Google Cloud Services And Tools

Google Cloud Services is a set of Computing, Networking, Storage, Big Data, Machine Learning, and Management services offered by Google which runs on the same cloud infrastructure that Google uses internally for YouTube, Gmail, and other end-user products.

In this blog, we are going to cover each of these services in detail.

Computing Service ^

Google Cloud provides the users with the facility of computing and hosting where you can choose to do the following:

Work in a serverless environment
Use a managed application platform
Build a cloud-based infrastructure to have maximum control and flexibility
Leverage container technologies to achieve maximum flexibility

1.) Cloud Functions

It is a functions as a service (FaaS) offering which provides a serverless execution environment for building and connecting cloud services. It is an event-based, asynchronous compute solution allowing users to create microservices (small, single-purpose functions) that respond to cloud events without the need for an explicitly managed server or a runtime environment. It can be written using JavaScript, Python 3, Go, or Java.

2.) Compute Engine

Compute engine is an unmanaged compute service of Google Cloud. It is an IaaS (Infrastructure as a Service) service that provides virtual machines (VMs) hosted on Google’s infrastructure. Users can perform many tasks after building a compute engine like:

Choose the regions and zones to deploy resources, giving users control over where the data is stored and used.
Choose the required operating systems, development stacks, languages, frameworks, services, and other software technologies as per users’ preference.
Make use of Google Cloud Storage or any third-party technologies.
Use virtual machines (VMs), called instances, to build applications similar to that of as you build your own hardware infrastructure.

3.) Google App Engine

The App Engine is a PaaS (Platform as a service) offering of Google Cloud used for building scalable web applications and IoT backends. It scales applications automatically depending upon the traffic received. It provides users with built-in services and APIs, such as Datastores, NoSQL, and a user authentication API.

4.) Google Kubernetes Engine/ Container Engine

It is a strong Cluster Manager and balanced system for running Docker containers. Kubernetes Engine schedules your containers into the cluster, keeps them healthy, and manages them automatically based on the requirements defined by the user.

5.) Google Cloud Container Registry

Container registry is a private Docker repository that works with the popular continuous delivery systems.

Storage And Database Services ^

Google Cloud provides a variety of storage and database services. Some of them are:

1.) Google Cloud Storage

It offers a unified offering across the Google Spectrum. It handles both live data as well as Cloud archival solutions. This service combines the performance and scalability of Google Cloud with sharing capabilities and advanced security.

2.) Cloud SQL

It is a fully-managed database service which allows user to create, configure, use, and administer relational MySQL and PostgreSQL databases in the cloud.

Cloud Storage & Database Service

3.) Cloud Bigtable

Cloud Bigtable is a high-performance NoSQL Big Data database service, designed to support very large workloads at consistent low latency and high throughput rates. It integrates conveniently with popular Big Data tools like Hadoop and Spark and supports the open-source, industry-standard HBase API. Google uses Bigtable internally to power services including Google Search and Gmail.

4.) Cloud Datastore

It is a NoSQL database that stores data in JSON documents (similar to MongoDB) which are automatically indexed so you can query on individual attributes. It provides an elastic, highly available document-oriented database as a service. It can store terabytes of data.

5.) Persistent Disk

It is a service that provides SSD and HDD storage that can be attached to instances running in either Compute Engine or Container Engine.

6.) Cloud Spanner

Cloud Spanner is a managed globally distributed relational database with ACID transactions, strong consistency, SQL semantics, horizontal scaling, and high availability features.

Networking Services ^

Networking is one of the most important and basics of Google Cloud Platform Services. These services help users to load-balance traffic across resources, create DNS records, and connect their existing network to Google’s network. The types of networking services available are as follows:

1.) Virtual Private Cloud (VPC)

It provides a set of networking services that are used by VM instances. It provides a private network with IP allocation, routing, and network firewall policies to create a secure environment for deployments. Every VPC project has a default network. Users can create additional networks in their projects, but networks cannot be shared between projects.

2.) Cloud Load Balancing

It is a process of distributing workloads across many computing resources. Load balancing helps to scale applications according to user requirements, balance load of Compute machines resources in single or multiple regions. This reduces the cost of resources and maximizes availability.

It provides the following two options:

Network Load Balancing
HTTP (S) Load Balancing

3.) Cloud DNS (Domain Naming System)

Cloud DNS is a scalable, reliable, and managed authoritative DNS service running on the same infrastructure as Google. It translates requests for domain names into IP addresses and offers a UI, command-line interface, and API for publishing and managing numerous DNS zones and resource records. It has low latency, high availability, and is cost-efficient.

4.) Cloud CDN (Content Delivery Network)

CDN is a geographically distributed network that consists of proxy servers and their data centers. The network uses Google’s globally distributed edge caches to speed up content delivery for websites and applications served from Google Compute Engine.

5.) Google Cloud Interconnect

Cloud Interconnect allows Cloud platform customers to connect to Google via enterprise-grade connections with higher availability and lower latency than their existing Internet connections.

Big Data Services ^

Big data services enable users to process and query big data in the cloud to get fast solutions to complicated queries. Google Cloud platform offers various bigdata services like:

Big Data Service

1.) BigQuery

It is a fully managed data analysis service that enables users to:

create custom schemas to organize data into tables and datasets.
load data from different sources
use SQL like commands to query large data
make use of web UI, command-line interface, or API
manage and protect data

2.) Cloud Dataflow

Cloud Dataflow provides a set of managed services and a set of SDKs that can be used to perform batch and streaming data processing tasks. It works well for high-volume computation, especially when the processing tasks can easily be divided into parallel workloads. It is also great for extract-transform-load (ETL) tasks.

3.) Google Cloud Pub/Sub

It is an asynchronous, serverless, large-scale, reliable real-time messaging service. Its usage is not just related to big data but could also be used to coordinate the App engine and Compute engine.

4.) Cloud Dataproc

It is a managed Spark and Hadoop service used to process big datasets using the powerful and open tools in the Apache big data ecosystem.

5.) Cloud Datalab

Cloud Datalab is an interactive Jupyter like notebook used to explore, collaborate, analyze, and visualize data. It is integrated with BigQuery and Google Cloud Machine Learning to provide easy access to key data processing services.

Machine Learning Services ^

AI Platform offers a variety of machine learning (ML) services. Users can select APIs that provide pre-trained models optimized for specific applications, or build and train large-scale models using a managed TensorFlow framework. Google Cloud offers a variety of APIs that enable users to take advantage of Google’s ML without creating and training their own models.

1.) Cloud Machine Learning

It is a managed service that enables users to build Machine Learning models based on mainstream frameworks like TensorFlow.

2.) Cloud AutoML

Cloud AutoML is a Machine Learning product that enables developers who are not that experienced in this field to provide train their high-quality models by Google’s transfer learning and Neural Architecture Search.

3.) Cloud Vision API

It is a REST API used for image recognition and classification. It allows users to integrate vision detection features, including image labeling, face and landmark detection, optical character recognition (OCR), etc.

4.) Cloud Speech API

It is a REST API that can be used to convert audio to text recognizing over 110 languages and variants, to support customer’s global user base.

5.) Cloud Natural Language API

It allows users to add sentiment analysis, entity analysis, entity-sentiment analysis, content classification, and syntax analysis.

6.) Translate API

It allows the users to quickly translate source text into any of over a hundred supported languages. Language detection helps out in cases when the source language is unknown.

Identity And Security Services ^

Identity and Security are one of the most important Google Cloud Services, knowing that data is safe and is encrypted.

1.) Google Cloud IAM

Cloud Identity and Access Management (IAM) can be defined as a framework of policies and technologies for ensuring that authorized people in an enterprise have the appropriate access to technology and resources.

2.) Cloud Resource Manager

This service is used for programmatically managing resource containers used for grouping and hierarchically organizing GCP resources.

3.) Cloud Security Scanner

It is a web security scanner for common vulnerabilities in App Engine applications, like cross-site-scripting (XSS), Flash injection, mixed content, and outdated or insecure libraries.

Management And Developer Tools ^

Management and developer tools are used by developers and development teams to be productive when writing, deploying, monitoring, and debugging applications hosted in Google Cloud.

Management & Developer tools Some of the tools are:

1.) Stackdriver

Google Stackdriver delivers real-time monitoring, logging, and diagnostics across GCP. It provides metrics, dashboards, alerting, reporting, and tracing capabilities.

2.) Console App

It is a native mobile application that enables customers to manage the key Google Cloud services and provides monitoring, altering, and the ability to take actions on resources.

3.) Google Cloud SDK

It manages Google Cloud resources and applications with command-line tools and libraries. The Cloud SDK contains gcloud, gsutil, and bq command-line tools, which can be used to access Compute Engine, BigQuery, and more.

4.) Cloud Deployment Manager

It is used for creating and managing cloud resources with simple templates. It Specifies all the resources needed for applications in a declarative format using YAML.

So this was all about the services and tools offered by Google Cloud Platform to build applications and perform tasks.

Frequently Asked Questions

1.) What tools come with the Google Cloud SDK?

Answer: The Cloud SDK contains gcloud, gsutil, and bq command-line tools which can be used to access different services like BigQuery, Compute Engine, etc.

2.) What database does Google Cloud use?

Answer: Google Cloud uses Cloud SQL which is a managed service that allows users to create, configure, use, and administer relational MySQL and PostgreSQL databases in the cloud.

3.) What are serverless services in GCP?

Answer: Serverless services enables users to build, develop, deploy functions and applications as source code and removing the infrastructure management role.

4.) What is the difference between Compute Engine and App Engine?

Answer: Compute Engine is an IaaS offering where the users have to create and configure their own virtual machine instances whereas App Engine is a PaaS offering where users have to deploy their code and everything else is handled by the platform.

Related References

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