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Google Professional Cloud Developer Practice Test Questions, Google Professional Cloud Developer Exam Dumps

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Kubernetes Engine

2. Demo- Kubernetes Engine

Kubernetes Engine. Let's talk about Google's Container service. It's a managed service. It's really extremely useful for developers. And one of the things we're going to definitely want to know on the developer exam is about engines. Now, this is again the overview part of the certification course, and therefore, realise that we're just going to touch on just a few things to give folks that are new to the platform or haven't been using Kubernetes since it became Kubernetes from Container Engine. So for those folks familiar with Google Cloud but haven't used it in about a year, a year and a half, or whatever it was, it used to be called Container Engine. That was the previous name of the container service. But with that said, let's go to Cup Benete's Engine over here. And you can see, in this specific project,I do not have any clusters deployed. What I want to do is create a cluster. Now, this is remarkably easy and also, to remember, when we deploy Covenante's engine, it's going to deploy as a cluster. Now the minimum configuration is to have three nodes, and then you can scale up from there. Whatever your requirements are, that's your call. Now, one of the things when we create the cluster is that we want to create basically a template. So this is the template here. I can create a regional or a Zonal config.It's up to me. And one of the things you'll notice on the left side is some additional basic steps or wizards in some respects. In reality, some of these will give you instructions. Some of these provide additional insight. So just be aware. Again, they'll just point it out to you where you go and what you're doing. You may need to save what you're doing at the time when you're creating your template. Now this is creating a standard cluster, essentially. And if you're just starting out with Kubernetes,you may want to go to your first cluster. I'm going to go continue in this case just to show you. And you can see it just brings you over to your first cluster template. What this does is pre-populate a few things for you and it's basically deploying a test cluster for you just to spin up and bring down. You'll see that it has five nodes in there. And I have the ability to go down and adjust my region in my zone. In this case, I believe I have a zonal. If I select regional, you can see that I could change that as well. So again, Zonal, it'll place me in a specific zone. I had to select that zone. In this case here, I'll just leave it as the US central one. No harm either way. I'm going to change my notes to three. Now the machine type is small. Once again, you customise this. What's really nice as well is that it gives you some of the key configs over here. Now, this is going to be deployed based on the compute engine. As you may be aware, both Kubernetes Engine and App Engine use the compute engine as its back end for virtual machines. So when we deploy this, it's really just deploying Compute Engine instances. Now one of the things I want to point out is that when we deploy, for example, our cluster, we have a lot of configuration variables. Now I'm going to skip over a lot of this because we're going to go through a lot of this for the different modules throughout the course, but with that said, if I'm going to enable monitoring, for example, the easiest way to deploy monitoring is just to enable it by default it is enabled.So I'm just going to go create and so this is going to create the cluster and then in about a minute or two it should be up and running. We'll go over to Compute Engine and validate that our three nodes are running there. So we'll come right back. Okay, so that got completed. You can see that I have my first cluster. It has three nodes in that cluster. You can see the total resources as well. And then if I want, I can go over here and connect. Now I would just simply copy this runningCloud shell and we'll be going through Cubaand quite a bit throughout the course. This is just more of a show and tell for our friends that are new to this service in Google Cloud. So there you go. So basically, we're authorised for the end point. You can see there I'm connected and now I couldgo over here and start listing, for example, information about the cluster, for example, and then simply I'll just run the container command to list the cluster information and we'll go through a good number of G Cloud commands as well as Kubernetes Day specific commands as well throughout the remaining part of the course. Now one more thing before we go, I did want to point out that we know that this is running on Compute Engine, so let's go to Compute Engine and just see our cluster nodes. As you can see here, this is our clusternodes and this is under VM instances, basically right here and we have one, two, and three right there. That's our first cluster node; there's three in that pool. Let's go ahead and proceed to the next module.

3. Whiteboard – Kubernetes

In this module, What we'd like to do is talk about the possibilities with Kubernetes Engine and the complementary services that go along with DevOps on the Google Cloud platform. There's a lot to talk about here, but I'm going to make it short and sweet and to the point. I want you to think about a few things. When you're considering DevOps, This information is good for pretty much anything as well. If you're studying for any exams, such as cloud engineer, developer, DevOps, focused, whatever, just the reality is even architect exam, this is really good for any of the Google Cloud exams. The reality is that they really need you to know DevOps and the tools that allow you to create a pipeline for your organisation or another organization. So let's talk about this. There are many good use cases for having a CD pipeline, a CI pipeline, and having automated serverless deployments with like cloud build, using cloudfunctions as your preferred function as a service method. But when we talk about the Kubernetes Engine, and I'm going to bring up my pin here,we want to focus on two things. Let's go ahead and start out by talking about clustering. So for example, if I have a G suite domain, and let's say it's company.com, make it simple, and we're already using G suite, and we have our Gmail used by the company, we have Google Drive, and we're just using G suite in general, we can extend that out to Google Cloud. And when we consider doing this, we, of course, have a lot of options from an im perspective. But we want to think of a few things as well. What about if we're going to use KubernetesEngine and we want to cluster our services between, you know, two or more projects? In this case, you know, three projects. Now what we want to consider is probably creating a VPC. Now do we want to create a shared VPC? Again, logically, there are a few things that could be done. But basically, when we want to think about it from that perspective, and I'll get my pen here,a different color, so you can see it is around. And where is that thing? There it is. Red. Okay, Now the VPC is likely going to be shared. So what we're going to need to do, though, is have our projects. So we have our three projects, and a shared VPC is essentially going to contain one or more shared network resources within a project. And of course, I have a project up here and essentially it's really undercompany.com and under this project,whatever you want to call it, I have myIP, my subnets, and again, I could choose to do whatever I want with this. But let's say I create a shared VPC. The easiest thing to do is to create a shared VPC and I could set up the correctIAM permissions, essentially create my service accounts, ensure the cluster administrator can bring up any number of resources needed inside the projects, and be able to monitor and manage the cluster as a whole. Generally, Kubernetes clusters are going to be in a service project and they need to be configured with a primary CIDR range because we need that primary CIDR range. This is essentially, again, for the node IP addresses. We also need two secondary ranges as well, for the pods and service IPS. So we have to think about networking really, really seriously. So let me just write this in for those who are thinking about it or studying for an exam in the future. But we want to think about it from this perspective. So we need the CIDR basically, and we need to have the primary range basically for the projects. And then we need to have a secondary range, essentially for our node IP. And we also need to have two additional secondary ranges, basically for our pods and a service IP as well. I think I got that. And again, just think about it from this perspective. But when we take those three cedar ranges and we put the clusters together, we essentially have what is called, and I'll put it right here, a shared VPC. And again, the networking part of this is literally another hour of discussion to consider, to think about,especially if you're going to do a geographic deployment. We also have to consider ingress and egress charges, but also real structure. I am as well, but from a covenant perspective, there are complementary tools and services we may want to look at. For example, we may just want to let me get my pen. Again, a different color. And we may just want to create a pipeline. And generally, let's say we're going to do this on Google Cloud. We have a couple of choices for our repository or source code. We can go ahead and put it on sourcerepositories, we can put it on GitHub, bitbucket, whatever works. So that's going to be step number one. Let me get my pen. Okay, did I not do that? There it is. Okay, sorry for the delay. Now step number one is to basically get our source code. Step number two: we have to build and test. We probably want to consider cloud building. This is where we're going to go ahead and build or test our code. And then we need to manage our versions. And we probably want to consider, guess what? Container registry And then we may want to put it in here. Again, depending on how you want to do this, you may want to, and again, rooms are a little tight. We may want to consider deploying a spinnaker or something of that nature as well in our V PC.So let me get my handy dandy marker here. There's a lot to go into this. And then after we have spinnaker, one of the things to think about, too, is our application. What's going to process our source code? What is the application that we're going to run and where are we going to run it? Well, we could, of course, think aboutApp Engine, our platform as a service. Cloud functions are what those services are as a service. That's our basic snippets of code that's going to be the trigger for whatever we're trying to set up. And this could be used beautifully,especially in a DevOps environment. Then, too, we're already using KubernetesEngine, but we may also want to consider, for example, Compute Engine as well. And again, we could put a block there for that as well. So whatever we choose, it's up to us to figure out how this is all going to work. Now, we do know that Kubernetes, when it deploys, is going to deploy containers on which compute engine, right? So, again, we're effectively using ComputeEngine when we're using a Kubernetes cluster. There are a lot of moving parts in the Google Cloud, just like any other cloud. And the reality is that there are a lot of options, a lot of amazing tools to use. What I'd like you to think about, whether you're going to do this in real life or for the exam, you need to realise again where Kubernetesfits in, how you deploy the clusters. And not just deploy the clusters, but how does the VPC go together? But also, right, how do you create a pipeline, right? How does this all work together? With that said, let's go ahead and move on to the next module.

Cloud Functions

1. Cloud Functions Basics

Let's talk about cloud functions. Cloud functions are now our function as a service. It's meant to run snippets of code, basically. It is serverless and fully managed. Now this is not exactly a high performance service in the sense that it's not submilliseconds or microseconds or anything, but it's a good service for the right use case. It's meant to trigger after events occur, basically. So, for example, I like to compare functions similar to a web hook in the world of web development. For example, someone goes to your website, hits the home page and what typically happens is a chat box pops up. How can I help you if you need help chatting in the box? sort of similar to that approach. Now, one of the things to think about before taking the exam is to realise that it's limited in its use case for how you can write the cloud functions. Basically, it's JavaScript essentially, which is what we want to keep in mind. So it's written in JavaScript but it runs in a nojscontainer essentially, which is the way I would look at it. It's integrated with Stackdriver. And another thing to note is that there are distinct variations of cloud functions. We have Http, which is our frontend basically, which is the foreground actually. And then the background, which would be like cloud pubsub, for example, would be a background type of service. Cloud functions allow you to write simple, single-purpose functions. It's not meant to create a whole application and basically deploy 100 micro functions at once. It's not really meant for that. It's really meant for you as a developer to take advantage of a serverless solution to maybe add value to your application. Basically, when we talk about a function, It's similar to snippets of code. If you've got a 1021 code base for your micro service to go out and just drop something in a bucket or pull something, for example, from a bucket, then that's what this is for. Some examples of cloud functions would be an object uploaded into cloud storage. And what happens after that object is loaded? Guess what happened? An event is generated and then the event within. Essentially, event information will be sent as a result of cloud functions. It will be triggered, of course, and cloud functions will be triggered when that object is dropped in that bucket, for example. And that's when it executes another way of looking at it. Many of Google's services are now integrated with cloud functions integrates withmany of Google services.Not everyone is just aware of the ones that it typically integrates with. We'll be talking more about cloud functions and the objective coverage for the course. Again, we just want to cover functions at a high level here for those folks that may not be familiar with them. Now, one of the things I want to pay attention to, for example, before we take the exam is to realise that there are drawbacks to cloud functions. For example, we may want to consider App Engine over cloud functions for microservices or for running functions. App Engine performs slightly better than cloud functions. Also, cloud functions, again, may not support every language and, remember, it's just mainly JavaScript. So if we need to write something in another language, like Python, for example, then this isn't going to be a good solution for that. It is serverless. One thing to keep in mind is that the flexibility with which you can run your function is quite limited. If you need flexibility, performance, and better choices for microservices, then App Engine is a better choice. Now, Cloud Functions is not a service that again is considered low latency. It is basically higher latency than perhaps other services. It's a little bit slower now. It is serverless. It's meant for taking services and making them function, basically running your Simplisa code. Now on the exam, the case study question will ask you to specify a cloud service to run a microservice perhaps. Again, I can't disclose exactly how you may run into this on the exam, but expect something centred around a case study, perhaps around cloud functions. And again, understand that App Engine may be the right choice, but Cloud functions may be the right choice as well, based on what you're reading in the case study. So just be aware of that when we're looking at some keywords on the exam, microServices or legacy to Cloud Serverless. These are keywords that you may want to start thinking about, for example, cloud functions. Not exclusively, but again, it could get you very far away from Kubernetes or Compute Engine, perhaps. And then you'd be worried about the Isit App Engine or cloud functions. You know the drawbacks to using microservices as well. Again, microservices are great for running specific tasks. You don't want to run a tonne of microservices on cloud functions for your application because, again, it's not low latency. For example, we're going to be talking more about cloud functions throughout the club. Hopefully this gave you a good idea of what cloud functions are for and how developers can take advantage of them. This may give you a better idea of why you may want to use them and what you can expect around what you're going to be tested on. Let's move on to the next subject.

2. Cloud Functions Demo

Let's talk about cloud functions. Now, cloud functions are a serverless execution environment. It is meant to build micro services and connect cloud services. And it's really focused on what's considered a single-purpose function where we're going to attach these functions to an event. Basically, in the web development world, we would call that a trigger or web hook. And again, that's really the goal. Basically, the function we're going to trigger when an event that you're watching is going to be fired off. Basically, the code that we're going to write is going to go over here to cloud functions. We're going to go ahead and create a function that will execute again based on an event. Really, it's that simple. We don't have to provision any VMs or containers or anything like that. Now, initially, when we create a function,we have some choices to make. For example, is it a web-based trigger, basically a web hook? Or do we want to go ahead and use one of these services as a trigger? Now I'm going to go more into detail on each of these during the course. The reality is that on the exam we're looking at maybe two to three questions that might focus on cloud functions. But again, for demo purposes, I do want you to see how useful this function as a service is. It's actually really simple to use. So, for example, we could select our runtime environment, which we can see when we change it to Python. It gives us a template we can work with. And over here, NodeJS again, and so on and so forth. Now over here I could change variables. I get to just change this for examples, regions, and so on and so on. So this is a regional service, as you can see. And then, over here I could use service accounts. And also, if I had a separate VPC setup, I could create a connector as well. Now we will go into some of the more detailed functions. For example, it triggers more or less around cloud functions during the course. This is more than just a demo to give folks an introductory view of cloud functions. So I'm going to go ahead and create this function, which will take approximately a minute to complete. At the most, maybe even 30 seconds. And it is completed. So it did take approximately 50 seconds, or just less than a minute to create. Here is one of our cloud functions. And then if we go over here to view the function, you can see again, it's got the basic details, nothing has really run yet. You can see it's using my app engine service account and then I can go over here and edit it as well. And then I go to Trigger. You can see the trigger type is http source is listed here and then testing what I could do is enter an event to test and then test the function. And again, it's just a simple "hello world" test. And then I'll add it to the log. Now, again, for the exam, it's fairly simple. I'll cover more details on this. Just remember, from an introductory perspective, that the cloud functions as serverless. It is meant to write single-purpose functions, and we're going to attach these functions to events and then they'll trigger based on an event that's being watched. Your code executes in a fully managed environment. And lastly, we don't have to deploy any infrastructure. It's all there for us in the back end. With that said, let's move on. And over here last week, you could see that little test invocation did kick off as well. Alright, let's move on.

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