Google Cloud Platform


This introduction is designed to help you understand the overall landscape of the Google Cloud Platform (GCP). Here, you'll take a brief look at some of the commonly used features and get pointers to documentation that can help you go deeper. Knowing what's available and how the parts work together can help you make decisions about how to proceed. You'll also get pointers to some tutorials that you can use to try out GCP in various scenarios.

GCP resources

GCP consists of a set of physical assets, such as computers and hard disk drives, and virtual resources, such as virtual machines (VMs), that are contained in Google's data centers around the globe. Each data center location is in a global region. Regions include Central US, Western Europe, and East Asia. Each region is a collection of zones, which are isolated from each other within the region. Each zone is identified by a name that combines a letter identifier with the name of the region. For example, zone a in the East Asia region is named asia-east1-a.

This distribution of resources provides several benefits, including redundancy in case of failure and reduced latency by locating resources closer to clients. This distribution also introduces some rules about how resources can be used together.

Accessing resources through services

In cloud computing, what you might be used to thinking of as software and hardware products, become services. These services provide access to the underlying resources. The list of available GCP services is long, and it keeps growing. When you develop your website or application on GCP, you mix and match these services into combinations that provide the infrastructure you need, and then add your code to enable the scenarios you want to build.

Global, regional, and zonal resources

Some resources can be accessed by any other resource, across regions and zones. These global resources include preconfigured disk images, disk snapshots, and networks. Some resources can be accessed only by resources that are located in the same region. These regional resources include static external IP addresses. Other resources can be accessed only by resources that are located in the same zone. These zonal resources include VM instances, their types, and disks.


This overview covers the following types of services:

• Computing and hosting

• Storage

• Networking

• Big data

• Machine learning

Computing and hosting services

GCP gives you options for computing and hosting. You can choose to:

• Work in a serverless environment.

• Use a managed application platform.

• Leverage container technologies to gain lots of flexibility.

• Build your own cloud-based infrastructure to have the most control and flexibility.

Storage services

Whatever your application, you'll probably need to store some data. GCP provides a variety of storage services, including:

• A SQL database in Cloud SQL, which provides either MySQL or PostgreSQL databases.

• A fully managed, mission-critical, relational database service in Cloud Spanner that offers transactional consistency at a global scale, schemas, SQL querying, and automatic, synchronous replication for high availability.

• Two options for NoSQL data storage: Cloud Datastore and Cloud Bigtable.

• Consistent, scalable, large-capacity data storage in Cloud Storage. Cloud Storage comes in several


• Multi-Regional provides maximum availability and geo-redundancy.

• Regional provides high availability and a localized storage location.

• Nearline provides low-cost archival storage ideal for data accessed less than once a month.

• Coldline provides the lowest-cost archival storage for backup and disaster recovery.

• Persistent disks on Compute Engine, for use as primary storage for your instances. 

Compute Engine

offers both hard-disk-based persistent disks, called standard persistent disks, and solid-state persistent disks (SSD).

You can also choose to set up your preferred storage technology on Compute Engine by using persistent disks. For example, you can set up MongoDB as your NoSQL storage.

Networking services

While App Engine manages networking for you, and Kubernetes Engine uses the Kubernetes model, Compute Engine provides a set of networking services. These services help you to load-balance traffic across resources, create DNS records, and connect your existing network to Google's network.

Networks, firewalls, and routes

Virtual Private Cloud (VPC) provides a set of networking services that your VM instances use. Each instance can be attached to only one network. Every VPC project has a default network. You can create additional networks in your project, but networks cannot be shared between projects.

Firewall rules govern traffic coming into instances on a network. The default network has a default set of firewall rules, and you can create custom rules, too.

A route lets you implement more advanced networking functions in your instances, such as creating VPNs. A route specifies how packets leaving an instance should be directed. For example, a route might specify that packets destined for a particular network range should be handled by a gateway virtual machine instance that you configure and operate.

Big data services

Big data services enable you to process and query big data in the cloud to get fast answers to complicated questions.

Data analysis

BigQuery provides data analysis services. With BigQuery, you can:

• Create custom schemas that organize your data into datasets and tables.

• Load data from a variety of sources, including streaming data.

• Use SQL-like commands to query massive datasets very quickly. BigQuery is designed and optimized for speed.

• Use the web UI, command-line interface, or API.

• Load, query, export, and copy data by using jobs.

• Manage data and protect it by using permissions.

Machine learning services

GCP Cloud AI offers a variety of powerful machine learning (ML) services. You can choose to use APIs that provide pre-trained models optimized for specific applications, or build and train your own large-scale, sophisticated models using a managed TensorFlow framework.


GCP offers a variety of APIs that enable you to take advantage of Google's ML without creating and training your own models.

• Google Cloud Video Intelligence API lets you use video analysis technology that provides label detection, explicit content detection, shot-change detection, and regionalization features.

• Google Cloud Speech API lets you convert audio to text, recognizing over 110 languages and variants, to support your global user base. You can transcribe the text of users dictating to an application’s microphone, enable command-and-control through voice, or transcribe audio files, among other use cases.

• Google Cloud Vision API lets you easily integrate vision detection features, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content.

• Google Natural Language API lets you add sentiment analysis, entity analysis, entity-sentiment analysis, content classification, and syntax analysis.

• Google Cloud Translation API lets you quickly translate source text into any of over a hundred supported languages. Language detection helps out in cases where the source language is not known.

• Dialogflow Enterprise Edition lets you build conversational interfaces for websites, mobile applications, popular messaging platforms, and IoT devices. You can use it to build interfaces, such as chatbots, that are capable of natural and rich interactions with humans.

Relevant Blogs:

What is Private cloud?  

Amazon Web Services  

How Cloud Storage Works?  

Multi tier application in kubernetes

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