What is Google Cloud?

Summary

Ryan Matsumoto introduces Google Cloud, a scalable and reliable platform for developers to build and run applications using Google's infrastructure. The video highlights Google Cloud's advantages, such as cost-effective scaling during seasonal spikes, and its range of products including Compute Engine, Cloud Run, and App Engine for hosting applications, Cloud Storage for data, and AI tools like Vision AI and Cloud Natural Language for enhancing apps with machine learning capabilities. It also showcases how these products can be integrated for unique use cases, like a social networking site for dogs, and encourages viewers to explore what they can build with Google Cloud.

Takeaways

• 🌐 Google Cloud is a platform that allows developers to utilize Google's computing resources for their applications.
• 💻 Cloud computing involves using someone else's computers to get work done, specifically Google's in this case.
• 🔍 Google Cloud's infrastructure supports a variety of Google's own products including Search, Gmail, and YouTube.
• 📈 One of the main benefits of Google Cloud is its scalability, which is crucial for handling large, seasonal demands like in retail.
• 🛠️ Google Cloud offers a range of products and services designed to solve common problems faced by developers worldwide.
• 🛡️ For databases, Google Cloud provides fully managed options like Cloud Spanner, reducing the need for upfront costs and management complexities.
• 🏢 Compute Engine, Cloud Run, and App Engine are among the services offered for hosting code and applications with varying levels of control and scalability.
• 🗂️ Cloud Storage, Cloud SQL, and Cloud Firestore are examples of Google Cloud's data storage options catering to different types of data and use cases.
• 🤖 AI and machine learning tools are available on Google Cloud, aiding both experienced ML developers and those new to the field.
• 🖼️ Vision AI can analyze images to provide insights that can enhance applications, such as identifying objects within photos.
• 📝 Cloud Natural Language allows for the analysis of text to extract information about entities, sentiment, and content categorization.
• 🧠 Vertex AI serves as a unified platform for training, hosting, and managing machine learning models on Google Cloud.

Q & A

What is the primary purpose of Google Cloud?

The primary purpose of Google Cloud is to provide cloud computing services that allow developers to build and run applications using Google's scalable and reliable computing infrastructure.

How does Google Cloud enable developers to use its computing resources?

Google Cloud enables developers to use its computing resources by sharing the data centers that power Google's own products and services, allowing developers to build and run applications on Google's infrastructure.

What are some of the key advantages of using cloud computing for a retailer setting up a database?

Using cloud computing for a retailer setting up a database allows for scalability during seasonal spikes, cost efficiency by avoiding large upfront costs for additional hardware, and reduced management hassle as the cloud provider handles database scaling, backups, performance requirements, and security.

What is Cloud Spanner and how does it benefit a retailer?

Cloud Spanner is a fully managed database service offered by Google Cloud. It benefits a retailer by managing database scaling, so they only pay for the data storage they actually need, which is particularly useful during massive seasonal spikes like the holiday season.

How does Google Cloud support developers with different needs in hosting applications?

Google Cloud supports developers with different needs by offering services like Compute Engine for virtual machines, Cloud Run for deploying containerized applications on a serverless platform, and App Engine for deploying highly scalable web apps and back-end services.

What are some of the data storage options provided by Google Cloud?

Google Cloud provides data storage options like Cloud Storage for unstructured data such as images, videos, and audio files, Cloud SQL for hosting Google-managed versions of relational databases like MySQL, Postgres, and SQL Server, and Cloud Firestore, a NoSQL document-based realtime database.

How can developers utilize Google Cloud's AI and machine learning tools?

Developers can utilize Google Cloud's AI and machine learning tools like Vision AI for image analysis, Cloud Natural Language for analyzing text, and Vertex AI for building, training, hosting, and managing machine learning models in their applications.

What is the role of Vision AI in enhancing an application with lots of images?

Vision AI provides an API that can perform object detection, find landmarks, extract text from images, and more, allowing developers to enhance their applications by providing insights into what's in each image.

How can Cloud Natural Language help in analyzing user comments in an application?

Cloud Natural Language can analyze text to provide information about entities, sentiment, syntax, and content categorization, which can be used to understand and process user comments in an application.

What is Vertex AI and what does it offer for machine learning developers?

Vertex AI is Google Cloud's unified machine learning platform that offers tools for training, hosting, and managing machine learning models, catering to both experienced machine learning developers and those new to the field.

Can you provide an example of how multiple Google Cloud products can be integrated for a unique use case?

An example is building a social networking site for dogs, where Cloud Storage is used for profile photos, Cloud Firestore for storing profile information, Vision AI for detecting objects in photos, and Cloud Run for deploying the application to the web, allowing it to scale automatically as more users join.

Outlines

00:00

🌐 Introduction to Google Cloud for Developers

Ryan Matsumoto introduces Google Cloud, a scalable and reliable computing infrastructure that allows developers to build and run applications using Google's resources. He explains the concept of cloud computing as utilizing Google's computers to get work done, and highlights Google's global data centers that power their own services. The video outlines the benefits of cloud computing, such as cost efficiency and scalability, especially during high demand periods like the holiday season for retailers. It also provides an overview of Google Cloud's wide range of products and services, including Compute Engine for virtual machines, Cloud Run for serverless container deployment, App Engine for scalable web apps, and various data storage solutions like Cloud Storage, Cloud SQL, and Cloud Firestore. Additionally, the video touches on AI and machine learning tools available on Google Cloud, such as Vision AI for image analysis and Cloud Natural Language for text analysis, and introduces Vertex AI for building and deploying machine learning models.

05:02

🔍 Upcoming Google Cloud Essentials Series

The script concludes with a teaser for the upcoming episodes of Google Cloud Essentials, promising to cover topics such as the Google Cloud Console, the Google Cloud SDK, the free trial offer, and key use cases. It encourages viewers to stay tuned for more insights and expresses excitement for the innovative applications developers will create using Google Cloud's platform.

Keywords

💡Google Cloud

Google Cloud is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube. It is central to the video's theme, illustrating how developers can leverage Google's infrastructure to build and run applications. The script mentions Google Cloud as a shared resource that provides scalable and reliable computing power to developers.

💡Cloud computing

Cloud computing refers to the delivery of computing services, including servers, storage, databases, networking, software, analytics, and intelligence, over the Internet ('the cloud') to offer faster innovation, flexible resources, and economies of scale. In the video, cloud computing is introduced as the concept of using someone else's computers to get work done, with Google's infrastructure being the 'someone else'.

💡Scalability

Scalability is the ability of a system, network, or process to handle a growing amount of work by adding resources. It is a key advantage of cloud computing highlighted in the script. For example, the video discusses how a retailer can manage seasonal spikes in demand without the need for expensive and inefficient on-premise solutions by using Google Cloud's scalable resources.

💡Data centers

Data centers are large buildings filled with servers, storage systems, and networking equipment used to host, manage, and process large amounts of data. The script mentions Google's data centers as the physical locations that house the computing resources shared with developers through Google Cloud.

💡Cloud Spanner

Cloud Spanner is a fully managed, scalable, relational database service from Google Cloud that offers transactional consistency at a global scale, high availability, and SQL semantics. The video uses Cloud Spanner as an example of a managed database service that can automatically scale to meet the needs of applications like a retailer's inventory management system.

💡Compute Engine

Compute Engine is a part of Google Cloud that provides virtual machines (VMs) running in Google's data centers. It allows developers to deploy applications on Google's infrastructure. In the script, Compute Engine is mentioned as a service that offers VMs for hosting code and applications.

💡Cloud Run

Cloud Run is a managed platform that enables you to run stateless containerized applications without having to manage the underlying infrastructure. The video script describes Cloud Run as a serverless platform for deploying containerized applications, emphasizing its fully managed nature.

💡App Engine

App Engine is a platform for developing and hosting web applications in Google-managed data centers. It is part of Google Cloud and supports several popular programming languages. The script positions App Engine as a service for deploying highly scalable web apps and back-end services.

💡Cloud Storage

Cloud Storage is an object storage service from Google Cloud that allows you to store and access data on Google's infrastructure with URL-based access. It is ideal for storing unstructured data such as images, videos, and audio files, as mentioned in the script.

💡Cloud SQL

Cloud SQL is a fully managed database service from Google Cloud that makes it easy to set up, maintain, manage, and administer relational databases. The script highlights Cloud SQL as a service hosting Google-managed versions of popular relational databases like MySQL, Postgres, and SQL Server.

💡AI and machine learning

AI (Artificial Intelligence) and machine learning are fields of computer science that emphasize the creation of systems that can learn and make decisions with minimal human intervention. The video discusses Google Cloud's AI and machine learning tools, which are relevant for developers with or without experience in machine learning, and provides examples like Vision AI and Cloud Natural Language.

Highlights

Introduction to Google Cloud for developers

Cloud computing enables using Google's computers to get things done

Google Cloud provides scalable and reliable infrastructure for building and running applications

Google's data centers house compute, storage, and networking capabilities

Google Cloud shares computing resources with developers

Key advantage of cloud computing is scalability

Example of handling massive seasonal spikes in retail using cloud databases

Fully managed database like Cloud Spanner eliminates the need for manual scaling

Google Cloud offers hundreds of products and services for developers

Compute Engine provides virtual machines in Google Data centers

Cloud Run enables deploying containerized applications on a serverless platform

App Engine allows deploying highly scalable web apps and back-end services

Cloud Storage is ideal for storing unstructured data like images, videos, and audio files

Cloud SQL hosts Google-managed versions of popular relational databases

Cloud Firestore is a NoSQL document-based realtime database

AI and machine learning tools are available for developers with varying ML expertise

Vision AI provides an API for object detection and image analysis

Cloud Natural Language enables analyzing text for entities, sentiment, syntax, and categorization

Vertex AI is Google Cloud's unified platform for training, hosting, and managing ML models

Google Cloud allows seamless integration of multiple products for unique use cases

Example of building a social networking site for dogs using various Google Cloud products

Google Cloud Essentials series will cover more topics like the Console, SDK, free trial, and key use cases

Transcripts

RYAN MATSUMOTO: Hi.

My name is Ryan, and this is an introduction to Google Cloud.

This video is great for anyone new to Google Cloud who's

interested in learning more.

In the next few minutes, we'll talk about what Google Cloud is

and how it can help you as a developer.

Ready?

Let's get started.

[MUSIC PLAYING]

Cloud computing is all about getting things done

using someone else's computers.

So when you use Google Cloud, you're

getting things done using Google's computers.

Google Cloud lets you build in host applications, store data,

and analyze data, all in Google's highly

scalable and reliable computing infrastructure.

Google's data centers, which are located all around the world,

house the compute, storage, and networking capabilities

that power Google's own products and services,

including Search, Gmail, and YouTube.

With Google Cloud, Google is basically

sharing these computing resources

with developers like yourself so you can build and run

applications using Google's computing infrastructure.

One of the key advantages of cloud computing is scale.

Take an example of a retailer looking to set up a database

to help manage their inventory, pricing,

and demand across thousands of stores internationally.

One of the biggest challenges in retail

is figuring out how to handle massive seasonal spikes

during the holiday season.

If you were to try to set up and manage

your own on-premise database, it would likely

be expensive and inefficient to provision additional hardware

to do so.

You'd have to pay large upfront costs

to set up the additional database infrastructure, which

you wouldn't even need for most of the year.

You'd also need to worry about implementing

your own complicated database charting strategy,

managing backups, meeting performance requirements,

and securing the entire thing.

Or you could use a fully managed database

like Cloud Spanner, where all this is managed for you.

Google Cloud would manage scaling for you

so that you only pay for the data storage you actually need.

Google Cloud has hundreds of different products and services

that solve problems shared by developers

all around the world.

While it would take me hours to talk about every single one,

here's a look at several different ways

that these products can help you as a developer.

One of the first things you may want

to do when trying out a cloud platform

is hosting your code and applications.

Compute Engine gives you virtual machines that

run in Google Data centers.

With Cloud Run, you can deploy containerized applications

on a fully managed serverless platform.

And with App Engine, you can deploy highly scalable web apps

and other back-end services.

Next, you probably want to store data, some of it

structured, some of it unstructured.

Cloud Storage is perfect for unstructured data like images,

videos, and audio files.

Cloud SQL hosts Google-managed versions of MySQL, Postgres,

and SQL Server.

You can run the same relational databases

you know without all the hassles of self-management.

Cloud Firestore is a NoSQL document-based realtime

database.

It's popular for use cases like gaming,

where it's very important for users

to have the most up-to-date version of data in real time.

Then there are AI and machine learning tools,

which can be helpful if you are an experienced machine learning

developer, but also if you know zero machine learning,

but still want to take advantage of Google's AI technologies

for your own applications.

Suppose you have images--

lots of images in your application-- and you

want to enhance your application by knowing

what's in each image.

Vision AI provides an API that will take an image

and run object detection, find landmarks, extract text,

and more, allowing your users to use

that information in your app.

Or maybe you want to analyze user comments

in your application using natural language processing.

With Cloud Natural Language, you can analyze a piece of text

and get information about its entities, sentiment, syntax,

and content categorization.

And if you want to build and deploy

your own machine learning models,

you can do that as well.

Vertex AI is Google Cloud's unified machine

learning platform for training, hosting, and managing machine

learning models.

One great aspect of Google Cloud is the opportunity

to seamlessly integrate multiple products to suit

your own unique use case.

Say that you're building a new social networking

site for dogs.

You could start out by storing profile photos

in Cloud Storage.

Then you could set up a Cloud Firestore database

to store other profile information, like dog

names, locations, and hobbies.

Next, you could use Vision AI to detect objects

in each photo, like balls, stuffed animals, and bones.

These machine learning-powered data insights

might help your users find other furry friends

with similar interests.

And finally, you could deploy your application

to the web using Cloud Run.

This would make it easy for your app to scale automatically

as you gain more users.

So there you have it, an overview of what

Google Cloud is and some of the different products

you may be interested in as a developer.

Stay tuned for more episodes of Google Cloud Essentials,

where we'll cover the Google Cloud Console, the Google Cloud

SDK, the free trial, key use cases, and more.

I can't wait to see what you build with Google Cloud.

[MUSIC PLAYING]