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Heroku vs. Netlify vs. AWS vs. Azure vs. Firebase

Modern web applications are often built based on powerful JavaScript features, such as Angular, React, and Vue.js. Those web applications can be hosted anywhere, but you might need more than just hosting. Several big cloud companies, including Heroku, Google, Amazon, and Microsoft Azur, offer practically everything you can ask for, while new competitors, such as Netlify, aim to provide an outstanding user experience for creating modern websites. This article will discuss these platforms and their features: Heroku, Netlify, Amazon Web Services, Azure, Firebase, and Digital Ocean.


The Heroku cloud platform was one of the earliest in June 2007. In addition to Ruby, it supports Python, PHP, Scala, Node.js, Go, Java, and many other popular languages. In Heroku, sites are hosted on a virtual system called Dynos that runs web servers. You can execute Linux commands using Dynos. Dynos can be customized and scalable to your requirements. PaaS provider Heroku is a subsidiary of the popular software company SalesForce. In addition to its acquisition by SalesForce, Heroku has gained many additional integrations.

Netlify Overview:

Serverless hosting and backend service for static web pages and web applications are provided by Netlify, a company specializing in automation and web hosting. Drag-and-drop components and Git repositories make creating and hosting a website easy. By providing features such as user authentication and serverless functions, Netlify eliminates the need for CI/CD pipelines and hosting infrastructure. Furthermore, you can preview each deployment you make or intend to make. Netlify will give you an idea of what your site will look like once deployed. All app pages are pre-rendered in static HTML by Netlify across your GitHub repository. To provide visitors with prebuilt static web pages, Netlify builds its repository and pushes it to GitHub. Then it runs content over a large CDN. Netlify’s free version is already quite generous, and the UX and features provided make working with it seamlessly and intuitive compared to Heroku’s free version


Amazon Web Services (AWS) launched in 2006 from’s internal infrastructure designed to handle its online retail operations. Amazon Web Services was one of the first companies to introduce a pay-as-you-go cloud computing model. AWS’s cloud computing platform currently consists of a mix of infrastructure as a service (IaaS), platform as a service (PaaS), and packaged software as a service (SaaS). There are various tools and solutions available on Amazon Web Services that can be used in data centers in more than 190 countries for enterprises and software developers. AWS services are available for government agencies, education institutions, nonprofits, and private organizations.

Microsoft Azure

The Microsoft Azure cloud computing platform, formerly Windows Azure, provides various cloud services, including computing, analytics, storage, and networking. In the public cloud, users can develop, scale, and run new applications or run existing ones. Azure is a platform that supports all industries, including e-commerce, finance, and a variety of Fortune 500 companies, and is open source compatible. It supports all industries, including e-commerce, finance, and a variety of Fortune 500 companies. Additionally, Azure offers a range of cloud computing services, such as infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), and serverless computing. The Azure subscription model works on a pay-as-you-go basis, which means subscribers will only be charged for the resources they have consumed each month.


Google acquired Firebase in 2014, a Backend as a Service (BaaS) cloud computing platform made public in 2011. In essence, this application development platform makes it easier for developers to develop, deploy, and manage mobile and web applications at a low cost and with high productivity. Among the industries that benefit most from Firebase are computer electronics, technology, travel, and tourism. According to SimilarTech, Firebase has 5.35 percent popularity in the computer electronics industry and 5.28 percent in the travel industry, respectively. SimilarTech claims that 51,913 unique domains use Firebase across multiple tech stacks. Two dominating products, Cloud Firestore and Realtime Database make Firebase so popular among users. It is considered the best option to run all data activities in real time with these well-documented and cloud-hosted NoSQL databases. Further, these databases can be modified while offline and are very scalable. As soon as the user goes online, it syncs the data.

Heroku vs. Netlify vs. AWS vs. Azure vs. Firebase:

Heroku is a backend platform for Node.js. It’s perfect if you want to spin up a microservice and deploy it in minutes. Startups and small businesses typically choose this service when time-to-market and budget are important. Heroku is not a good choice for performance-heavy applications. Large apps will deploy slowly on the platform. Netlify is one of the best platforms to host web applications. It is fast, supports numerous languages, and is simple to use. With Netlify, you can host static sites and use serverless backend services for your front-end applications. If you’re looking to deploy a backend application like a REST API, use Heroku; if you’re looking to deploy a static site or add a new feature to an existing frontend project, use Netlify. Amazon Web Services is a good choice when you work on a considerable project or need a wide range of features and products. AWS is also more secure than younger competitors like Netlify when you’re concerned about IT security (e.g., banks). There are many different services available on Amazon Web Services, which is a serverless architecture. Users can basically get all their needs met with it.

There are essentially no differences between Azur and AWS with regard to their flexible computing, storage, networking, and pricing capabilities. There are several features shared by both public clouds, such as autoscaling, self-service, pay-as-you-go pricing, security, compliance, identity, and access management. AWS and Azure both support hybrid cloud, but Azure does so better. AWS offers direct connections, while Azure offers express routes. The Firebase app development platform is one of Google’s newer offerings that we have yet to explore on a larger scale. You can use it to get started, especially if you are developing Android and iOS apps. The Firebase platform provides backend services as a service.

Final Thoughts

The purpose of this article was to compare Heroku, Netlify, AWS, Azure, and Firebase. When choosing a platform for web projects, you must ask yourself many important questions. The importance of some aspects can vary depending on your situation. If you’re just starting out, you’re probably looking for a cheap and easy solution, whereas larger projects require more sophisticated features and security.

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Why has Amazon Web Service (AWS) become so popular?

The cloud platform Inc (AMZN) offers has become an integral part of Amazon’s business portfolio. In the second quarter of 2021, AWS brought in a record $14.8 billion in net sales accounting for just over 13% of Amazon’s total net sales. In recent quarters, Amazon Web Services has grown steadily by 30%, making it the frontrunner over competitor Microsoft Azure in the cloud computing market. Throughout this article, you will get familiar with Amazon Web Services, tools, and why it has become so successful and popular among IT managers.

What is AWS?

Amazon Web Services which stands for AWS includes a variety of cloud computing products and services. it is a highly profitable division of Amazon that provides servers, storage, networking, remote computing, email, mobile development, and security. There are three main services offered by Amazon Web Services. EC2, Amazon’s virtual machine service, Glacier, Amazon’s cloud storage service, and S3, Amazon’s storage system. According to one independent analyst, AWS has over a third of the market at 32.4%. This is followed by Azure at 20%, and Google Cloud at 9% by the first quarter of 2021. There are 81 availability zones in which AWS servers are located. In addition to providing security by diversifying the physical locations in which data is stored, AWS divides its serviced regions to allow users to set geographical limitations on their services (if so choose). AWS spans 245 countries and territories in total.

Why AWS is Cost-Efficient?

Bezos compares Amazon Web Services to utility companies from the early 1900s. A century ago, factories would build their own power plants, but once they could buy electricity from a public utility. The need for expensive private electricity plants subsided. Amazon Web Services is moving companies away from physical computing technology and toward the cloud. It was traditionally necessary for companies to build and maintain a storage facility if they needed large amounts of storage. If the company wants to store on the cloud, they may have to sign a huge contract for a large amount of storage space they can “grow into”. If the business takes off, building or buying insufficient storage could be disastrous. Not only does it fail, but it could also be costly.

It is the same with computing power. Companies with high traffic typically purchase a lot of energy in order to maintain their business during peak hours. For tax accountants, for example, computing power lays unused during off-peak times, yet it still costs the firm money. As a result of AWS, companies only pay for what they use. they don’t have to build a storage system upfront or estimate their usage first. Their costs are automatically scaled and based on their usage.

The Benefit of using AWS:

When Amazon launched its first cloud computing service, Amazon EC2, in 2008, it broke new ground. AWS offers more solutions and features than other providers and offers free tiers with access to the AWS Console. Users can centrally manage their management. As a service tailored for different skill sets, Amazon Web Services is easy to use for those who are unfamiliar with software development utilities. Web applications can be deployed in minutes with AWS facilities, without the need to provision servers or write any additional code. There is a vast network of Amazon data centers which ensures low latency across the globe. AWS’ replication capacity makes it possible to duplicate services regionally, allowing you to recover quickly.

Amazon Web Services Tools:

1. Elastic Compute Cloud (EC2):

EC2 is a cloud platform provided by Amazon that offers secure and resizable computing capacity. Its purpose is to enable easy access and usability to developers for web-scale cloud computing while allowing for total control of your compute resources. Deploy applications rapidly without the need for investing in hardware upfront, all the while being able to launch virtual servers as needed and at scale.

2. Relational Database Services (RDS) :

Configure, manage, and scale your databases in the cloud with Amazon Relational Database Service (Amazon RDS). Automate tedious tasks such as hardware provisioning, database arrangement, patching, and backups – cost-effectively and proportionately. The RDS database server supports six familiar database engines, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle, and MySQL, which are optimized for performance and memory. It is easy to migrate or reproduce existing databases to Amazon RDS using the AWS Database Migration Service. Visit Amazon’s RDS page to learn more.

3. Simple Storage Service (S3):

In addition to providing outstanding scalability, data availability, security, and performance, Amazon S3 facilitates object storage. For websites, applications, backups, and more, businesses of all sizes can utilize S3 to store and protect large amounts of data. With Amazon S3, data can be organized frictionlessly and access controls can be configured.

4. Lambda

Without owning or managing servers, Lambda lets you run code. users only pay for the compute time consumed. run code for nearly any application or backend utility without having to administer it. Users upload the code, and Lambda does the rest, ensuring high availability and precise software scaling.

5. CloudFront

A content delivery network platform such as CloudFront allows data, videos, apps, and APIs to be distributed rapidly on a global scale in a secure manner with minimal delay. Connected with the global infrastructure of AWS, CloudFront seamlessly integrates with systems like Amazon S3, Amazon EC2, AWS Shield, and [email protected] to manage custom code, personalizing the experience. There are no additional charges when connecting with systems such as Amazon S3, Amazon EC2, etc.

6. Glacier

With Amazon Glacier, you can cache and back up data for years. With these storage classes, you can ensure confident delivery, comprehensive security, and compliance capabilities, and meet regulatory requirements. Using these services, users can store for as little as $1 per terabyte monthly. meanwhile, they can save both in the short and long run when compared to their on-premises servers.

7. Simple Notification Service

Users can chat directly with customers through system-to-system or app-to-person communication between decoupled microservice apps using Amazon SNS. It provides low-cost infrastructure for bulk message delivery, primarily to mobile users.

Wrapping Up

In this article, you learned about Amazon Web Services, their benefits, disadvantages, and tools. Amazon Web Services is a cash cow for Amazon. In the same way, Amazon is transforming America’s retail space By pricing its cloud products extremely cheaply, Amazon is able to offer affordable, scalable services to anyone, from a start-up to a Fortune 500 company.

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What is SaaS? An insightful guide

SaaS which is the acronym for Software as a service refers to the cloud-based delivery of software to users. instead of purchasing an application once and installing it, users subscribe to it. SaaS applications can be accessed from any compatible device through the Internet. the application itself is run by cloud servers, which may be hundreds of miles away from the user’s location. Its provider manages access to the application, including security, availability, and performance. SaaS applications run on the provider’s servers. Whatever the name, these applications run on a provider’s servers. In this article, we will get familiar with SaaS and see why we use it.

What is SaaS?

Software as a service (SaaS) refers to a software distribution model in which a cloud provider hosts applications and makes them available to end users over the internet. An independent software vendor (ISV) might contract with a cloud provider to host the application in this model. In larger companies, such as Microsoft, the cloud provider may serve as the software vendor as well. Besides infrastructure as a service (IaaS) and platform as a service (PaaS), SaaS is one of three main categories of cloud computing. IT professionals, business owners, and individuals all use SaaS applications. Products range from personal entertainment, like Netflix, to advanced IT tools. SaaS products are often marketed to both B2B and B2C customers, unlike IaaS and PaaS. By 2024, analysts predict the market for SaaS products will reach $200 billion, according to a recent report by McKinsey & Company.

How does SaaS work?

Software as a service is delivered over the cloud. Either the provider hosts the application and its associated data on its own servers, databases, networking, and computing resources, or it is an ISV that contracts a cloud provider to host the application at the provider’s data center. Web browsers are usually used to access SaaS applications. If you have a network connection, you can access the application from anywhere. Consequently, these applications eliminate the need for setup and maintenance. Users simply subscribe to access the software, which is ready to use.

As a service provider, SaaS is closely related to application service providers (ASPs). Moreover, on-demand computing software delivery models are where the provider hosts the customer’s software. Software-on-demand SaaS allows customers to access an application that has been designed specifically to be distributed as a SaaS application over the network. All customers receive the same source code for the application. New features or functionalities are rolled out to all customers as soon as they are released. They store customer data locally, in the cloud, or both locally and in the cloud, based on the service-level agreement (SLA). By integrating these applications with other software via APIs, businesses can integrate their own software tools with them.

What are the Pros and Cons of Software-as-a-service?

There are a number of advantages and disadvantages to using SaaS applications, although the benefits often take over the disadvantages for modern businesses.


1. Cost Effectivenes

With SaaS, companies can reduce their internal IT costs and overhead. The providers maintain the servers and infrastructure that support the application, so businesses are only charged a subscription fee.

2. Scalablity:

As usage increases, the SaaS provider scales up the application by adding more database space or computing power.

3. No need for installation:

Its providers update and patch their applications regularly.

4. Accessibility from all devices:

The SaaS applications allow users to access them from any device and anywhere. This gives businesses the flexibility to have employees operate anywhere in the world, while users have access to their files wherever they are. Moreover, most users use multiple devices and change them frequently. they don’t have to reinstall SaaS applications or purchase new licenses every time they change devices.

5. Customization :

It is common for SaaS applications to be customizable and to integrate with other business applications.


1. Security

SaaS applications often face security challenges due to cloud computing.

2. The need for stronger access control

Service disruptions, unwanted changes to service offerings, or security breaches can all result in problems for SaaS customers – all of which can have a profound impact on their ability to use the service. It is important that customers understand their SaaS provider’s service level agreement and ensure it is enforced to proactively mitigate these issues.

3.Vendor lock-in

Switching vendors can be challenging with any cloud service provider. customers need to migrate large amounts of data when switching vendors. Moreover, some vendors use proprietary technologies and data types, which can further complicate the transfer of customer data between different cloud providers. Vendor lock-in occurs when customers cannot easily switch between service providers because of these factors.

The Future of Software-as-a-Service

In a short time, cloud computing and SaaS have made significant strides. Increased awareness and uptake have accelerated SaaS product growth, which has led to the development of SaaS Integration Platforms (SIPs) such as Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). Non-core IT activities will continue to be outsourced to specialists who can do them better.

Companies can develop end-to-end integrated solutions using the cloud. This allows them to concentrate on their core competencies while outsourcing hardware and software issues. Through the adoption of various “SaaS” services, companies will be able to establish long-term relationships with service providers, leading to innovation as customers’ needs grow. Future applications of high-performance computing will include analyzing large amounts of customer data and monitoring application logs. It may be possible for SaaS one day to help businesses address critical challenges such as predicting which customers will churn or what cross-selling practices are most effective. As businesses increasingly require large amounts of data, software performance, and backups, cloud-based providers are becoming increasingly popular.

Wrapping Up

In this article, you learned about Service-as-a-Software, what it is, how it works and its pros and cons, and its future of it. In general, As a cloud-based technology, software-as-a-service, or SaaS, provides users with software. rather than buying the application once and installing it, SaaS users subscribe to the application. SaaS applications are accessible from any computer or mobile device that has a compatible Internet connection. the actual application runs on cloud servers far away from the user’s location.

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How to quickly create and deploy a Vue.js web Application using Github?

In the previous articles we have discussed the benefits of using the Vue.js front-end framework. In this article, we are going to see how we can quickly create and deploy a web application using Vue. Of course, you can create any kind of web application according to your taste and need and the main focus of this tutorial-based article is not on the application itself but mostly on the configuration, installation of the packages, and deployment of the web application. As a result, we will consider the default written script in the App.vue and main.js as it is – You can replace your own code in them – And will work on using Netlify to host our files. If you are not familiar with Netlify we will introduce it in the first section of this article.

What is Netlify?

As web developers, we worry about how to distribute or serve our applications to customers after completing the main task of creating applications customers can use. To deploy your Vue JS application, you can use a variety of services. These services include GitHub Pages, GitLab Pages, and Bitbucket Pages, as well as Firebase, hosting, Heroku, Digital Ocean, AWS solutions, CloudFront, Now, and Surge, among others. In this article, we will be focusing on Netlify, one of the easiest platforms for setting up your Vue JS application.

Using Netlify for your Vue JS web application is one of the fastest ways to deploy your Vue JS application. It is a serverless platform based on Git. In addition, it allows you to build, collaborate and publish your apps quickly. Moreover, Netlify provides solutions that cover cloud lambda functions and even JamStack architecture. It integrates with the most modern web development tools. There are three reasons to use Netlify to deploy your app. First of all, it is super-fast to set up and provides a 3-step process that is easy for even a novice to follow. the second reason is that it is free. And the third reason is that it will continuously deploy changes as soon as you push them.

Step by Step Guide:

Now that we know what we will do and why we will do it, let’s get started. The first step is to make sure you have Vue installed on your operating system. If you have not installed it yet, the command below will do that for you. npm install -g @vue/cli We can also check the installation success and its version by the following command: vue --version Now we are ready to create a new project. To do so, you can use the below command: vue create TestVue It will then create a scaffold in the file location you selected of a Vue JS application based on your default settings. Now switch to the directory that has been created and run the default script created by Vue JS, using the below command. cd TestVue
yarn serve
Notice that if you are using npm instead of yarn, you can use the following: npm run start After that, if everything goes well, you will be able to see the following result in your localhost address given in the terminal:

Afterward, you can enter your scripts in the main.js and App.vue files which are located in the src folder. Notice that if you are using anything like bootstrap, you need to have a correct version of it installed on your operating system. Meaning that the version needs to be compatible with the Vue JS version. The next thing you should do is to minimize the size of the project files by running the build command: npm run build

# for yarn use this one:

yarn build
The result should be something like this:

Deployment on Netlify:

Now, we are ready to deploy our Vue JS application to a host. As we mentioned earlier, we will use Netlify. Before we want to get started with it, we should push our script to Github. Then we will use the repository on Netlify to deploy the App on its web servers. To make this happen follow the steps taken in the photos. First, we should head over to Netlify Signup Link and sign up. You will then see the signup method, in which you should choose Github or Gitlab or anywhere you wish. However, this tutorial goes on with Github:

Next, we should authorize Netlify to connect to our GitHub account:

Afterward, fill in the blanks:

Select import from Git.

choose GitHub.

Once more, authorize Netlify to connect to your GitHub account.

Based on your plan, select one of the boxes.

If you have selected all repositories, specify the one that you want to deploy.

enter the specifications as below:

That’s it! Now you can have your web application up and running and if you update the repository, the Vue JS app on Netlify will be updated instantaneously.


In this tutorial-based article, you learned how to create a web application using Vue.js and also how to deploy it on a web page using Netlify. This way you can easily push your projects on GitHub and deploy them using the Netlify host. One of the highlights of Netlify is its easy 3-step deployment process, as well as its continuous automated updates.

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Fast API compared to Django and Flask

This article mainly focuses on three different types of python web frameworks including Django, Flask, and Fast API. The purpose of this article is to discuss three frameworks that are used for the development of Python-based web applications. Besides understanding these frameworks, we will also look at their advantages and disadvantages. Finally, we will compare these frameworks on the basis of several important parameters. We will cover the following major points in this article.

Django Framework:

Django is a free and open-source web framework based on Python. Developed in 2003 by Adrian Holovaty and Simon Willison, it follows the model-view-template (MVT) architecture pattern. Due to its robust behavior, it is now one of the most popular frameworks in the world. There are many giant websites such as Instagram, Mozilla, Nextdoor, and Clubhouse that use Django to build complex database-driven websites. one of its primary goals is to make it easy to develop complex database-driven websites. The reasons for being famous are less code, low coupling and reusability, and pluggability of components at the time of development. These features also help with rapid development.

Pros and Cons of Django:


1. It generates HTTP responses and is also based on the MVC (model-view-controller) architecture. Using the MVC architecture, you can create user interfaces that have three main components. In a model-view-controller architecture, the model manages the data of the application. The view renders the user interface of the model, and the controller controls the input and the interaction between the user and the model.

2. In addition to the ORM (object-relational mapper), the framework also includes a relational database, web templating system, and URL dispatchers; with the ORM connecting the models, the relational database handling HTTP requests, and the URL dispatcher handling regular expressions as controllers;

3. Several applications can be bundled using the contrib package in the Django framework, and we can allow third-party code to run within running projects using Django’s configuration system.

4. Provides security against most typical web attacks like cross-site request forgery, cross-site scripting, SQL injection, and password cracking.

5. The rest framework from Django provides powerful API functionality; The rest framework has an API browser for testing endpoints, and Django with the rest framework supports authentication and permission rules.

6. It is possible to perform numerous tasks with Django, including managing content, RSS feeds, verifying users, and generating site maps.

7. In addition to providing scalability, Django also provides maintenance by allowing code to be reused and maintained properly so that it can’t be duplicated.


1. There are no conventions in Django frameworks. The components often do not match when configuring “on the go”. This slows down development since everything needs to be well defined during the process.

2. A problem with Django’s software is that it contains too many reusable modules, and this can slow down development. its slowness is also due to the need to verify that previous versions are compatible with the new ones.

3. Small projects with fewer features may not be suitable for Django because of its complicated functionality. Flask is a better option for small projects.

4. There are a lot of features and configurations in Django, which makes it hard to learn quickly.

Flask Micro-Framework

In a nutshell, Flask is a microframework as it does not require any specific libraries or tools for web development. It leverages pre-existing third-party libraries for common functionality. This framework makes it easy and fast to build lightweight applications with fewer features by using the Python programming language. Flask is a framework for building web apps using the Python programming language. Flask is based on werkzeug, jinja, MarkupSafe, ItsDangerous. Which all are part of the pallet projects.

Pros and Cons of Flask


1. Its simplicity makes it easier for developers to learn and comprehend Flask’s principles. therefore, it is suitable for beginners.

2. As opposed to Django, Flask has a smaller codebase. it is also easier to use and more flexible, making it suitable for smaller projects.

3. In addition to being simple and lightweight, Flask is also extremely functional and able to be divided into several modules. All of these parts are flexible and easy to change, move, and test on their own.

4. Microframeworks like Flask enable tech products to grow very rapidly. For example, if you want to start small, but you want to grow your product eventually. However, you haven’t decided where to go. With Flask, you’ll have time to think about the possibilities and scale up.

5. In addition to its flexibility, Flask allows you to add changes at almost any point in the development process.


1. Lacks CSRF protection. Cross-Site Request Forgery is a technique by which victims’ credentials are used to carry out various actions on their behalf. Flask-WTF extension is often used to enable CSRF protection to address this issue.

2. It is better to use Flask for simple and innovative cases rather than for large projects that require complex features and fast development.

3. Compared to Django, Flask’s community is smaller and as a result, you may have a harder time finding a solution to some problems.

4. As a microframework, Flask does not come with many tools. Developers often have to add extensions manually. For example, libraries are often added. By adding too many extensions, the framework will have to process a lot of requests, so it can slow down the development process.

Fast API

In recent years, FastAPI has gained popularity as the fastest framework out of the three web frameworks. Some developers regard it as the best framework. However, it is very soon to judge whether it can outperform Django or Flask in all aspects. The main reason is, that they are completely different, and the choice depends on the type of your project.

With FastAPI, you can build APIs with Python 3.6+ versions which is one of the fastest Python frameworks. It is a framework that is fast to code and causes fewer bugs than other frameworks. The main distinctions of Fast API are fast development, fewer bugs, and high and fast performance. The FastAPI framework is used by companies such as Netflix and Uber that support asynchronous programming and run with WSGI, ASGI, and JSON Schema. FastAPI is crucial for integrating Starlette, Pydantic, OpenAPI, and JSON Schema.

Pros and Cons of Fast API


1. There is a reason for the name of this framework ‘Fast API’. Because of Starlette and Pydantic, it is at the same level as NodeJS.

2. Developers do not need to worry about documentation since FastAPI comes with Open API, Swagger UI, and ReDoc already integrated. Developers can focus on the code rather than getting the tools set up.

3. Asynchronous code is probably the most exciting feature of FastAPI. using the Python async/await keyword, asynchronous code can reduce execution times significantly.

4. With its autocomplete feature, applications can be created with a lower amount of effort and can also be debugged faster.

5. FastAPI integrates well with OAuth 2.0 and external providers.


1. The guideline community is small because FastAPI is a relatively new framework. We lack external educational materials like books, courses, or tutorials.

2. During the development of the applications, we must tie everything together in FastAPI, resulting in a very long or crowded main file.

Summing Up (Which one is better?):

In this article, you got familiar with all the three web frameworks, Django, Flask, and the recently-released Fast API. you learned about the pros and cons of each one of them. Now, still one question remains: Which one is the most suitable? To answer this question, you need to first answer another question: For which use case? As different projects need different qualities in different aspects, We need to first know our use case and then decide which framework is the best.
There are four parameters that determine the quality of a web framework. Performance, Community, Flexibility, and Packages. In terms of performance, Considering what we read in the above article, FastAPI is the newest, most advanced, and most modern framework. it offers the fastest performance. Flask is also a fast framework because of its micro-framework specifications. Overall, it is faster than Django. In terms of community, Due to its market value, Django will take over when it comes to the number of users and community. It is the earliest among them, which is why it covers most of the community. FastAPI is newly developed and has a lower community than Django. In terms of flexibility, Flask is the best because it provides compatibility to modify every part of the application, which makes it the most flexible framework. And finally, In terms of packages, the biggest Python-based web application development framework is Django, which has around 2500 packages; Flask is a microframework, which has no packages, and Fast API has fewer packages.

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What is DoS Attack and How to Prevent it?

Denial-of-Service attacks (DoS) shut down a machine or network by flooding it with traffic or sending information that triggers it to crash, preventing its users from accessing it. DoS attacks accomplish this by flooding the target with traffic. The DoS attack robs legitimate users (e.g. employees, members, or account holders) of the services or resources they expect. Often, DoS attacks target the web servers of high-profile organizations, such as banks, commerce, and media firms, as well as government agencies and trade associations. Although DoS attacks rarely result in the theft or loss of significant information or assets, they can cost the victim a lot of time and money to handle.

How Does a DoS Attack happen?

Often, DoS events are caused by the overloading of a service’s underlying systems. In order to clarify how overload-based DoS attacks work, let’s imagine an attack on a shopping website. The requests that you make when you shop online pass through your Internet Service Provider’s network. Through one or more exchanges, and out to other providers’ networks. Once your clicks have passed through the hosting service, they reach the shopping site’s infrastructure.
Each server within a shopping site will do a small part of the work needed to create the page you see. These include database servers that provide product lists and application servers that interpret product information. And also, web servers that create the pages you are viewing. Like humans, each server can only do so much work in a given period of time. Thus, when too many users request pages from a shopping site at once, the infrastructure or servers may not be able to handle everyone’s requests in a timely manner. This may result in some or all users not being able to view the shopping site. or, to put it another way, they are unable to access the service.

DoS and DDoS:

In a Dos attack, the attacker employs a small number of attacking systems (possibly just one) to overload the target. This was the most common approach to attacking the Internet during the early days when services were small and security technology was developing rapidly. Nevertheless, nowadays, a simple DoS attack is usually easy to ward off since the attacker is easily identifiable and blocked. Industrial control systems may be notable exceptions to this, as equipment may not tolerate bogus traffic well, or may be connected via low bandwidth connections that are easily saturated.

On the other hand, in DDos (stands for Distributed Denial of Service) attacks, an attacker recruits (many) thousands of Internet users to send a small number of requests each, which, when combined, overload the target. These participants may be willing accomplices (for example, attacks initiated by loosely organized illegal “hacktivist” groups) or unwitting victims whose machines have been infected with malware.

Different Types of DoS Attacks:

Volume Based Attacks

Flooding attacks include UDP floods, ICMP floods, and other spoofed packet floods. The attack aims to overload the attacked site’s bandwidth and is measured in bits per second (Bps).

Protocol Attacks

Among them are SYN floods, fragmented packet attacks, Pings of Death, and Smurf DDoS attacks. These attacks consume the actual server resources or those of intermediate communication equipment, such as firewalls and load balancers, and are measured in packets per second (Pps).

Application Layer Attacks

There are many types of attacks in this class. These attacks include low-speed attacks, GET/POST floods, attacks on Apache, Windows, or OpenBSD vulnerabilities, and more. Usually composed of seemingly innocent and legitimate requests, these attacks aim to crash the web server. The magnitude of these requests is measured in Requests per second (Rps).

Different Types of DDoS Attacks:

UDP Flood

User Datagram Protocol (UDP) floods, by definition, are DDoS attacks that flood a target with UDP packets. Their goal is to flood random ports on a remote server. It causes the host to keep checking for applications listening on that port, and (when none are found) reply with an ICMP ‘Destination Unreachable’ packet. This consumes host resources, resulting in unavailability.

ICMP (Ping) Flood

This attack is similar to the UDP flood attack in that the target resource is the subject of the attack with ICMP Echo Request (ping) packets. Due to ICMP Echo Reply packets that the victim’s server sends, this type of attack consumes both outgoing and incoming bandwidth.

SYN Flood

As a result of a weakness in TCP connection sequence (the “three-way handshake”), an SYN flood DDoS attack exploits a feature of an SYN request. This feature consists of the fact that in order to initiate a TCP connection with a host, an SYN request must be followed by an SYN-ACK reply from that host. And also an ACK response from the requester must come in the following. SYN floods occur when the requester sends multiple SYN requests without acknowledging the host’s SYN-ACK response or sends the SYN requests from a spoofed IP address. In either case, the host system keeps waiting for acknowledgments to each request, binding resources until new connections are not possible, resulting in a denial of service.

Ping of Death

In a POD attack, the attacker sends multiple malformed or malicious pings to a computer. the maximum IP packet length is 65,535 bytes (including headers). Nevertheless, the Data Link Layer usually limits the maximum frame size – for example, 1500 bytes over an Ethernet network. In this case, a large IP packet consists of multiple IP packets, and the recipient host reassembles the IP fragments into a complete packet. The recipient ends up with an IP packet with more than 65,535 bytes when reassembled as a result of malicious manipulation of fragment content in a Ping of Death scenario. The packet overflows the memory buffer, causing legitimate packets to underperform.

HTTP Flood

A DDoS attack involving HTTP floods exploits a web server or application using seemingly legitimate HTTP GET or POST requests. HTTP floods don’t use sub-standard packets, spoofing, or reflection techniques, and take less bandwidth than other attacks to bring down a site or server. When a server or application has to allocate maximum resources to every request, the attack is most effective.

NTP Amplification

In NTP amplification attacks, the perpetrator exploits publicly-accessible Network Time Protocol (NTP) servers to overwhelm a victim server with UDP traffic. the name of the attack is amplification assault because the query-to-response ratio is anywhere from 1:20 to 1:200. In other words, if an attacker obtains a list of open NTP servers (e.g., by using Metasploit or Open NTP Project data), he or she can easily launch a devastating DDoS attack that is high-bandwidth and high-volume.


With Slowloris, one web server can take down another without affecting other services or ports on the target network. Slowloris does this by keeping as many connections as possible open to the target web server. Using Slowloris, the target server has a connection, but only a partial request is sent to the server. Slowloris constantly sends more HTTP headers, but never completes a request. the target server keeps each of these false connections open until the maximum concurrent connection pool reaches the overflow level, which prevents legitimate clients from connecting.


In this article, you learned about DoS and DDoS attacks and their different types. Most of the attacks occur by creating an overload of requests to the target server by the attacker. The attacker may have different motivations such as a political reason, boredom, money extortion, etc. The Overload DoS attacks may happen on the application layer or the network layer.

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Why is Kubernetes an Important Tool ?

Kubernetes also known as “K8s”, automates the deployment and management of cloud-native applications by orchestrating containerized applications running on a cluster of hosts. With this tool, workloads are distributed across a cluster and dynamic container networking is automated. It allocates storage and persistent volumes to running containers, scales automatically, and continuously maintains the desired state of applications, providing resilience. The Kubernetes platform is an open-source platform for managing containerized workloads and services. It facilitates declarative configuration as well as automation. There is a large, rapidly expanding ecosystem of Kubernetes services, support, and tools available.

Why Do we need Kubernetes?

When it comes to the necessity of Kubernetes, the summarized answer is that it saves developers and operators a lot of time and effort, allowing them to focus on building the features they need instead of trying to figure out and implement ways to keep their applications running well, at scale. As Kubernetes keeps applications running in spite of challenges (such as failed servers, crashed containers, traffic spikes, etc.), it reduces business impacts, reduces the need for fire drills to restore broken applications, and protects against other liabilities, such as the costs of not meeting Service Level Agreements).

Kubernetes automates the process of building and running complex applications. here are just a few of its many benefits:

1. The standard services that most applications need, such as local DNS and basic load balancing.

2. The majority of the work of keeping applications running, available, and performant depends on standard behaviors (such as restarting this container if it dies).

3. Pods, replica sets, and deployments are abstract “objects” that wrap around containers, enabling easy configurations around collections of containers.

4. A standard API that applications can call to easily enable more sophisticated behaviors, making it much easier to create applications that manage other applications.

Kubernetes Use Cases:

You can bundle and run your applications using containers. In a production environment, you must make sure that the containers that run the applications don’t go down. For example, if a container goes down, another container needs to start. Wouldn’t it be easier if a system handled this behavior? As a result, Kubernetes can be your solution. Kubernetes provides a framework for running distributed systems in a resilient manner. Kubernetes handles scaling and failover for your application provides deployment patterns, etc. For instance, it can handle a canary deployment for your system easily. Its use cases include:

Automated rollouts and rollbacks

The Kubernetes platform allows you to specify the desired state of your deployed containers, and it can automatically change the state to the desired state at a controlled rate. For example, you can automate it to create new containers for your deployment, remove existing containers, and adopt all of their resources into the new container.

Storage orchestration

You can use Kubernetes to automatically mount local storage, public cloud providers, and more.

Service discovery and load balancing

The Kubernetes platform allows exposing containers either via their DNS names or by using their own IP addresses. In the event that high traffic to a container occurs, Kubernetes will load balance and distribute traffic to keep the deployment stable.

Automatic bin packing

Kubernetes uses a cluster of nodes to run containerized tasks. You tell the system how much CPU and memory (RAM) each container needs. Kubernetes can fit containers onto your nodes to maximize resource utilization.

Secret and configuration management

It is possible to store and manage sensitive information, including passwords, OAuth tokens, and SSH keys, without having to rebuild your container images or expose secrets to your stack configuration with Kubernetes. You can deploy and update secrets and application configuration without having to rebuild your container images, and you do not have to expose secrets to your stack.


A Kubernetes cluster restarts applications that fail, replaces containers when they fail, kills containers that fail the user-defined health check, and does not advertise them until they are ready to be used by clients.

How Does Kubernetes Work?

It is important for developers to plan out how all the components fit together and work together. They should also plan out how many of each component should run, and what should happen if challenges occur (such as many users logging in at the same time.) Typically, they store their containerized application components in a container registry (local or remote) and define their configuration in a text file. To deploy the application, they “apply” these configurations to Kubernetes. Its job is to evaluate and implement this configuration and maintain it until told otherwise.

1. It Analyzes the configuration and aligns its requirements with those of all other applications on the system.

2. Provides resources appropriate for running new containers (for example, some containers may require GPUs that are not present on every host).

3. It Grabs container images from the registry and starts up the new containers and helps them connect to one another and to system resources (e.g., persistent storage), so the application works as a whole

Once Kubernetes has monitored everything, it tries to fix things and adapt when real events diverge from desired states. if a container crashes, Kubernetes restarts it. if an underlying server fails, Kubernetes finds resources elsewhere to run the containers that the node was hosting. As traffic spikes to an application, Kubernetes can scale out containers to handle the additional load, in accordance with configuration rules.

Advantages of Kubernetes?

There are several important advantages to Kubernetes that have made it so popular:

1. Scalability

As the number of containers increases, Kubernetes spins up additional container instances and scales them out automatically, which is similar to how cloud-native applications scale horizontally.

2. Integration and extensibility

It supports many open source solutions complementary to it, including logging, monitoring, alerting, and more. Its community is working on a variety of open source solutions complementary to Kubernetes.

3. Portability

It is possible to run containerized applications on K8s across an array of environments, including virtual environments and bare metal. Kubernetes is supported in all major public clouds.

4. Cost efficiency

Due to its inherent resource optimization, automated scaling, and flexibility to run workloads where they are most valuable, you can control your IT spending.

5. API-based

It is built upon its REST API, which allows all its components to be programmed.

6. Simplified CI/CD

CI/CD is a DevOps practice for automating building, testing and deploying applications. Enterprises are now integrating Kubernetes and CI/CD pipelines to create scalable CI/CD pipelines.

Kubernetes and Docker

In Kubernetes, Docker can serve as an orchestration platform for running containers. When Kubernetes schedules a pod on a node, its kubelet instructs Docker to launch the specified containers. Container status is continuously collected from Docker by the kubelet, which aggregates this information in the control plane. Docker pulls containers onto the node and starts and stops them as necessary. When Kubernetes and Docker are used together, the automated system asks Docker to do those things instead of the admin doing them manually on all nodes.

Wrapping Up:

In this tutorial, you learned about Kubernetes, its advantages, use cases, and how it works. In summary, it Automates container networking needs and distributes application workloads across a Kubernetes cluster. It also allocates storage and persistent volumes to running containers, provides automatic scaling, and continuously keeps applications in the desired state, ensuring resiliency.

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What is Mongo DB and Why do We Need it?

The MongoDB document database is an open-source platform with horizontal scale-out architecture and a flexible schema for storing data. It was founded in 2007 and has gained a widespread following among developers across the globe. MongoDB databases store data as documents, not as tables of rows and columns. each record is described as a document in BSON, a binary representation of the data. In JSON format, applications can retrieve this information. MongoDB offers a replacement for traditional relational database systems that use SQL. In a relational database, data is stored in tables, rows, and columns with relationships between entities. In MongoDB, the data is stored in documents using JSON-like structures to represent and interact with data.

Mongo DB Overview:

The MongoDB database was developed in 2009 as a highly scalable, robust, and free NoSQL database. it also has a commercial version. its source code can be found on GitHub. As a versatile, flexible database, MongoDB has established itself as a popular choice for many high-profile organizations and companies, including Forbes, Facebook, Google, IBM, and Twitter. MongoDB is a non-relational database system. There are two primary types of databases: SQL (relational) and NoSQL (non-relational).
Relational databases store data arranged in columns and rows. Microsoft SQL Server Oracle and Sybase are relational database management systems (RDBMS). However, NoSQL databases store unstructured, schema-less data in multiple collections and nodes. Non-relational databases do not require fixed table structures. NoSQL databases can be scaled horizontally and support limited join queries. NoSQL stands for “Not Only SQL”.

Mongo DB Use cases

The MongoDB database is best suited for unstructured data, so it is a great choice for Big Data systems, MapReduce applications, news site forums, and social networking sites. Below are some of the use case categories that MongoDB is appropriate for:

1. Internet of Things (IoT)
2. Blog and Content Management systems
3. Catalog Management
4. E-Commerce type of product-based applications
5. High-Speed operations in the Real-time
6. If you need to maintain location data.
8. If the application design may change at any point in time.
7. In Personalizations.

When shouldn’t You use MongoDB?

Despite the fact that Mongo DB has a lot of useful applications and use cases, there are circumstances in which you shouldn’t use this database. These situations are:

1. You need ACID compliance. The ACID acronym stands for Atomicity, Consistency, Isolation, and Durability. Applications that require database-level transactions (like a banking system) must be ACID compliant. MongoDB isn’t as strong as most RDBMS systems in terms of ACID.
2. When you deal with complex transactions.
3. You work with stored procedures. Unfortunately, MongoDB has no provisions for stored procedures.
4. You don’t need a database like MongoDB if your business isn’t experiencing explosive growth and its data is consistent.

Advantages of Mongo DB

there are many benefits to using Mongo DB. In this section of the article, you will see why so many great companies like Twitter, IBM, Sony, HTC, Cisco, and so on, use this popular database:

1. It has no schema and it is a document-type database.
2. It supports field, range-based query, regular expression or regex, etc for searching the data from the stored data.
3. It is very easy to scale up or down.
4. For working temporary datasets, it uses internal memory, which is much faster than external memory.
5. MongoDB support primary and secondary index in any field.
6. It supports the replication of the database.
7. Mongo DB is utilized with a sharding mechanism to perform load balancing. By using Sharding, the database can be scaled horizontally.
8. MongoDB can be used as a file storage system which is known as a GridFS.
9. In addition to aggregation pipelines, map-reduce techniques, and single objective aggregation commands, it also provides different ways to aggregate data.
10. It can store Any file type of any size without affecting our stack.
11. MongoDB basically uses JavaScript objects in place of the procedure.
12. In addition, it supports special collection types such as TTL (Time-To-Live) for storing data that expires after a certain period of time.

MongoDB vs. Postgres

Among the main differences between MongoDB vs. PostgreSQL are their systems, architecture, and syntax. MongoDB is a document database, whereas PostgreSQL is a relational database. MongoDB has a distributed architecture, while PostgreSQL is monolithic. Postgres uses SQL, whereas MongoDB uses BSON.

What is PostgreSQL

Open source PostgreSQL is an object-relational database management system (ORDBMS) with an emphasis on extensibility and standards compliance. It is based on the SQL language and incorporates many features to store, scale, and manage the most complex data workloads safely. PostgreSQL is an ACID-compliant, transactional database management system that stores data in tabular format and uses constraints, triggers, roles, stored procedures, and views as its core components.

Postgres Advantages:

1. It is free and open source.
2. Postgres has a wide variety of community and commercial support options are available for PostgreSQL users. these include mailing lists and IRC channels.
3. It supports several languages.
4. It is highly Extensible.
5. Postgres protects data integrity.
6. It builds fault-tolerant environments.
7. Postgres has a robust access-control system
8. It supports almost all international characters.

MongoDB compared to Postgres:

Using MongoDB, users can create schemas, databases, tables, and other objects that are characterized by key-value pairs, similar to JSON objects with schemas. It is a NoSQL database that is flexible and allows users to create documents that are identified by a primary key. The MongoDB shell provides a JavaScript interface through which users can interact and perform CRUD operations. Its interface provides a JavaScript interface through which users can interact. In other words, MongoDB is a general-purpose, document-based, distributed database created for modern application developers.

In general, PostgreSQL is suitable for the situations when you need a database that is Standard compliant, transactional, ACID (Atomicity, Consistency, Isolation, Durability) compliant and has a large range of NoSQL features.

On the other hand, Mongo DB is best For real-time analytics, for when you need scalability and caching, but this database is not built for accounting applications.

Wrapping Up:

In this article, you got familiar with MongoDB, its use cases, pros and cons, limitations, and its comparison with the PostgreSQL database. In addition to being widely used in different industries and use cases, MongoDB is one of the most popular NoSQL databases. A highly versatile data management system, MongoDB enables rapid development and low downtime operations by providing powerful features such as scaling, consistency, fault tolerance, agility, and flexibility.

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What is TCP/IP and How does it Work?

TCP/IP which is the acronym for Transmission Control Protocol/Internet Protocol is a set of standardized rules that allow computers or network devices to communicate with each other. This communication can either be on the internet or on a private network like an intranet. The TCP/IP protocol suite functions as an abstraction layer between internet applications and the routing and switching fabric.

TCP/IP functionality

TCP/IP determines how data should be exchanged on the internet by providing end-to-end communications that specify how it should be broken into packets, addressed, transmitted, routed, and received at the destination. TCP/IP is designed to make networks reliable so that data cannot be easily hacked. It also has the ability to recover automatically from the failure of any device on the network.

TCP which stands for Transmission Control Protocol has its own specific function in the IP suite. TCP defines how applications can create channels of communication across a network. It also manages how a message is assembled into smaller packets before they are then transmitted over the internet and reassembled in the right order at the destination address.

IP or Internet Protocol is another important protocol of the IP suite and it defines how to address and route each packet to make sure it reaches the right destination. Each gateway computer on the network checks this IP address to determine where to forward the message.

Common TCP/IP protocols include the following:

1. HTTP (Hypertext Transfer Protocol) handles the communication between a web server and a web browser.
2. HTTPS (Hypertext Transfer Protocol Secure) handles secure communication between a web server and a web browser.
3. FTP (File Transfer Protocol) handles the transmission of files between computers.

How does TCP/IP work?

TCP/IP uses the client-server model of communication, meaning that a service is provided for a user or machine (a client), like sending a webpage, by another computer (a server) in the network. The TCP/IP suite of protocols is classified as stateless, which means each client request is considered new because it is unrelated to previous requests. Being stateless frees up network paths so they can be used continuously.
On the other hand, the transport layer itself is stateful. It transmits a single message, and its connection remains in place until all the packets in a message have been received and reassembled at the destination. The TCP/IP model differs slightly from the Open Systems Interconnection (OSI) networking model designed after it. The OSI reference model has seven layers and defines how applications can communicate over a network.

The 4 layers of the TCP/IP model

The TCP/IP functionality consists of four layers. Each of these layers has specific functionality and protocol. These layers include:

1. The application layer provides applications with standardized data exchange. Its protocols include HTTP, FTP, Post Office Protocol 3, Simple Mail Transfer Protocol, and Simple Network Management Protocol. At the application layer, the payload is the actual application data.

2. The transport layer is responsible for maintaining end-to-end communications across the network. TCP handles communications between hosts and provides flow control, multiplexing, and reliability. The transport protocols include TCP and User Datagram Protocol, which are sometimes used instead of TCP for special purposes.

3. The network layer, also called the internet layer, deals with packets and connects independent networks to transport the packets across network boundaries. The network layer protocols are IP and Internet Control Message Protocol, which are used for error reporting.

4. The physical layer, also known as the network interface layer or data link layer, consists of protocols that operate only on a link — the network component that interconnects nodes or hosts in the network. The protocols in this lowest layer include Ethernet for local area networks and Address Resolution Protocol.

Why is TCP/IP important?

TCP/IP is not controlled by a single company or authority. As a result, the IP suite can be modified easily. Moreover, it is compatible with all operating systems, so it can communicate with any other system. The IP suite is also compatible with all types of computer hardware and networks. Furthermore, TCP/IP is highly scalable and consequently, can determine the most efficient path through the network. It is widely used in current internet architecture.

Uses cases of TCP/IP

TCP/IP use cases vary in so many different ways. This protocol can be used to provide remote login over the network for interactive file transfer to deliver email, to deliver webpages over the network, and to remotely access a server host’s file system. In general, it is used to change the form of information at the time of transferring the data over a network from the concrete physical layer to the abstract application layer. It elaborates the basic protocols, or methods of communication, at each layer as data passes through.

Pros and cons of TCP/IP

The advantages of TCP/IP:

1. Helps establish a connection between different types of computers.
2. Works independently of the OS.
3. Supports many routing protocols.
4. Uses a client-server architecture that is highly scalable.
5. Can be operated independently.
6. Supports several routing protocols.
7. Is lightweight and doesn’t place unnecessary strain on a network or computer.

The disadvantages of TCP/IP:

1. Is complicated to set up and manage.
2. The transport layer does not guarantee the delivery of packets.
3. Is not easy to replace protocols in TCP/IP.
4. Does not clearly separate the concepts of services, interfaces, and protocols, so it is not suitable for describing new technologies in new networks.
5. Is especially vulnerable to a synchronization attack, which is a type of denial-of-service attack in which a bad actor uses TCP/IP.

Differences between TCP/IP and IP ?

There are numerous differences between TCP/IP and IP. For example, IP is a low-level internet protocol that facilitates data communications over the internet. Its purpose is to deliver packets of data that consist of a header, which contains routing information, such as the source and destination of the data, and the data payload itself.


IP is limited by the amount of data that it can send. The maximum size of a single IP data packet, which contains both the header and the data, is between 20 and 24 bytes long. This means that longer strings of data must be broken into multiple data packets that must be independently sent and then reorganized into the correct order after they are sent. Since IP is strictly a data send/receive protocol, there is no built-in checking that verifies whether the data packets sent were actually received.


In contrast to IP, TCP/IP is a higher-level smart communications protocol that can do more things. TCP/IP still uses IP as a means of transporting data packets, but it also connects computers, applications, webpages, and web servers. TCP understands holistically the entire streams of data that these assets require in order to operate, and it makes sure the entire volume of data needed is sent the first time. TCP also runs checks that ensure the data is delivered. As it does its work, TCP can also control the size and flow rate of data. It ensures that networks are free of any congestion that could block the receipt of data. An example is an application that wants to send a large amount of data over the internet. If the application only used IP, the data would have to be broken into multiple IP packets. This would require multiple requests to send and receive data since IP requests are issued per packet. With TCP, only a single request to send an entire data stream is needed; TCP handles the rest. Unlike IP, TCP can detect problems that arise in IP and request retransmission of any data packets that were lost. TCP can also reorganize packets so they get transmitted in the proper order, and it can minimize network congestion. TCP/IP makes data transfers over the internet easier.

Wrapping Up

In this article, you learned about TCP/IP protocol, its functionality, layers, importance, pros and cons, and difference with IP protocol (which is a lower level network protocol). Of course, there are other high-level models that are newer and work more efficiently than the TCP/IP model like the OSI, but the TCP/IP protocol is more popular and widely adopted among companies and developers. Moreover, the OSI model is not practically used for communication. Rather, it defines how applications can communicate over a network. TCP/IP, on the other hand, is widely used to establish links and network interaction.

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