The only Cloud services you actually need to know

Summary

This script offers an insightful overview of cloud services, emphasizing the ubiquity of virtual machines as the foundational layer for all cloud offerings. It distinguishes between managed and unmanaged services, elucidating the convenience of services like AWS's S3 and RDS, which abstract infrastructure management. The talk also touches on the concepts of serverless computing with AWS Lambda and the importance of observability in cloud applications. Additionally, it discusses the trade-offs between regional and global services, highlighting the scalability and latency benefits of global databases.

Takeaways

• 🤖 The script discusses the redundancy in cloud services, emphasizing that most services are built on the same underlying technology, such as virtual machines (VMs).
• 🛠 It highlights the importance of understanding the top five cloud services and recognizing that many other services are just repackagings of these core offerings.
• 📚 The speaker introduces the concept of managed versus unmanaged services, explaining that managed services abstract away the infrastructure management, while unmanaged services require more hands-on control.
• 🌐 The difference between regional and global services is explored, with regional services being confined to a specific location and global services distributed worldwide.
• 💾 The script explains that object stores like Amazon S3 are managed services that simplify file storage without worrying about the underlying infrastructure.
• 🔍 It also covers the complexity of databases and how cloud providers offer managed database services like Amazon RDS and DynamoDB to alleviate the burden of database management.
• 🔑 The concept of vendor lock-in is introduced, where using proprietary services like DynamoDB can make it difficult to migrate to other platforms.
• 🛠️ The script touches on AWS Lambda, a serverless compute service that abstracts away the infrastructure, allowing developers to focus solely on their code.
• 🌐 Networking services like load balancers and CDNs are mentioned as important but not the focus of the script; their role in cloud architecture is acknowledged.
• 📈 Observability is discussed as crucial for monitoring and logging application performance, with external tools like Datadog offering enhanced capabilities over native cloud provider tools.
• 📊 Data warehouses and specialized platforms like Snowflake are presented as alternatives to cloud provider offerings, suggesting that focused platforms may provide superior solutions.

Q & A

Why do many people prefer using cloud services instead of hosting their own databases?

People prefer cloud services because they offer managed solutions that abstract away the complexities of hosting databases, such as replication, scaling, and backups, allowing users to focus on their applications rather than infrastructure management.

What is a Virtual Machine (VM) in the context of cloud services?

A Virtual Machine (VM) is a service that allows users to rent a computer in the cloud, complete with allocated resources like CPU, RAM, and disk space, which can be remotely accessed and managed, often via SSH.

What is the main difference between managed and unmanaged services in cloud computing?

Managed services are those where the cloud provider handles the infrastructure, scaling, and maintenance, abstracting away the underlying complexity from the user. Unmanaged services, on the other hand, only provide the basic resources, leaving the user to manage and configure the environment as needed.

Can you explain the concept of 'serverless' in cloud computing?

Serverless refers to the abstraction of server management, where the cloud provider dynamically manages the allocation of machine resources. The user submits their code to the cloud, which then runs it in an environment without the user having to manage servers or runtime environments.

What is Amazon S3 and how does it differ from storing files on a VM?

Amazon S3, or Simple Storage Service, is an object store that allows users to store and retrieve any amount of data from anywhere on the web. It differs from storing files on a VM in that it abstracts away the complexities of file management, such as scaling storage and handling file replication, providing a simple interface for file operations.

What is the significance of understanding the difference between regional and global cloud services?

Understanding the difference is crucial for optimizing latency, cost, and data residency requirements. Regional services are hosted in specific locations, which can affect performance for users outside that region. Global services, on the other hand, distribute data and processing across multiple regions, reducing latency and improving performance for a worldwide user base.

What are some examples of managed database services offered by cloud providers?

Examples of managed database services include Amazon RDS for relational databases and Amazon DynamoDB for NoSQL databases. Other providers like Google Cloud and Microsoft Azure offer similar services such as Google Cloud SQL, Firestore, and Azure Cosmos DB.

What is AWS Lambda and how does it fit into the serverless computing paradigm?

AWS Lambda is a Functions-as-a-Service (FaaS) offering that allows users to run code without provisioning or managing servers. It is a highly serverless service as it abstracts away almost all infrastructure management, executing code in response to events and automatically scaling the compute resources.

What is meant by 'vendor lock-in' in the context of cloud services?

Vendor lock-in refers to the situation where an application is built using proprietary services or tools offered by a specific cloud provider, making it difficult to migrate to another provider without significant changes or data migration due to the lack of equivalent services.

How do observability services like Datadog differ from those provided by major cloud providers?

Observability services like Datadog specialize in providing comprehensive monitoring, logging, and alerting solutions that are often considered easier to use and more feature-rich than those offered by cloud providers. However, they may require additional setup and integration work compared to the native tools provided by cloud services.

What is the role of a Content Delivery Network (CDN) in cloud architecture?

A CDN is a globally distributed network of proxy servers and data centers that deliver content to users based on their geographic location, ensuring faster delivery of web content and reducing latency. It is inherently a global service due to its nature of distributing content worldwide.

Outlines

00:00

🌐 Understanding Cloud Services and Virtual Machines

The speaker begins by addressing the common sentiment that hosting one's own database is undesirable and that AWS, while not necessarily innovative, offers a plethora of cloud services that can be overwhelming to understand. The focus is on explaining the underlying similarities among cloud services and highlighting the top five services to understand deeply. The concept of managed versus unmanaged services is introduced, with virtual machines (VMs) being the foundation of most cloud services. VMs provide a sense of renting a computer with allocated resources, and they form the basis for other services. The speaker emphasizes the extensibility of VMs and their role as an unmanaged service, where the cloud provider only allocates resources and the user has full control.

05:02

📚 Managed Services: Storage and Databases

The speaker discusses the benefits of managed services, starting with file storage solutions like AWS's S3, which abstracts the complexities of file management and provides scalability and simplicity. S3 is an example of a managed service where AWS handles the infrastructure, allowing developers to focus solely on their application logic. The speaker also touches on the challenges of managing databases, which are complex and often best handled by managed database services like AWS's RDS for relational databases or DynamoDB for non-relational databases. The use of open-source software by cloud providers to create managed services is highlighted, as well as the proprietary nature of some services like DynamoDB, which can lead to vendor lock-in.

10:02

🛠 The Spectrum of Cloud Services: From VMs to Serverless

The speaker explores the spectrum of cloud services, from fully managed services like AWS Lambda, which is a serverless compute service, to less managed services like VMs. AWS Lambda represents a high level of abstraction where the developer only needs to focus on the code, with the cloud provider handling the execution environment and scaling. The speaker also discusses the trade-offs of serverless architectures, such as the lack of persistent state and the limitations on disk access. The importance of understanding the spectrum of services is emphasized, as it allows developers to choose the right tool for their specific needs.

15:03

🌐 Networking, Observability, and Specialized Services

The speaker briefly mentions networking services like load balancers and CDNs, which are essential for managing traffic and delivering content globally. The focus then shifts to observability, which involves logging, monitoring, and alerting to ensure applications run smoothly. External tools like Datadog are highlighted for their ability to simplify observability tasks. The discussion also includes data warehouses and specialized platforms like Snowflake and Databricks that excel in specific areas, offering potentially better solutions than general cloud provider services. The speaker emphasizes the importance of trying out these services to gain hands-on experience.

🌍 Regional vs. Global Services and the Power of Global Databases

The speaker concludes by differentiating between regional and global services, using a CDN as an example of a global service and VMs as inherently regional. The benefits of global databases, which manage data distribution and replication to reduce latency and handle scale, are underscored. The speaker notes that while global services and managed services tend to be more expensive, they solve complex problems and can be worth the cost. The importance of practical experience with these services is reiterated, encouraging users to build applications using them.

Keywords

💡Cloud Services

Cloud services refer to the various offerings provided by cloud computing companies, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. These services enable businesses and individuals to use resources over the internet instead of maintaining their own infrastructure. In the video, the speaker discusses the overwhelming number of cloud services and how most of them are essentially the same under the hood, built on top of foundational services like virtual machines (VMs).

💡Virtual Machine (VM)

A virtual machine is a software emulation of a computer system. It allows users to run multiple operating systems on a single physical computer. The video emphasizes VMs as the foundational service for cloud computing, where resources like CPU, RAM, and disk space are allocated to a VM, simulating a physical computer that can be used for various computing tasks.

💡Managed Services

Managed services are cloud services that are fully managed by the cloud provider. This means the provider handles maintenance, updates, and other operational aspects of the service, freeing the user from these responsibilities. The script mentions AWS S3 as an example of a managed service, where AWS abstracts the complexities of file storage, allowing users to focus solely on their application logic.

💡Unmanaged Services

Unmanaged services are cloud offerings that require the user to manage and maintain the service themselves. The video uses the example of VMs, where the cloud provider only provisions the resources, and the user is responsible for everything else, including software installation and configuration.

💡Serverless

Serverless computing is a cloud-computing execution model where the cloud provider dynamically manages the allocation of machine resources. Pricing is based on the actual amount of resources consumed by an application, rather than on pre-purchased units of capacity. The video explains that serverless is a spectrum, with services like AWS Lambda being at the fully managed end, abstracting away almost all infrastructure concerns.

💡Database Services

Database services are cloud offerings that provide managed database solutions. These can be relational databases like MySQL or non-relational databases like DynamoDB. The video discusses how cloud providers offer managed database services to simplify the complexities of database management, such as replication and scaling.

💡Vendor Lock-in

Vendor lock-in occurs when a user is dependent on a specific vendor for a product or service, making it difficult to switch to another provider without significant effort or cost. The script uses DynamoDB as an example of a proprietary service that could lead to vendor lock-in, as it is only available on AWS, making it challenging to migrate to another cloud provider.

💡AWS Lambda

AWS Lambda is a serverless computing service provided by Amazon Web Services. It is a functions-as-a-service (FaaS) platform that runs code in response to events and automatically manages the computing resources required by that code. The video explains Lambda as a service that abstracts away the infrastructure, allowing developers to focus solely on their code.

💡Observability

Observability in cloud computing refers to the ability to understand the internal state of a system by analyzing its outputs, such as logs, metrics, and alerts. The video mentions observability as an important aspect of cloud services, where tools provided by cloud providers or third-party services like Datadog help monitor and alert users about the health and performance of their applications.

💡Data Warehouse

A data warehouse is a system used for reporting and data analysis, and is considered a core component of business intelligence. The video discusses how cloud providers offer data warehouse services like Amazon Redshift and Google BigQuery, and how specialized platforms like Snowflake focus solely on solving data warehousing challenges, potentially outperforming the broader offerings of cloud providers.

💡Regional and Global Services

Regional services are those hosted in a specific geographic location, serving traffic primarily from that region, while global services are distributed across multiple regions, providing a consistent experience worldwide. The video explains the difference by using examples like VMs, which are inherently regional, and CDNs, which are inherently global, and discusses the implications for latency and data replication.

Highlights

The speaker emphasizes the ubiquity of cloud services and the difficulty in keeping up with the vast array of offerings, particularly from AWS.

An explanation is provided on why most cloud services are fundamentally similar, suggesting that understanding a few core services can generalize to others.

The importance of understanding the concept of managed versus unmanaged services and what 'serverless' truly means in the context of cloud computing.

A detailed exploration of the differences between regional and global services in cloud computing, and their implications for latency and data storage.

An introduction to the concept of a Virtual Machine (VM) as a fundamental building block for cloud services.

The extensibility of VMs and how they serve as the base for almost every cloud service, including compute and storage.

A discussion on the unmanaged nature of VMs, where the cloud provider only provisions resources and the user has full control.

The introduction of Amazon S3 as an example of a managed service for file storage, abstracting away the complexities of file management.

The benefits of using managed services like S3, including scalability, ease of use, and automatic data replication.

An explanation of the complexities involved in self-hosting databases versus using cloud-managed database services like AWS RDS.

The role of open-source software in cloud services, with AWS RDS being an example of a managed service built on open-source databases.

The concept of vendor lock-in when using proprietary cloud services like AWS DynamoDB, and the implications for scalability and cost.

An introduction to AWS Lambda as a serverless computing service, abstracting away infrastructure management from the developer.

The trade-offs of using serverless services like Lambda, including the lack of persistent state and the limitations on disk access.

A brief overview of networking services in cloud computing, such as load balancers and CDNs, and their importance for application performance.

The importance of observability in cloud services, including logging, monitoring, and alerts for maintaining application health.

The role of third-party services like Datadog in providing enhanced observability compared to native cloud provider tools.

A discussion on data warehouses and the offerings from cloud providers like AWS Redshift and Google BigQuery, and the emergence of specialized platforms like Snowflake.

The emergence of companies like Versel that aim to simplify the use of AWS resources by providing a more user-friendly interface.

The speaker's recommendation for hands-on experience with cloud services, emphasizing the importance of practical application over theoretical knowledge.

Transcripts

nobody wants to host their own database

AWS isn't doing anything creative

they're actually just taking open-

Source soft logic wise we can do pretty

much everything with these Services

nowadays there's so many different cloud

services that even just knowing the

names of all the services that AWS

offers is difficult let alone

understanding what they actually do well

the good thing is that I'm going to

explain to you why most of the cloud

services are all really the same under

the hood and I'm also going to be giving

you roughly my top five services that

you should actually understand and know

and everything else is just a

repackaging of those top five we're

going to go even deeper than that and

learn about the differences between

managed and unmanaged services because I

think that's kind of a buzzword nowadays

it kind of gets into the whole meaning

of what does serverless actually mean

we'll also touch on the difference

between a regional and a global Service

and we'll also be talking about all

kinds of different cloud services and

providers from the big boys like AWS gcp

as well as the startups versel kind of

the midsize companies like snowflake

data dog and kind of talk about how they

fit into the overall picture now the

single most important service to know

and to know really well is something

that you're probably already familiar

with you can in a sense rent a computer

as a service it's called a VM a virtual

machine now technically you might not be

renting a physical computer but you can

think of it as that cuz you'll have

resources allocated to your VM for

example some CPU some amount of ram disk

space which you can usually add on to so

from your perspective you're getting a

computer well it turns out that pretty

much every single service is built on

top of this any cloud service you're

going to use is in a sense built on top

of VMS if you want to run some type of

compute or server it's going to be

running on top of some type of machine

using some CPU and other resources if

you want to store a bunch of files it's

going to be stored on top of a computer

because even though the files are going

to be stored probably on disk well to

read and write to those files you're

going to need some type of computer to

run a database I probably don't have to

tell you it's going to require all of

these everything is just built on top of

computers and pretty much every cloud

provider will offer some like this

Amazon has ec2 Google has compute engine

I'm sure Azure has their own the good

thing about these is that they're so

extensible if you really wanted to you

don't need any of those other services

you can do everything you need to using

just VMS and so this is an example of an

unmanaged service because the cloud

provider isn't really doing anything

other than provisioning the resources

and then letting you do whatever you

want to and of course they're not going

to like physically mail the VM to you're

going to be connecting to it remotely

probably via SSH now what if you want to

store some files such as images videos

and other types of assets that you

probably need for your app yeah you can

store them on the VM and then serve them

from the VM that would work but

computers aren't specialized for

handling files so a better solution a

more scalable solution and just more

efficient in general is to use some type

of file storage mechanism on AWS it's

called S3 simple storage service it's

basically an object store that's what

they're called and so an object store is

kind of like a black box even though

I've drawn it as like a white box here

but all you really do is read and write

files to it you can delete files of

course but it's very simple the

interface from a programming perspective

is really really simple compared to

manually handling files via like a VM

you don't worry about where they're

being stored you don't worry about

allocating additional space with a VM

you'll have let's say like 100 gbt or

something you know you try to upload a

file and you run out of space you don't

have space on cloud services it's easy

to get more space but it's something you

still have have to kind of manage

yourself as a developer well object

stores like S3 abstract all of that away

for you you'll never run out of space

you'll probably never need to do

anything to scale your read and writs

now as you can imagine these files are

still being stored somewhere they're

being stored on a disk somewhere

persistently and to read and write the

files of course you're using CPU and

probably Ram but again you don't have to

worry about that this is an example of a

managed service because AWS or your

cloud provider is managing all the

infrastructure for you it's also

sometimes called serverless but it's not

to say that there isn't a server

involved there definitely is you can't

do any of this stuff without computers

but it's abstracted away from you and

that's really powerful cuz all you have

to do is worry about your application

logic reading and writing the correct

files you don't worry about the

infrastructure at all it's obviously

less powerful in the sense that you

don't have precise control over what

this service is doing but you usually

have enough control like if you wanted

your files to be stored in a particular

region usually services like this will

let you choose the region that you want

to they'll usually also automatically

replicate files for you so that's

another benefit of using a managed

service because if we stored a file on

our own VM what if the VM dies or you

know some type of Hardware failure well

if you only stored it on one computer

you lose that data that was on that dis

well object stores solve this problem by

replicating the files for you now object

stores are good for storing data but

they're not good at storing everything

what if you had actual application data

not files and images but like you want

to store your database data well

databases are really really complicated

so you usually want to run some type of

specific database software like MySQL or

some other type of relational or

non-relational storage like databases

are basically just a really really

complex wrapper over these resources

particularly dis space well of course if

you want to you can just run your own

MySQL on top of a VM and you can

replicate it among other VMS if you want

to like create replicas of it if you

wanted to do sharding and scale your

database like that you can have some of

your data split among the machines

that's doable but it's complicated isn't

it and so to solve this Cloud providers

will usually give you a managed solution

for storing your data your database data

in the world of AWS it's RDS relational

database service that's if you want a

relational database there's also Dynamo

if you want a non-relational database

once again the whole point of using a

cloud service for this rather than

hosting your own database is because

nobody wants to host their own database

nobody wants to deal with those issues

unless they have to now is a good chance

actually to talk about proprietary

software in many cases AWS isn't doing

anything creative they're actually just

taking open-source software kind of like

we discussed right now my sequel or

postgress is open source to solve this

problem of making the user experience

better is just to take open source

software and then host it and make a

manage service out of it that's a lot of

what relational database service does

but there is something else Dynamo DB if

you want to use this type of database

like this database service you can only

do so on AWS so this is an example of

proprietary software if you built your

app around Dynamo DB and now you decide

that it's costing you too much money you

want to move to a different service well

you're going to have to migrate all of

your data because AWS is the only one

who offers Dynamo DB if you want to go

to Google Cloud you can't and so this is

commonly talked about as vendor lockin

generally you don't want to be locked in

but recognize that it's probably not

going to be a problem unless your app

actually starts scaling because if

you're spending like a 100 bucks a month

on Dynamo DB hopefully your company is

making more than that much money but if

you start spending thousands and

thousands then it becomes an issue and

you'll also find that different

companies have their own versions of

databases for example Google's version

of a Dynamo DB would be either fir store

or Cloud spanner Microsoft has their own

Cosmos DB I think it's called I've never

used it the idea is that once you know

about one service you you know about one

database that AWS offers then going to a

different cloud provider is pretty

trivial because they have their own

version so once you know one you've

learned the others like every cloud

provider has an object store they all

have a VM service they all have their

own proprietary or open source database

Services I talked about how a lot of

services just take open- Source software

and then just make a managed service out

of it well one of the services that

didn't do that was AWS Lambda commonly

known as functions as a service this was

in a sense taking this CPU component the

compute component like if you wanted to

actually create an API or run some type

of compute not necessarily storing

persistent data you would use something

called AWS Lambda and pretty much every

big cloud provider has copied it Google

has Cloud functions I'm sure Azure has

their own but the idea is all you have

to do you don't worry about the

infrastructure at all you don't worry

about the VM the disc you hardly worry

about the CPU and the ram you set like

memory limits and things like that but

basically you take your code as a

developer and that code is pretty much

deployed for you you don't have to worry

too much about the environment you just

take your code and it runs now the

problem with functions as a service this

is one of the most serverless services

that you can do and the reason I say

that is because serverless is really a

spectrum there are services that are

completely managed by the cloud Lambda

would be a pretty good example of that

and then there are other services like

VMS that are not managed at all and then

there are database Services which are

half managed and half not sometimes

Dynamo DB is very managed but the idea

is that there's a spectrum and Lambda or

functions as a service abstract away

pretty much everything for you but that

does come with some downsides for

example if you want to manage any type

of State in your API which is becoming

less and less common with rest apis and

microservices you probably won't need to

do that but if you do you probably won't

be able to use Lambda unless you use

some type of external storage because

when you run a Lambda function you don't

really have access to your disc that's

abstracted away from you it can be good

sometimes and sometimes it can be bad so

it depends on what type of problem

you're trying to solve but with Lambda

most apis can be solved with this way

and if they can why would you ever want

to manage your own VM it's a pain so now

if you just look at these four

categories of services you can build

almost anything with these the one big

category I've probably been lacking on

is networking and I probably won't go

super in depth into that for example

like load balancers CDN and things like

that but logic wise we can do pretty

much everything with these services and

you probably don't even need ec2 you

don't need VMS cuz VMS you can handle

everything with anyway but just looking

at this we have persistent file storage

we have persistent like application data

storage and we have compute we can serve

our front end or our back end where we

go from here is kind of opinionated so

there's two categories I kind of wanted

to talk about one is just observability

in general and I'm not an expert when it

comes to AWS with observability but I

think the services are going to be

pretty similar to Google Cloud but it's

about like your logging your monitoring

data and your alerts being able to

observe how your application is running

via like servers side logs or metrics

for example if you want to see like how

much CPU your VMS are using or how long

your queries are taking that would be

monitoring data and if you wanted to

know if one of these Services went down

for some reason or the latency got too

high you'd probably want to be alerted

of that via some push notification in

real time so that's what observability

is about and the big cloud providers

have done a decent job of giving you

tools for observability but there

actually are other services such as data

dog it's a relatively big company

actually and their whole proposition is

that they can handle observability

better than the big cloud providers even

though there's actually a bit more

friction in using one of these external

tools because there's more work involved

in like setting up the monitoring agents

and things like that but generally

speaking people are big fans of services

like data do because they make this

stuff actually easier for you it's not

just that when you think about something

called Data warehouses the big cloud

providers have I think aw us is is

called red shift Google has big query

and they do a decent job some of them do

better than others but even given that

they're actually are other platforms

like snowflake like data bricks that are

basically companies dedicated to solving

these problems and if they're spending

all their energy on one specific area

then they think and in many cases they

do do better than the big providers

tools like AWS have made development so

much easier than it was years ago where

you needed your own servers still people

complain that AWS is really really

complicated to use and so now there are

companies like versel which pretty much

at a high level are rappers around AWS

and I don't mean that as an insult

because in a sense AWS is just wrappers

around like other open source software

the whole goal of these Cloud providers

is to give you an easier way to use AWS

resources just like how these resources

RDS functions as a service they're just

wrappers around VMS everything is just

an abstraction on top of other things

and that's okay because the whole point

is to make development easier now lastly

I wanted to talk about the differences

between Regional and Global Services cuz

it's kind of a buzzword you see it

thrown around a lot the definition is

kind of fuzzy for example if we talk

about a Content delivery Network a CDN

well that's inherently a global Service

because you have a world m app and a CDN

is basically just a distribution of

servers around the world that store some

static data usually and so you can't

really have a regional CDN now take the

other side take a VM for example VMS are

inherently Regional you can't have one

VM split in five different regions right

you just have one VM in a location you

could have a second VM somewhere else

and a third one somewhere else and you

know you could have these VMS under a

load balancer serving traffic in

different parts of the world that's

perfectly fine the service itself is

regional though a VM is regional

sometimes it gets kind of fuzzy if we're

talking about databases like Dynamo DB

or Google Cloud spanner and before I

even get into those let's just talk

about a regular relational database

service like RDS and I think Google's is

cloud SQL I really prefer the names in

Google Cloud they're just a bit more

intuitive but with a regional database

service you have your world map and you

have your database service hosted in a

certain region even though it can be

partially managed for example like

replicas database backups and a lot of

things can be managed for you by the

cloud provider it's still in a single

region and it'll be serving traffic

probably around the world so some places

in the world are going to receive data a

little bit slower usually it doesn't

matter though but when you get into

Global databases these are super super

super powerful because they actually

manage sharding and replication for you

and they distribute your data all around

the world even though it's distributed

around the world they will work together

generally your request will be routed to

the nearest location the power of a

global database is huge even though most

people probably won't need it it is very

powerful in just handling the scale for

you and making the latency as small

small as possible because data is stored

as close to the user as possible kind of

like with a Content delivery Network and

generally you'll find that Global

Services usually cost more and managed

cloud services also cost more because

the more work that the cloud provider

does for you the more they're going to

charge you of course sometimes it's

worth it though like this is a very hard

problem to solve you probably don't want

to implement your own Global database by

yourself you probably just want to pay

somebody to do it for you this is a lot

of open-ended discussion but I think

that's what's most important I could

have gone into an example of one of

these Cloud providers but looking at it

from a high level I think is most

important and getting hands on with it

which is something we didn't do is

something I'd also recommend to you like

don't just watch me talk about this

stuff try using some of these Services

try building an application out of them