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Professional Cloud Developer Certification Video Training Course

The complete solution to prepare for for your exam with Professional Cloud Developer certification video training course. The Professional Cloud Developer certification video training course contains a complete set of videos that will provide you with thorough knowledge to understand the key concepts. Top notch prep including Google Professional Cloud Developer exam dumps, study guide & practice test questions and answers.

101 Students Enrolled
252 Lectures
20:27:00 Hours

Professional Cloud Developer Certification Video Training Course Exam Curriculum

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1

Introduction to Course

4 Lectures
Time 00:12:00
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2

Course Readiness

7 Lectures
Time 00:22:00
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3

Introduction to Google Cloud Platform

5 Lectures
Time 00:32:00
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4

Compute Engine

4 Lectures
Time 00:34:00
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App Engine - PaaS

3 Lectures
Time 00:23:00
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Kubernetes Engine

3 Lectures
Time 00:25:00
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Cloud Functions

2 Lectures
Time 00:11:00
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Cloud Storage

4 Lectures
Time 00:51:00
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Networking

7 Lectures
Time 00:50:00
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Developing on Google Cloud Platform

6 Lectures
Time 00:50:00
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1. Designing highly scalable, available, and reliable cloud-native applications

63 Lectures
Time 04:04:00
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2. Building and Testing Applications

23 Lectures
Time 01:53:00
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3. Deploying applications

45 Lectures
Time 03:25:00
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4. Integrating Google Cloud Platform Services

35 Lectures
Time 02:54:00
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5. Managing Application Performance Monitoring

30 Lectures
Time 02:20:00
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16

Case Study - Hiplocal

3 Lectures
Time 00:11:00
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17

Resources to help Study and Tips to Prepare!

8 Lectures
Time 00:30:00

Introduction to Course

  • 3:00
  • 5:00
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  • 2:00

Course Readiness

  • 2:00
  • 2:00
  • 1:00
  • 2:00
  • 3:00
  • 10:00
  • 2:00

Introduction to Google Cloud Platform

  • 8:00
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  • 6:00
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  • 4:00

Compute Engine

  • 14:00
  • 8:00
  • 2:00
  • 10:00

App Engine - PaaS

  • 6:00
  • 9:00
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Kubernetes Engine

  • 9:00
  • 6:00
  • 10:00

Cloud Functions

  • 7:00
  • 4:00

Cloud Storage

  • 12:00
  • 10:00
  • 16:00
  • 13:00

Networking

  • 10:00
  • 11:00
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  • 11:00
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Developing on Google Cloud Platform

  • 10:00
  • 17:00
  • 6:00
  • 9:00
  • 5:00
  • 3:00

1. Designing highly scalable, available, and reliable cloud-native applications

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2. Building and Testing Applications

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3. Deploying applications

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4. Integrating Google Cloud Platform Services

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5. Managing Application Performance Monitoring

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Case Study - Hiplocal

  • 4:00
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Resources to help Study and Tips to Prepare!

  • 3:00
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About Professional Cloud Developer Certification Video Training Course

Professional Cloud Developer certification video training course by prepaway along with practice test questions and answers, study guide and exam dumps provides the ultimate training package to help you pass.

Networking

6. VPC Whiteboard

Let's talk about what a VPC is. We now have a general understanding of what a VPC is, but it's sometimes easier to visualise it. Now, very simply put, we know that a VPC is really a private, isolated virtual network. We could think of this as a way to manage our networking functionality for our resources.

Another thing I like to explain to people about Google Cloud is that a VPC is a virtual version of a traditional network. Now one of the things about a VPC is that it is global. What's really nice is that it spans all regions. So, for example, if I'm on-premises and I want to access Google Cloud, I may be using services, for example, such as Cloud VPN, or I may be using services such as Cloud Interconnect, whatever that is. But in a nutshell, let's just say I do want to access Google Cloud.

I'm going to access it through whatever interconnection service we're going to use. And when I do this, I will essentially have access to, say, the East Coast of the United States. And I'm going to have my VPC network basically span, for example, multiple regions. In this case, it's us west and us east.

However, part of this enables me to provide a "basically regional and zonal approach" to distributing my network services. As an example, the US East would have roughly this range, and the US West would have roughly this one. So when I deploy a VPC in Google Cloud, what I'm doing is going east. It might be, for example, between Charleston, South Carolina, and us west of Oregon.

I'm not on the Internet, but I'm travelling through Google's well-equipped network to get from Charleston to Northern Virginia, Oregon, or Iowa, or wherever. I'm going to go directly over Google's network, and I don't have to, for example, go out to the Internet and go back into Google Cloud. This is really a nice benefit of using Google Cloud services.

And keep in mind that I could have multiple VPCs in the project as well. Now, throughout the course, I'm going to get deeper into some of the networking capacities that we really want to know for the developer exam. So just be aware that there is a lot to this, but much of it may cover other exams as well as your general knowledge of a VPC. So to sum this up, when I deploy a project, I can have multiple VPCs, and again, I can create one VPC and another VPC here all in, for example, the same project.

So if I go back here to Cloud Architect, for example, and I go to the VPC network, I have a default one and I have a test one as well. So I have two VPCs, and if I want to create another VPC, I can do that as well. So with that said, the VPC provides a lot of power from a structural perspective.

With my VPC networks, remember, I can subnet. I have the option to create my own VPC or build it myself. Again, it's auto mode versus custom mode. What's really nice is that with the VPC network, I can configure subnets, my routes, my firewall, and also how DNS would handle everything as well. So with that said, there's a lot more to talk about from the perspective of VPC networking wise. But just be aware that, for the purposes of this course, this is a good introduction, and we'll talk more about VPCs from a developer perspective in the course. Let's move on.

7. Hybrid Connectivity Networking Whiteboard

When it comes to connecting to Google Cloud, it's important to understand your options and what these options really mean. Basically, I want to talk about cloud VPN and cloud interconnect. And when we talk about cloud VPN and cloud interconnection, there are of course going to be a few things I'm going to highlight here to get you thinking from an introduction to Google perspective, but also from an exam perspective.

Google's virtual private network service is now known as cloud VPN. It's a managed service. However, if we want to connect from on-premises over here, what we want to do is again determine whether we want to spend the money and whether we have the resources. Do we, for example, have a cost estimate for using cloud VPN or cloud interconnect? And if we do, we need to realize a few things. First, cloud VPN and cloud interconnect aren't used together; we use one or the other. So if I want to use cloud interconnect, this is going to provide me with a dedicated private bandwidth link, essentially. And also note that there's cloud interconnection. This is directly from Google. As a result, you must have an embark point that is supported at your on-premises site.

Now, not every site is supported; it depends on your location. However, partner interconnect does the same thing, and that could be an option as well. So partner interconnect, cloud interconnect—it's the same thing. It's just that there are a few. I wouldn't say it's the same thing from a detailed perspective, but the thought is that you're going to get a private connection from on-premises to Google Cloud. You could use a partner or use Google if Google is available. Most customers like to use them directly, or if they have a provider that they're comfortable with, they may use them. It really depends on the use case. Cloud interconnect will provide at least a ten gigabit connection from on-premises to Google Cloud.

And what we want to consider is that cloud interconnect typically has a minimum of ten gigabytes, but it can scale up to 100 gigabytes in some locations. Now one of the challenges is that, again, you have to be in the right location, more or less, and if that works, great. On the other hand, you might want to go with the partner interconnect approach, which will provide you with basically additional bandwidth allocations that are more flexible. And sometimes it's not just ten gigs; you go smaller, like one gig or ten gigs as well. As a result, they have a bit more flexibility and partner interconnectivity. But for the purposes of this course, we want to focus on cloud interconnect and cloud VPN. So we know that if we want dedicated, low-latency, highly available connections between one point and another that are on-premises, then cloud interconnect may fit our bill. Now.

How about a cloud VPN? Cloud VPN is a little different now. It is not a dedicated low-latency connection, but we are using Cloud VPN on this side. And, once again, I apologise for the writing; I probably should have typed it, but you get the idea. So we'll use Cloud VPN over here, and then what we want to do is use our gateway over here. So basically, we want to know that CloudVPN is a gateway service. So we could use Cloud VPN here and then connect to any supported gateway on our end. So it could be from Cisco, it could be from Brocade, it could be from whatever Juniper we may be running—whatever networking switches we may be running, chances are they have a gateway that would work. So we want to check the materials beforehand. So in a nutshell, we want to consider connectivity between Google Cloud and OnPrem.

Cloud VPN and cloud interconnect are the two main options. Now, I did want to make a quick reference to Cloud Router. So Cloud Router is a service that we can use as part of Google Cloud. And what this means is that Cloud Router can expand our capabilities, for example, with dynamic routing changes, which we could add to VPN. So that's just one brief application of Cloud Router. But the main focus will be on CloudVPN and Cloud Interconnect on the exam. So let's go ahead and move on.

Developing on Google Cloud Platform

1. Download SDK

In this module, What we like to do is install the software development kit. Now, there are a few different ways to get to it. We could go to our utilities and click on Downloads. Or we could also go and scroll down to install all the SDKs as well. And also, you can do it via the app engine as well as a couple of other locations. But in general, you should pretty much just go install the SDK. This will bring us over to the SDK web page. I'm running Windows, so I'm going to go ahead and just leave it as an installation for Windows. What I want to do now is, since I have a project created, if I go back, you can see that I have two projects. What I want to do is go download the installer, and your antivirus may pop up. saying, "Do you want to install it again?" Go ahead and select "run." and I'm glad it's safe.

So I want to go next. Read the license. I'm going to go ahead and install this just for myself. Locally. The director will be next. Now, one of the things to point out is that when you install this, it's going to ask you to install other components. Now you could install the Python bundle that's available with it. You do need to have Python installed locally for you to be able to run the SDK locally on your desktop or your Linux box. There are PowerShell tools that are available if you want to use them.

Then there will be beta commands, which are commands that are relatively new but have not yet entered production mode. So select "install." Now, I had this installed before, so I uninstalled it. Generally, there aren't any issues I run into after uninstalling it. Except for once, I did have one issue. So if you do get an issue, you may need to go in and validate it. Did uninstall. You may need to use the Windows Uninstall programme to double-check that it has been removed. If there are no programmes directories, you may need to remove them.

Installing the components You should go show the details. This will show you what it's doing. As you can see, it's installing components. And if I scroll over, it has the app data. And then it's also showing you the tools that have been deployed. So you can see that it's also installed the BigQuery command-line tools as well as the CLI dependencies, etc. It also instals SSH. Okay, so it's still installing, and we will let it complete and come back and check on it. Okay, completed. Let's select next. We do want to just validate whether we want to install or use the Start menu. Shortcuts our desktop, as well as the shell; when we started, do we want it to start immediately?

And then we do need to go global, actually. Excuse me. G Cloud is now knitted with G Cloud in it. You don't have to do it right now. You do it later when you bring it up. But basically, that command is going to go ahead and initialise the cloud shell, and this will help identify what projects and regions and zones you want to connect to and then log into Google Cloud. So let's go finish. Now let me just adjust this so you can see what's going on as efficiently as I can look like. That will be about as good as I'll get. Okay, now what I'd like to just point out is that you can see that it brings up some choices for the configuration to use because I've had other configurations; it pulls up those as well.

But now I want to make a new one because I don't want to use the previous one. So I'm going to select two. Now it says, basically, "Enter a configuration name." What we want to do is enter a configuration that hasn't been utilised before. So I'm going to call this, let's say, GCP training. DevOps I'm going inside. So now it says it's been set to GCP Training DevOps. And basically now it's saying, "What is the account I would like to use?" Well, I'd like to use number two, and it says I am now logged in to that account, and now I have to select the project that I want to use.

And I could either create a new project or select an existing one. So I'm going to go ahead and select GCP Training Number 1. But before we do that, let's go over to the console and validate what we have. So let's go over to projects, and it says GCP Training 23022. Let's validate what we have, and that is a good project. So let's go ahead and select one. And after we select this, what's going to happen is, let's say, for example, that we're working in a specific zone all the time.

Our programs and our cloud services are in Iowa. We have the ability to select a default-compute region and zone if we want. In this case, I'm going to say, "No, I don't need to do that for demo purposes." But if you want to select yes, you can see that it's pretty much done. Now that you've read all this, basically it says that if you need more help or just want to play around, type the G Cloud help command. But let's do this. Let's go type "Google Cloud" and then "Projects" and "List."

What this will do is list my current projects, and you can see that I have a project, giving you the project number, project ID, and project name. And with that said, that's pretty much all you need to do to set up an SDK locally. So I'm logged in, and I'm already in the project that I want to be in. If I want to do anything else, for example, then what I want to do is make sure I know the commands to change, for example. But to do that, if we have help issues or don't know what we're doing, type Gcloud help. Of course, this will give me the flags, commands, and syntaxes that I may want, so let me go ahead and get out of this.

Now, let's say just one more quick command before we continue on. Let's say, for example, that I move this up here into the middle of the screen and adjust it so you can see it in the middle of the screen as well. Okay, so let's go to G Cloud, and let's say I want to know, for example, my available compute regions, let's say.So what I would do is type G Cloud, computespace zones, and then list, and when I enter that, it will bring up the available zones and regions. So I would recommend that you set your zones and regions, especially if you're going to be tied to a specific zone and region. It will save you some time and hassle down the road if you're not paying attention. But once again, that's really all you need to do to get started with the SDK.

It's very intuitive in the sense that the commands and gcloud are straightforward. There is a page you want to go look at. For example, go to Quick Start for Windows and scroll down here to the Gcloud reference, and then over here you can see that there are different commands. For example, these are going to be the commands that you can type for pretty much any service or any requirement that you need, like the Gcloud version. If I want to know what version of GCloud I'm using, it will show me the version that I'm using. That said, I go over to Gcloudsource, and the version is listed here. So if I go to the Gcloud version, it will go ahead and list everything we have, and there are some flags that could be used, but in general, the G Cloud version and then any flag that we want. Pretty straightforward. OK, let's move on.

2. Devops on GCP Part 1

Let's talk about DevOps. Now, on this new exam that was released in November 2018, there's a significant amount of additional material that focuses on development and DevOps, for that matter. Now, what I'd like to do is give a brief overview of what DevOps is and then proceed into the specific areas in Google Cloud that help facilitate both development and operations, working together in one big happy family. And what I mean is, how do all of these Google Cloud services work together, such as CloudBuild, Kubernetes engine, container registry, et cetera? How do they all work together to make your life easier as a developer?

Now, if you're a cloud architect and you haven't done any development, this area will be critical for you to know. Again, if you're familiar with DevOps and use the services I just mentioned, and you understand what cloud endpoints are and how to implement them, you'll be fine. If you don't, you need to definitely spend some time on DevOps and the services that complement it. In Google Cloud, we're looking at probably 10–12% of the questions being development-related, and therefore, that could make or break your exam. Let's proceed. Okay. What is DevOps? Well, DevOps is an enterprise software development phrase that's typically used to help facilitate agile relationships between development and IT operations.

Now, again, there are a lot of different definitions out there. This is sort of the most straightforward one that I decided to use. Now, the goal of DevOps really is to facilitate the relationship between two or more business units. Generally, it's development operations. But I've seen that in some organizations, DevOps, for example, will be called Dev Test Ops or QA Ops. Sometimes those departments are broken up even more. But with that said, let's move on. This is really what's going to, I think, attract a lot of people.

And I want to focus on three terms you're going to see on the exam. It's mostly continuous integration, and they're not going to spell it out for you, but they'll say "CI," "CI pipeline," and "CD pipeline." It's important to know that a CI pipeline is different from a CD pipeline, but it's also important to know why you want to deploy that CI pipeline and how you would do it with the Google Cloud services. We're going to talk a lot more about that coming up. We're just starting in the module, but I just want to make sure you get these three terms. I'm not going to read them to you. I'm not going to provide a dissertation.

If you get lost on this, I'm going to recommend you go over to puppet.com, and the linkdown there has a really good description of DevOps and CI/CD pipelines and continuous deployment. All right, the main thing I do want to point out is to make sure you know what continuous integration is, at least at a high level, and what this really means is that the developer is going to create a copy of basically an application's code. A programme could be a microfunction or a service, whatever it is. These are working copies, and the goal is that the copy of, say, this application that's being rolled out is synchronised with the main line several times a day.

Now the main line is basically going from development to QA to testing to production, essentially at its highest level. Once again, there's more to the story than what I'm talking about. I'm not here to give you DevOps; there are whole classes on that as well. But you need to understand why you want to deploy a CI pipeline; that's really the main focus. And then continuous delivery is more of an evolution. It's sort of built on top of CI, and this is just providing that capability for a development group to be able to roll out changes to production as quickly and efficiently as possible. Now with Google, there are a lot of toolsets that are available and features, for that matter, that you can utilize to facilitate your DevOps pipelines, your CI pipelines, and your DevOps best practices, however you want to look at it. The case studies, though, really focus on the CI capabilities and how Google cloud services such as endpoints, source code repositories, and cloud building can sort of play into solving a problem for the customer as described in the case study. And we're going to have a few case study questions. We're going to talk about this, but I just want to make sure that we get this right. So here is a nice diagram that gives you an overview of basically a CD pipeline, where the developer is going to roll out code in. This code is going to be on GitHub.

Generally, a GitHub is what? It's a repository for your redeveloped code, and then you'll use container builder, which is really now cloud build. still have the same capabilities. I should clarify that only the name changed in January. I'll update the diagram when time permits, but just think about it from that perspective. So you're going to deploy this via-cloud build, let's say, over to a solution for basically Canary testing and development. Spinnaker could be a solution like that. Once again, you need to know what a container builder is and what GitHub is.

These are things you're going to see in the exam. Let's draw another diagram in which they're now using cloud source repositories to cloud build and deploying it to Spinnaker, which is essentially what your Canary testing is for, at least in one of the use cases. Then you can see that the users are also load balanced between the container engine, which is Kubernetes.

Now once again, an older diagram. I'll get around to updating it eventually, but you get the gist. Hope. I hope. Okay, now this is exactly what you're going to have to do on the exam. What is going to happen is that you'll get a case study. This case study will typically ask you to approach the question in one of two ways. The first thing they're going to ask you is that, basically, the customer is doing this, and we need you to help the customer provide a GitHub.

What would you recommend to the customer? Now that Google does have source repositories, which is essentially a good use case in a lot of cases for some customers who want their own private GitHub, they could consider that. Now again, you'll need to select the right Google Cloud service. They will, on the other hand, have questions with four different answers in each of the answers. To put it another way, the answer to each question is divided into four parts. And I've got examples of this at the end. I don't want to get into the questions right now; I want to get into a lot of this at the end. But just to give you an idea of how it works. And what you'll have to do is fill in the blanks with what would go here, what would go here, what would go here, and what would go here, in the correct order and sequence.

And when I say "order in sequence," again, they sort of mean the same thing. However, in Google's world, you'll need to look at how Google is asking the question and determine because the reality is that you don't need a Kubernetes engine. You could be using another service, and they may throw in an alternate service, or you may not actually need load balancing, but they may have one answer without load balancing and another with it. And you'll need to decipher from what they're asking: do you need load balancing or not? Now why wouldn't you want load balancing if the production app is beyond me? But again, we'll go back and focus on these questions a little bit later.

Okay, let's talk about DevOps services. Now, I generally like to bring in AWS, and that way, folks that are already AWS certified already understand a lot of these capabilities with the AWS products. And I hope this helps you correlate the AWS capability to the Google Cloud Platform capability. Now, code repository-wise, basically, what is your GitHub? Where do you store your code? Cloud repositories are essentially a way to keep your code safe, right? In AWS, we have "code pipeline" cloud repositories. In Google Cloud, we build and test code. Basically, this is your cloud-building solution in Google Cloud Build. Automate your deployments in AWS. CloudBuild would do that as well. AWS uses code deployment with Kubernetes.

For example, with pipelines, you want to use something like a unified CI or CD pipeline. And this is crucial for the exam: you should definitely consider using Kubernetes Engine and Container Registry in AWS. You would essentially be using the code "Star." Now. Cloud Build? What exactly is Cloud Build? That's a really good question. The reality is that cloud computing is really more of a facet of multiple capabilities. The goal of this is to run your images, which have been generally imported over from the repository, ensure that the builds are efficient, reliable, etcetera, secure, and be able to take those images and deploy them in different environments. Now, a couple of things about cloud build to note are that, with cloud build, you have a lot of flexibility in defining your workflows for your testing and your deployments.

What's more, you could do this with a variety of environments, including virtual machines, Kubernetes Firebase, and serverless capabilities. You can choose how you want to provide these services. You could also use third-party tools and package everything into Docker containers, which a lot of customers like to use. Maven, for example, appears to be a popper. I think Bazel is another one sometimes as well sometimes.But, in essence, you automate everything, and you can use the free Google services. These are services that you're going to add to the pipeline before or after cloud building. Some of those services would be Kubernetes engine apps, engine cloud functions, cloud source repositories, et cetera.

You could also use a spinnaker. Spinnaker is used quite a bit with Cloud Build as well. And the goal is to make pipeline management easier. You create custom workflows, you enable privacy, and there are a lot of great capabilities there. Now, let's talk about, and we'll go over each of these services in greater detail shortly. But again, the goal is to give you a highlight here. Container Registry, again, sounds pretty straightforward. I think the goal is to help you manage your Docker images, basically control who can do what, how your developers or users can deploy your images, and provide that IAM capability that you would need. And essentially, a container registry is really a private Docker registry. That's really the simplest way to look at it. The goal is that you're going to be able to provide a place for your members, your team members, let's say, to be able to do the work that they need to in a manner that is secure, private, removes vulnerabilities, is highly available, et cetera.

So you want to store, manage, and secure your containers with the Container Registry. I hope that made sense. We're going to talk more about it here coming up. Lastly, before we move on to the next slide, we have cloud repositories. Now, cloud repositories are actually known as "CloudSource repositories" as well, just to clarify that. And it's really a private Git repository, but in the sense that it allows you to collaborate with your team members, but also mainly to connect your workflow to other tools such as Cloud Build, Stackdriver, Cloud Pub Sub, and even App Engine if you so choose. What's really cool is that Google provides this for free, at least at the time of writing. Who knows if that's going to change, but for now it's free. It allows you to create private repositories and lets you organise code as if you're pretty much using GitHub. But basically, it's a private GitHub on Google Cloud.

It's hosted by Google. What's actually cool, though, is that a lot of developers I've talked to and seen using IS like to use source repositories along with their already existing GitHub repository, for example. So you can mirror code as well, if you so choose. OK, let's move on to the next slide. And here's a comparison between Google Cloud and AWS.

Now, AWS has an API gateway. GCP calls the API Gateway essentially "cloud endpoints." Again, to some extent, the same capabilities. I'm going to talk about endpoints here in a few minutes. User interface. Yes. Now one of the main differences with GCP again is that AWS has a really easy-to-use interface. In comparison to Google, I'll say that. I know Google has one in beta or alpha mode. I think they're definitely attending to that. But right now it's strictly CLI, and then listed are open APIs and Rest.

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