The work describes the concept of cloud computing generally and the Google cloud platform specifically, a minor comparison between the three major cloud providers (AWS, M.S. Azure and GCP) is discussed and reasons for choosing GCP are shown. A step-by-step procedure to create a GCP account with a free $300 from google is also shown and creating an instance is described in great details. Other aspects are covered such as Billing, Storage, Networking, Security and much more not to mention where to find all the documentary and necessary classes and code-labs to completely master all the products and services of GCP.
Cloud Computing has been with us for many years now, but still for many medium and small size companies there are many doubts and questions about why and how to migrate there business to the cloud. Should they invest in a team of IT specialists? Is the process very complicated? Would it take a very long time that the company cannot afford? And many other issues that keep MSB’s (Medium & small size business) afraid to approach
Cloud providers. Cloud hosting offers great flexibility, which is a good fit for situations where you do not know (or cannot know) how much computing power you need. You do not need to overprovision to handle situations where you might need a lot of computing power in the morning and less or almost none overnight. In addition, cloud hosting comes with the maintenance built in for several products, which
means that cloud hosting results in minimal extra
work to host your systems compared to other options where you might need to manage your own databases. Google is
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There are many cloud providers out there, including
many more.
With so many competitors in the market, each
of these companies must have its own take on
how to best serve customers. It turns out that
although each provides many similar products,
the implementation and details of how these
products work tends to vary quite a bit[
Google Cloud Platform (GCP) is a portfolio
of cloud computing services that grew around
the initial Google App Engine framework for
hosting web applications from Google's data
centers [
Creating a GCP account couldn’t be easier and can be established in three easy steps: 1. Go to cloud.google.com 2. Click on Create a new GCP account. 3. Enter location and credit card information.
In order to benefit from the $300 free credit that google provides for new users to help them in learning and training with the GCP services, It is very important to choose the choice “individual” when choosing the account type in the step 2 window, the other option “business” doesn’t include the free offer as shown in Figure 1.
After that you just need to enter your address and credit card information and you are all set.
After creating a new GCP account a
welcome screen message appears and then
automatically go to console.cloud.google.com
where you will find your dashboard. The
dashboard is where you will spend most of your
time after migrating your project to the cloud.
In this page you can find all the information,
resources and controls needed to monitor and
control your project. Performance Dashboard
gives you visibility into the performance of
your Virtual Private Cloud (VPC) network. It
provides packet loss and latency (Round Trip
Time, or RTT) metrics between the zones
where you have virtual machine (VM)
instances [
To create a new instance you must go to the main left hand side menu on the console and from there go to the compute engine menu and choose VM instances. The first time you click this link, Google initializes a Compute Engine for you, which should take a few seconds. Once that’s complete, you should see a Create button, which brings you to a page, where you can configure your virtual machine as shown in Figure 3. After giving the instance a name it is necessary to choose in what region you want your instance to be, google has many data centers around the world and in a specific region they have multiple zones as shown in Figure 4.
It is recommended to choose a data center nearer to the customers or users of your project to reduce latency, or a data center in your own country if you have security reasons. Now you must choose and configure what type of virtual machine you need to use for your project, google provides a wide variety of computing power with a suitable amount of memory to assist it, as shown in Figure 5.
Starting from a small micro processor with only 1GB of memory to up to 96 high performance multicore processors with over multiple Terabytes of memory in some data centers.
Now the computing power has been configured it is time to choose what image or operating system your project is going to run on. Google also provides a wide variety of images and multiple versions of each image to choose from as shown in Figure 6.
Next the firewall and security options should be configured as required and click create. It will take a couple of seconds for the GCP data centers to prepare the VM, when prepared, your instance shall appear and you can click on SSH to enter the shell where you can use your VM as you need as shown in Figure 7.
With Cloud Functions, instead of thinking about virtual servers (like Compute Engine), containers (like Kubernetes Engine), or even “applications” (like App Engine), you think only about single functions that run in an entirely serverless environment.
Instead of building and deploying an application to a server and worrying about how much disk space you need, you write only short, narrowly scoped functions, and these functions are run for you on demand. Creating a cloud function can be shown in Figure 8.
In the world of Cloud Functions, other types of events from lots of different cloud services can trigger requests (in addition to regular HTTP requests). For example, a function can be triggered by someone uploading a file to Cloud Storage or a message being published via Cloud Pub/Sub [7].
All of these events can be monitored by different triggers, which can then run different functions—it’s this unique ability to knit different pieces together that makes Cloud Functions so interesting. Cloud Functions allows you to associate small pieces of code to different events and have that code run whenever those events happen. For example, you could hook up a function so that it runs whenever a customer uploads a file into a Cloud Storage bucket, and that function might automatically tag the image with labels from the Cloud Vision API.
When it comes to storage, you should ask yourself a couple of questions: do you want your data to be edge-cached to speed up downloads for users on the internet? Are you optimizing for throughput or latency? Is it OK if the “time to first byte” is a few seconds? How available do you need the data to be? How many concurrent readers do you need to support? The answers to these questions will define what kind of cloud storage is most suitable for your project [8]. The more your storage is frequently accessed and spread on data centers near your users, the less the latency but on the other hand the more the cost, and the opposite is also true, as shown in Figure 9.
GCP provides many services that can support your project or your migration to the cloud, here are some of them: • Artificial intelligence & machine learning: AI Hub (beta), Cloud AutoML (beta), Cloud TPU, Cloud Machine Learning Engine, Diagflow Enterprise Edition, Cloud Natural Language, Cloud Speech-to-Text, Cloud Text-to-Speech, Cloud Translation, Cloud Vision, Cloud Video Intelligence, Cloud Inference API (alpha), and more. • API management: API Analytics, API Monetization, Cloud Endpoints, Developer Portal, Cloud Healthcare API • Data analytics: BigQuery, Cloud Dataflow, Cloud Dataproc, Cloud Datalab, Cloud Dataprep, Cloud Composer, and more. • Databases: Cloud SQL, Cloud Bigtable, Cloud Spanner, Cloud Datastore, Cloud Memorystore. • Developer tools: Cloud SDK, Container Registry, Cloud Build, Cloud Source Repositories, Cloud Tasks, and more, as well as Cloud Tools for IntelliJ, PowerShell, Visual Studio, and Eclipse. • Internet of Things (IoT): Cloud IoT Core, Edge TPU (beta). • Hybrid and multi-cloud: Google Kubernetes Engine, GKE On-Prem, Istio on GKE (beta), Anthos Config Management, Serverless, Stackdriver, and more. • Management Tools: Stackdriver, Monitoring, Trace, Logging, Debugger, Cloud Console, and more. • Migration: Cloud Data Transfer, Transfer Appliance, BigQuery Data Transfer Service, Velostrata, VM Migration, and more. • Networking: Virtual Private Cloud (VPC), Cloud Load Balancing, Cloud Armor, Cloud CDN, Cloud NAT, Cloud Interconnect, Cloud VPN, Cloud DNS, Network Service Tiers, Network Telemetry. • Security: Access Transparency, Cloud Identity, Cloud Data Loss Prevention, Cloud Key Management Service, Cloud Security Scanner, and more.
In security matters, once the users have identified the Google Cloud Platform services that would benefit them, owners can manage which team members or admins have access to which services.
Encryption keys are essential for encrypting data at REST [9]. For this purpose, Google launched Cloud KMS (Key Management Service). Cloud KMS is a managed service that lets users create, rotate, and handle encryption keys for Google Cloud services such as Cloud SQL databases and Compute Engine disks. By using Cloud KMS, you can handle AES256, RSA 2048, RSA 3072, RSA 4096, EC P256, and EC P384 cryptographic keys.
As shown, Google cloud has a very wide variety of products and services that can be implemented to your project very easily and at a low cost. These services can not all be illustrated in this document, but google has provided a number of methods and documentation to help understand and master each service, making GCP one of the easiest to learn and use cloud services on the market. For more details about each service you can go to cloud.google.com/docs where there is an answer for almost everything. As for training and step by step illustration it is recommended to go to g.co/codelabs/cloud where you can find many examples and codelabs that you can benefit from when learning and using the $300 free credit that google generously provides each new learner.