Google Cloud Platform (GCP) 101

“The Google Cloud Platform (GCP) is a suite of cloud services hosted on Google’s infrastructure.”

Google initially launched Google App Engine framework for hosting web applications back in 2008. Gradually they have grown into one of the premier cloud computing platforms competing with Amazon Web Services (AWS) and Microsoft Azure. Google Cloud Platform (GCP) currently dominates the market from computing and storage to data analytics, machine learning, and networking.

Google Cloud Platform products span is growing every single day and they are used by hundreds of developers, data-scientists and researchers. Let’s list down a few of them.

1. 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

2. API management: API Analytics, API Monetization, Cloud Endpoints, Developer Portal, Cloud Healthcare API

3. Compute: Compute Engine, Shielded VMs, Container Security, App Engine, Cloud Functions, GPU, and more

4. Data analytics: BigQuery, Cloud Dataflow, Cloud Dataproc, Cloud Datalab, Cloud Dataprep, Cloud Composer, and more

5. Databases: Cloud SQL, Cloud Bigtable, Cloud Spanner, Cloud Datastore, Cloud Memorystore

6. 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

7. Internet of Things (IoT): Cloud IoT Core, Edge TPU (beta)

8. Hybrid and multi-cloud: Google Kubernetes Engine, GKE On-Prem, Istio on GKE (beta), Anthos Config Management, Serverless, Stackdriver, and more

9. Management Tools: Stackdriver, Monitoring, Trace, Logging, Debugger, Cloud Console, and more

10. Media: Anvato, Zync Render

11. Migration: Cloud Data Transfer, Transfer Appliance, BigQuery Data Transfer Service, Velostrata, VM Migration, and more

12. 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

13. Security: Access Transparency, Cloud Identity, Cloud Data Loss Prevention, Cloud Key Management Service, Cloud Security Scanner, and more

14. Storage: Cloud Storage, Persistent Disk, Cloud Filestore, and more

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How can I use Google Cloud Platform?

Google has provided documentation for getting started and a frequently asked questions page for developers. You can also come across tons of resources from the internet.

- Read their Google Cloud blog which is the best place to learn about current research and product development at GCP —

- Explore Google Cloud Platform conference to get to know more about the platform and it’s latest updates.

Google NEXT —
Google Developer conference which is called Google IO —

- Watch videos from Google Cloud Platform Youtube channel

- Get free course materials from digital tutors around the world. (I’ll share a few of them I have used.)

GCP Tutorials from Cloud Academy

GCP Tutorials and Certification on Coursera

Free GCP podcast by Google

Okay, next very best thing to do is spin up a project your own and get acquainted with it! I’ll go through the basics you can follow along with online tutorials I have mentioned above. Nonetheless, you’ll be prompted to an in-browser tutorial, do not skip them as it is an easy way to get oriented to the platform right off the bat.

Getting Started with Your First Project

First, you’ll want to get an account with Google Cloud Platform if you haven’t already. This can be done in a few easy steps.

  1. Sign up with a Gmail account.
  2. Agree to the terms of service.
  3. Sign up for the free trial (one year of free membership and $300 credit toward your account).
  4. Enter your credit card information.

Creating Your First Project

Now it’s time to create your first project and enable billing. This is fairly straightforward.

To create a project, simply click on “create a new project,” then follow the prompts. Every Google Cloud Platform project needs a unique title so make sure you supply one or accept a generated one. Then scroll down to IAM policies. You’ll want to make sure you have the right privileges in place.

After you’ve gone through a few of the tutorials and created your first project, open up the hamburger menu in the upper left corner. When you expand the menu you’ll see a long list of services.

Available Command Line Tools

gcloud toolkit which supports shell run commands like touch, nano, and cat to create, edit, and output the content of files.

Use SSH to remote access Google Console in browser.
-Use $sudo for root access
-Switch user to root access using $sudo su

Machine Learning on GCP

GCP offers Machine Learning engines, including Tensorflow (its branded machine learning and deep learning framework) and ML APIs.

Google Cloud Machine Learning (ML) Engine is a managed service that enables developers and data scientists to build and bring machine learning models. It does offer training and prediction services as well.

I’ll be writing about my experience in spinning up a VPS and configuring virtual hosts with Linux using Google Compute Engine next.

Until then. 👋

Cloud Specialist - Engineer - Part-time Blogger

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