll include the link
in the description below.
If you want to go to it,
bit.ly/migration-series is
where it is.
We have a few videos
there, and then we
have linked to a solutions
guide from the videos,
as well, where you can learn how
to get started with migration.
I'm also working
on a sketch note,
so stay tuned for a migration
sketch note, as well.
ROMIN IRANI: So Priyanka,
the next question
is, how Google Cloud
can help startups?
PRIYANKA VERGADIA:
That's a great question.
We do have a startup
program that we
can link in the
description below,
where you can find out
more about the offers,
and discounts, and
things like that,
and how you can get started.
So not a lot that
we can add here,
but there's a lot more
information on the link
that we will put, so
go check the link out.
ROMIN IRANI: The
next question is
that, I would like to make
an app for COVID-19, which
I want to connect to Cloud,
so how do I store my data out
there?
So the question
would specifically
be around, what sort
of different ways,
or different storage options,
are available on Google Cloud?
ROMIN IRANI: Yeah.
This is an interesting question.
Well, there are a lot
of storage options,
and depending on what
type of app it is.
Say, it's a mobile
app, you probably want
to use something like
Firestore because it's easier
to connect to a mobile app
and has direct integrations.
But if there is a relational
database that you need,
you can use Cloud SQL for that.
If this is going to be a super
global, high-performing app
that requires lots
of reads and writes,
then you probably want
to look at Spanner.
But if this is
just starting out,
maybe you're better off
starting out with Firestore
for a non-relational database.
And then if you
need a relational,
I would say cloud SQL.
There are a lot more options.
For images, for example,
you would use Cloud Storage.
For more static data, use that.
But in keeping
the answers short,
and maybe include the
link in the description,
so you can see where you are.
We'll include a flowchart
so you can decide what type
of database you should select.
ROMIN IRANI: Yep.
It's cool to see so
many options, depending
upon your use case.
Yeah.
PRIYANKA VERGADIA: Yeah.
And so, the next question
is, how useful can GCP
be for Flutter developers?
I've had this question
a lot, so Romin,
I'm very curious to see what
you usually respond to this one.
ROMIN IRANI: Yeah.
So if you look at
Flutter development,
or maybe even if I
need to expand it out
to general mobile
development, I think
one of the ways that Google
Cloud can help out here
is that, for the
mobile applications,
you could be using Google
Cloud as a backend.
It could be your API, it
could be your storage.
It could even be for hosting
the web application itself.
So the way I would look
at it is that Google Cloud
provides various options for you
to host your backend services,
or APIs.
You could either do it yourself,
post them on Compute Engine,
you've got support
for Kubernetes, too.
As well as even
serverless options
like App Engine, or Cloud
Functions, Cloud Run.
So there could be
great platforms
by which you could post your
backend for mobile applications
that you create.
At the same time, no
discussion would be complete
if we don't mention Firebase.
So Firebase could be an option.
A suite of services
that gives you,
not just the real-time database,
but even additional services
around it, maybe a remote
configuration, A/B testing.
Plus, if you look
at Firebase hosting,
that gives you a great way
by which you could host
production websites itself.
So multiple options
given to you,
but GCP would be a
great backend to power
your mobile applications.
PRIYANKA VERGADIA:
Well, awesome.
Thank you so much for sending
us all your questions.
We definitely enjoyed
answering them.
ROMIN IRANI: Yes, thank you
so much for the questions.
PAUL RAVINDRANATH: Thank
you, Priyanka and Romin,
for answering the
questions on Google Cloud.
I hope you all
found that useful.
If you'd like to know about
the latest shows and updates
from Google Devs India,
hit the subscribe button.
And you can also follow us
on Twitter @GoogleDevsIN.
That's all for now, folks.
Stay safe.
