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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.

Self-healing

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 WSGI and Why is it necessary?

WSGI is a specification for how a server and application communicate. Both the server interface, as well as the application interface, are specified in PEP 3333. A WSGI application (or framework or toolkit) can be stacked on any server that conforms to the WSGI specification. These applications are compatible with each other. A middleware piece must implement both sides of the WSGI interface: the application on top, and the application below. For a middleware piece to be a middleware piece, it must implement both sides of the WSGI interface, application, and server.

WSGI Overview:

There were about 14 million users on the web in 1993, and 100 websites. Pages were static at the time, but dynamic content, such as news and data, was already necessary. Rob McCool and others implemented the Common Gateway Interface (CGI) for the HTTPd web server of the National Center for Supercomputing Applications (NCSA). Since then, the number of Internet users has exploded, and dynamic websites have become ubiquitous. This was the first web server capable of serving content generated by a separate application. When learning a new language or even at the time of learning to code, developers, soon enough, want to know how to hook their code into the web.

There have been many changes since the advent of CGI. The CGI approach became impractical because it required creating a new process on each request, wasting CPU and memory. Some other low-level approaches have emerged, such as FastCGI](1996) and mod_python (2000), which provide different interfaces between Python web frameworks and the web server. The proliferation of approaches led to limitations in developers’ choices of frameworks and web servers.

As a solution to this problem, Phillip J. Eby proposed PEP-0333, the Python Web Server Gateway Interface (WSGI) in 2003. The idea was to provide a high-level, universal interface between Python applications and web servers. PEP-3333 came out in 2003 to add Python 3 support to the WSGI interface. As of today, almost all Python frameworks rely on WSGI for communication with their web servers. This is how Django, Flask, and many other popular frameworks do it.

How does WSGI work?

When a WSGI server receives a client request, passes it on to the application, and then sends the response back to the client. It does nothing else; All the gory details must be supplied by the application or middleware. WSGI spec is not needed to build applications on top of frameworks or toolkits. If the middleware is not already integrated into the framework or the framework provides some kind of wrapper to integrate those that are not, one must understand how to stack it with the application or framework.

Why Do we Need WSGI?

Python applications cannot be run on a traditional web server. Grisha Trubetskoy, a developer, designed the Apache module mod_python in the late 1990s in order to execute arbitrary Python code. For several years in the late 1990s and early 2000s, Apache configured with mod_python ran most Python web applications. However, mod_python wasn’t a standard specification, it was only an implementation that allowed Python code to run on a server. As a result, the community became aware that a consistent way to execute Python code for web applications was needed as mod_python’s development slowed and security vulnerabilities were discovered. The Python community came up with WSGI as a standard interface that modules and containers could implement. WSGI is now accepted for running Python web applications.

Purposes of WSGI:

WSGI Provides Flexibility:

In applications, developers can replace web stack components with others. For example, they can switch from Green Unicorn to uWSGI without modifying the application. PEP 3333 states that if such an API is available and widely used in Python web servers, users will be able to choose a framework and web server that suits them, while framework and server developers can concentrate on their preferred areas of specialization.

WSGI servers promote scaling:

A WSGI server is responsible for serving thousands of requests for dynamic content at once, not a framework. WSGI servers handle web server requests and decide how to forward those requests to an application framework. To scale web traffic efficiently, segregation of responsibilities is essential.

Different Implementations of WSGI:

There is a long list of WSGI implementations out there which you can find on the WSGI Read the Docs page. The following four implementations are among the most recommended and popular ones:

1. Green Unicorn

The Gunicorn web application server is an enterprise-class WSGI web server that offers a lot of functionality. It natively supports various frameworks through its adapters, making it an excellent drop-in replacement for many development servers. Gunicorn works in much the same way as Unicorn’s successful Ruby web server. Both use the pre-fork model. In essence, this means that the central [Gunicorn] master process manages workers, creates sockets, and bindings, etc.

2. uWSGI

UWSGI is gaining steam as a high-performance WSGI server implementation.

3. mod_wsgi

Mod_wsgi is an Apache HTTP Server module developed by Graham Dumpleton for hosting Python-based web applications with WSGI extensions and includes Python 2 and 3 (as of versions 2.6 and 3.2).

4. CherryPy

This framework uses the Python programming language to build object-oriented web applications. It wraps the HTTP protocol, but stays at a low level and does not offer much more than what exists in RFC 7231. There is no support for tasks like templating for output rendering or backend access in CherryPy. You can use it as a web server or launch it from any WSGI-compatible environment. You can extend the framework with filters, which are called at certain points during request/response processing.

Which Frameworks use WSGI?

Flask and Django are both popular python frameworks that implement web Applications and both of them use WSGI. There are of course other python frameworks that use WSGI, but Django and Flask are the two most common. We will have a brief introduction to both frameworks in the following.

Django

With Django, you can create secure and maintainable websites quickly and easily. The experienced developers have built it and it can handle much of the hassle of web development, so you can focus on writing your app without reinventing the wheel. The software is free and open source, has an active community, great documentation, and many free and paid support options.

Flask

This lightweight WSGI web application framework allows users to create simple and fast web applications while scaling up to complex applications with ease. Originally designed as a wrapper for Werkzeug and Jinja, Flask has gained popularity as a web application framework for Python. Developers decide which tools and libraries they want to use. There are several extensions available from the community that makes adding new functionality easy. Flask offers suggestions but does not enforce dependencies. Developers choose the tools and libraries they want to use.

Wrapping Up:

In this article, you got familiar with WSGI, what it is, why we use it, why is it important, and how to implement it. In summary, WSGI is the Web Server Gateway Interface. It is a specification that describes how a web server communicates with web applications, and how web applications can be chained together to process one request.

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Introduction to Docker and its Use Cases

Several development teams are focusing on Docker as one of their favorite container-based platforms. It is becoming increasingly popular due to its reliability, performance, and functionality. The open-source containerization software and its underlying components must therefore be understood. In this article, we will focus on Docker, containers, use cases of Docker, its advantages, and its differences from Virtual Machines.

What is Docker?

The Docker containerization platform provides a lightweight virtualized environment called a container that allows developers to develop, deploy, and manage applications. It serves primarily as a development platform for distributed applications that can operate in a variety of environments. By making the software system agnostic, developers don’t have to worry about compatibility issues. Since Docker utilizes virtualization to create containers to store apps, the concept may seem similar to virtual machines. Also, packaging apps into isolated environments (containers) makes it easier to develop, deploy, maintain, and use applications. In spite of the fact that both containers and virtual machines are isolated virtual environments used for software development, there are important differences between them. The most important difference is the Docker container’s lighter, faster, and more resource-efficient nature.

What are Containers?

A Docker container is a lightweight virtualized runtime environment that can be used to run applications. Each container contains the necessary code, tools, runtime, libraries, dependencies, and configuration files to run a specific application. They are independent of the host and from all other instances running on the host. In Docker, containers are built by running an image on the Docker Engine. As these are the most common terms, you should be aware of the difference between Docker images and Docker containers. Unlike virtual machines, containers virtualize at the application level. In this way, the OS kernel is shared with the host and an operating system is virtualized over it, so resources are spared and lightweight virtual environments can be quickly and easily configured.

Using containers, we can isolate certain kernel processes and trick them into thinking they’re the only ones running on a completely new computer. unlike virtual machines, containers can share the kernel of the operating system with only their respective binaries/libraries loaded. Thus, you don’t have to install a whole separate OS (called a guest OS) inside your host OS. You can run multiple containers inside one operating system.

What are the Benefits of Using Docker?

1. New Developers can quickly Get started With the Team’s Project

When a new developer starts to work on your product, he still has to install some local servers, set up a database, install libraries, integrate third-party software, and configure it all. How long does it take? From a few hours to many days. Even if your project has an excellent onboarding manual that explains all the steps, there is a high probability that it won’t work for every laptop and system configuration. A new developer’s onboarding is often a collaborative effort by the whole team that guides him or her through the installation of all missing parts and resolving system problems. The Docker container automates all these manual installation and configuration steps, so the developer only has to launch Docker and run a single command (docker-compose up), and that does all the work for him. No matter if he uses Docker on a macOS, Windows, or Linux computer.

2. You can Test Your App in all Environments:

You must have heard of a famous developer’s excuse “It worked on my machine”. Whether something works on your server or on the developer’s computer does not guarantee that it will work. Additionally, the software versions may not match the missing libraries or tools. Besides, there are many different computers and servers out there, and their configuration may differ in so many ways. if you do not use Docker, you have to configure them manually, which can be time-consuming and prone to error.

In order to solve this problem, Docker bundles not just the code but also all the components that need to run an application or website. These components are inside Docker containers, which are isolated and independent of the outside world. This allows them to run in a predictable and consistent manner everywhere. This means developers spend less time fixing issues and more time delivering new features.

3. No vendor Lock-in When it comes to Hosting

The Docker container is similar to the cargo container. Docker containers, just like cargo containers, are standardized, so most computers, servers, and cloud computing (such as container ships, freight trains, and trucks) can handle them. It gives you great flexibility in terms of your hosting technology and provider. You can start with a small, cheap server and scale it into a larger, more expensive one when necessary. And what’s more, you won’t be stuck with just one host.

4. Flexible scaling of your app or website

While Docker won’t make your website or web application scalable out of the box, it may be a key component of software scalability. especially if you use AWS or Google Cloud to host your website. The right containers can be launched in many copies to handle the growing number of users. In the cloud, this scaling can be automated, so if more people use your site, more containers will be launched. The same applies to downsizing, fewer users mean a smaller hosting bill.

5. Keep track of all changes made to your application components

The Docker container enables developers to easily define a programmable environment for the code to run in. This eliminates the need for written or spoken instructions to be executed by humans. No more manual installation or configuration. Docker converts all these manual processes into code, so there will be no more misunderstandings when a developer installs a library without notifying others that it is required to launch the application. An automated installation and configuration process that is automatically performed on every developer’s computer, as well as on the server. And this saves a lot of time during development.

6. Makes your application easier to compose with third-party apps

It has already been mentioned that Docker helps you bundle your code with third-party software inside closed containers. However, it also provides a vast repository (Docker Hub) where developers can find templates (called Docker Images) for creating containers for their website or web application. Using the configuration already created by the Docker community reduces the development time since no new configuration needs to be created, and the development team will save time by not starting from scratch.

Differences between Docker and Virtual Machines:

Both Docker Containers and Virtual Machines are containers that can store code and mix it with additional software, files, and configuration. At first glance, these two may seem similar. Virtual machines require a separate operating system (like Linux or Windows) to be installed inside of them. and operating systems are not the lightest pieces of software. In other words, if you have a lot of virtual machines, it will get very heavy (both in terms of disk space and computing power).

Docker containers, instead of having their own operating system, use the operating system of the computer/server where Docker is installed. In the Docker engine, computer resources can be accessed by the containers in a way that makes them feel like they have their own operating system.

Conclusion:

In this article, you got familiar with Containers, Docker, its benefits and use cases, and its differences from Virtual Machines. In summary, with Docker, you can easily build, test, and deploy applications. Docker packages software into standardized units called containers that contain libraries, system tools, code, and runtime so it can run quickly. You can deploy and scale applications in any environment with Docker and know that the code will run.

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Introduction to Redis. What is it? And Why Do we Use it?

A NoSQL database known as Redis (which stands for Remote Dictionary Serve) is an in-memory key-value data store, cache, message broker, and queue that runs quickly. This project was initiated by Salvatore Antirez Sanfilippo, the original developer. He developed a real-time web log analyzer and wanted to increase the scalability of his startup in Italy. In response to significant difficulties scaling some types of workloads using traditional database systems, he began prototyping the first proof of concept version of Redis. Github and Instagram were among the first companies to adopt this technology. Therefore, it’s no surprise that the technology has been adopted and patronized not just by large companies, but also by developers.

What is Redis?

The official Redis document describes it as an in-memory data structure store (BSD licensed) that serves as a database, cache, and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, and geospatial indexes with radius queries and streams. In short, Redis is a tool in the In-Memory Databases category of a tech stack. There are no external dependencies for Redis since it was written in ANSI C. It works on most of the POSIX systems, including BSD, Linux, and OS X. OS X and Linux are considered to be the two operating systems for which Redis has been developed and tested the most. However, Linux has been used to deploy it. Despite not being officially supported by Microsoft for the Windows builds, it does run on Solaris-derived systems such as SmartOS.

Why Do we Use Redis?

This software allows for caching. Caching is the process of storing data in temporary storage components Which are used in the future to serve data faster by storing temporary data in temporary storage components. When this happens, Redis is used. It is compatible with most major programming languages and protocols, such as Python, Java, PHP, Perl, Go, Ruby, C/C#/C++, JavaScript, and Node.js.

Use Cases of Redis:

It is common for many people to use Redis for caching data and for session storage (i.e. web sessions). Redis has a lot of uses that can be applied and is useful for any situation, especially when it comes to speed and scalability, it is easy to scale up and down. Redis is commonly used for session caching, page caching, message queue applications, leaderboards, and many other tasks by experienced users or companies that have been using it for a long time.

Redis is also popular among large cloud companies offering fully-managed databases or DBaaS. Among the companies using Redis are Twitter, Amazon Web Services, Microsoft, Alibaba, and Microsoft Azure Cache for Redis in Azure, and Amazon Web Services is offering Elasticache for Redis. Use cases of Redis to describe the types of scenarios you can apply, implement, and integrate with your business applications and environment. As the Redis delivers super-fast performance. it is frequently used for real-time applications. we’ll examine each of these where it is ideally applicable.

Caching

Basically, caching is the process of storing data in a temporary storage location to allow it to be accessed faster in the future. the cache is a temporary storage location for data. In order to reduce latency access with disks or SSDs, increase throughput, and ease database and application load, Redis is a good choice for implementing an in-memory cache. Caching solutions with Redis include web page caching, database query results caching, persistent session caching, and caching of frequently used objects like images, files, and metadata.

Session Store

As a user interacts with applications such as a website or a game, the session state captures the current state of user interaction with the application. As long as a user is logged in to the system, a typical web application keeps a session for each connected user. An application uses a session state to remember user details, login credentials, personalization information, recent actions, shopping cart information, and more.

Each user interaction must be handled without disrupting the user experience by reading and writing session data. therefore, no round trips to the main database should be required during the live session. when a user is disconnected from the application, the session state life cycle ends. some data will remain in the database after the session ends, but transient information can be discarded after the session ends.

Messaging Applications

As a result of its support for Pub/Sub, pattern matching, and a range of data structures including lists, sorted sets, and hashes. Redis has also been able to support high-performance chat rooms, real-time comment streams, and social media feeds.

Game Applications

Real-time leaderboards and scoreboards are often built using Redis by game developers. To implement this use case, a Redis Sorted Set data structure can be used, which provides uniqueness of elements while keeping the list sorted by the users’ scores (points) associated with the key. Update the user’s score whenever it changes. Sorted Sets can also be used to handle time-series data by using timestamps for scoring. A popular technology for implementing session stores, Redis has a very high throughput, so it is widely used for implementing session stores. As well as the use cases mentioned above, Redis is used in many other ways in many different ways in machine learning, real-time analysis, media streaming, etc.

Redis Pros and Cons:

Pros

1. It’s Faster than nearly all caching we know.
2. It is Simple user friendly due to its easy setup.
3. It supports almost all data structures.
4. It allows storing key and value pairs as large as 512 MB.
5. It has its own hashing mechanism called Redis Hashing.
6. Zero downtime or performance impact while scaling up or down.
7. It is open source and stable.

Cons

1. Due to the fact that the data is sharded based on the hash-slots assigned to each Master, the data to be written into those slots will not be preserved if the Master holding those slots is unavailable.
2. Clients that connect to the Redis cluster need to know the cluster topology, causing extra configuration work.
3. Failover does not happen unless the master has at least one slave.
4. It requires a huge RAM because it is in memory so are not supposed to use it on RAM servers.

How Does Redis Store Data?

There are 5 data types for storage in Redis:

1. String: a text value
2. Hash: A hash table of string keys and values
3. List: A list of string values
4. Set: A non-repeating list of string values
5. Sorted Set: A non-repeating list of string values ordered by a score value

Data type operations are supported in Redis, so you do not have to load an entire data object at an application level, modify it and then restore the modified object. The Redis memory management mechanism is encapsulated, resulting in a much simpler approach than Memcached’s Slab mechanism. Redis supports keys and values of up to 512MB in size. this limit applies to aggregate data types (Lists and Sets).

Conclusion

In this article, you learned about Redis, What it is, why we use it and how we do it. Moreover, you learned about the pros and cons of using Redis in addition to its use cases. In summary, Redis (Remote Dictionary Server) is an in-memory data structure store that is used as a distributed, in-memory key-value database, cache, and message broker, with optional durability. In addition to strings, lists, maps, sets, sorted sets, HyperLogLogs, bitmaps, streams, and spatial indexes, Redis supports other types of abstract data structures as well.

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What is an API Gateway? And Why is it Important?

API gateways are tools that allow you to manage APIs between a client and a collection of backend services. API gateways act as reverse proxies to collect API calls from clients, aggregate the services required to fulfill them, and return the appropriate results. An API gateway sits in front of a set of APIs or microservices to coordinate data requests and delivery. In addition to acting as a single entry point and standardizing interactions between apps, data, and services, API gateways can also support and manage API usage by performing a variety of other functions, from authentication to rate limits to analytics.

What is an API Gateway?

Typically, API gateways handle requests by invoking multiple microservices and aggregating the results, so that the best path is determined. they route all API calls from clients to the appropriate microservices through request routing, composition, and protocol translation. The API gateway allows mobile clients to retrieve all product details with a single request using an API gateway. It can translate between web protocols and web-unfriendly protocols used internally. Invoking various services, such as product information and reviews, and combining the results.

One of the components of an API management system is an API gateway. It intercepts all incoming requests and forwards them to the API management system, which handles a variety of necessary tasks. The API gateway differs from implementation to implementation in terms of what it does. An example of a common API gateway function would be authentication, routing, rate limiting, billing, monitoring, analytics, policies, alerts, and security.

Why do we use an API gateway?

There are many enterprise APIs deployed via API gateways. these gateways handle common tasks across a system of API services, including user authentication, rate limiting, and statistics. In its simplest form, an API service accepts a remote request and returns a response. But real life is never that simple. When you host large-scale APIs, consider all your concerns. Those concerns are:

1. You use authentication and rate limiting to prevent API abuse.
2. You want to measure how people use your APIs, so you include analytics and monitoring.
3. If you intend to monetize your APIs, you should connect to a billing system.
4. Microservice architectures may involve calling dozens of different applications.
5. Over time, you’ll add some API services and retire others, but your clients will still want to find all your services together.

With all of this complexity, your challenge is to provide your clients with a simple and reliable experience. An API gateway lets your client interface be decoupled from your backend implementation. When a client makes a request, the API gateway breaks it into multiple requests, routes them to the right places, produces a response, and keeps track of everything.

How does an API gateway work?

Using APIs, separate applications can communicate and exchange data inside and outside of a business. API gateways provide a focal point and standard interface for these activities. As well as receiving requests from internal and external sources, it packages multiple requests, routes them to the appropriate API or APIs, and receives and delivers responses to the user or device who made the request.

An API gateway is also essential to a microservices-based architecture, where data requests are invoked by a variety of applications and services using multiple, disparate APIs. API gateways perform similar functions here: Provide a single point of entry for a defined group of microservices, and apply policies to determine their availability and behavior.

Additionally, API gateways handle the tasks that are involved with microservices and APIs. These task are:

1. API Security
2. service discovery
3. basic business logic
4. authentication and security policy enforcements
5. stabilization and load balancing
6. cache management
7. monitoring, logging and analytics
8. API Transformation
9. Rate-Limiting
10. protocol translation

Building Microservices Using an API Gateway:

Using an API gateway is a good idea for most microservices-based applications since it acts as the single entry point for the system. The API gateway is responsible for request routing, composition, and protocol translation, and can streamline the system. with an API gateway, each client gets a customized API. Depending on the request, the API gateway routes it to the appropriate backend service, while for others it invokes multiple backend services and aggregates the results. if there are any failures in the backend services, the API gateway can return cached or default data to mask them.

Pros and Cons of API Gateways:

In addition to standardizing and centralizing the delivery of services via APIs or microservices, API gateways also help secure and organize API-based integrations in a variety of ways. The followings are the benefits of an API gateway:

1. Simplifies service delivery:

With API gateways, multiple API calls can be combined to request and retrieve data, which reduces traffic and reduces requests. This benefits mobile applications and streamlines the API process.

2. Provides flexibility:

Developers can customize API gateways to encapsulate the internal structure of an application in a variety of ways, to invoke and aggregate multiple back-end services.

3. Extends legacy applications:

As an alternative to a broader and more complicated (and expensive) migration, enterprises can leverage API gateways to work with legacy applications and even extend their functionality.

4. Contributes to monitoring and observability:

For monitoring API activity, most organizations use specific tools, but an API gateway can help. Monitoring failure events can be pinpointed using API gateway logs.

In spite of all the benefits mentioned above, there are some challenges that teams might face with an API gateway:

1. Reliability and resilience:

Enterprises must be wary of adding features that adversely affect performance, especially since API gateways represent an extra step between customers and applications or data. Any impairment or hindrance to the API gateway’s functionality may result in the failure of associated services.

2. Security:

If the API gateway is compromised, a serious security problem could occur across a wide range of an enterprise’s business areas. External-facing interfaces and internal APIs and systems should be separated carefully, and authentication and authorization parameters should be defined.

3. Complexity and dependencies:

Every time an API or microservice is added, changed or deleted, developers must update the API gateway. this is especially challenging in an environment where a few applications can become hundreds of microservices. It is possible to mitigate these issues by creating and adhering to API and microservice design rules.

API Gateways vs API proxy:

There are also API proxies, which are basically subsets of API gateways that provide minimal processing for API requests as an alternative to API gateways. API proxy handles communication, including protocol translation, between specific software platforms, such as proxy endpoints and target APIs. However, API gateways usually provide better performance analysis and monitoring capabilities. in addition, they can control the flow of traffic between sending and receiving points.

How an API gateway supports DevOps and serverless environments:

The most common way microservices communicate in organizations that follow a DevOps approach is through APIs. microservices are used to build apps fast and iteratively.
Moreover, modern cloud development, including the serverless model, relies on APIs for provisioning infrastructure. you can deploy serverless functions and manage them with an API gateway. In general, APIs become increasingly important as integration and interconnectivity become increasingly important. As API complexity increases and usage increases, API gateways become increasingly valuable.

Conclusion

In this article, you have got familiar with API gateways, what they are, their use cases, pros and cons, and their implementation. Essentially, API gateways are API proxies that sit between API providers and API consumers; API gateways are façades that provide API interfaces for complex subsystems. The API gateway acts as a protector, enforcing security and ensuring scalability and high availability of defined back-end APIs and microservices (both internal and external). Typically, The gateway sits in front of an API and serves as its single-entry point. API gateways combine API requests from clients, determine which services are needed, and provide a seamless user experience.

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A Complete Guide to Microservice Architecture

An architecture based on microservices consists of a series of small, autonomous services. Each service is self-contained and should implement a single business capability within a bounded context. a bound context is a natural division within a business and provides a definite boundary within which a domain model can be applied. In a microservice architecture, services are loosely coupled and can be developed, deployed, and maintained independently. These services each handle a discrete task and can communicate with other services using simple APIs to solve larger complex business problems. In this article, we will take a close look at the different aspects of microservices, what they are, What are the challenges and benefits of using them and so on.

What are Microservices?

A microservice is a small, independent, and loosely coupled service. It can be written and maintained by just one or two developers. Each service has a separate codebase, which can be managed by a small team. There is no need to rebuild and redeploy the entire application when updating an existing service. Services are responsible for persisting their own data.Data persistence is handled by a separate data layer in contrast to the traditional model. services communicate with one another via well-defined APIs. internal implementation details of each service are hidden from other services. polyglot programming is supported. Services do not need to share the same technology stacks, libraries, or frameworks, for example.

The Pros and Cons of Microservices:

It is possible to build the constituent services by one or more small teams from the beginning separated by service boundaries, making it easier to scale up development efforts in the future. Once developed, these services can also be deployed independently of each other, making it easy to identify hot services and scale them independently from the whole application.

Another benefit of microservices is also improved fault isolation, which means that the whole application does not necessarily stop working in the event of an error in one service. if the error is fixed, a smaller version of the application could be deployed instead of a whole app being re-deployed. One of the advantages of microservices architecture is that you can choose which technology stack (programming languages, databases, etc.) is best suited to the required functionality (service) instead of having to use a more standardized, one-size-fits-all approach.

Pros:

Easier Debugging:

Managing bug fixes and feature releases is easier with microservices because they are deployed independently. you can update a service without redeploying the entire application, and you can roll back an update if something goes wrong. When a bug is discovered in a traditional application, it can stall the entire release process. new features may be delayed while a bug fix is integrated, tested, and published.

Smaller teams are needed:

It is important to use microservices that are small enough to be built, tested, and deployed by a single team. Small teams are more agile than large teams because of slower communication, increased management overhead, and diminished agility.

Small code base:

It is easy for monolithic applications to become tangled over time due to a high number of code dependencies. adding new features requires touching a lot of code. Adding new features is easier with a microservices architecture because it does not share code or data stores.

Scalability:

It is possible to scale out services independently, allowing you to scale out subsystems requiring more resources without scaling out the entire application. with orchestrators like Kubernetes and Service Fabric, you can load more services onto a single host, which allows for better resource utilization.

Data isolation:

The process of performing schema updates is much simpler, because only one microservice is affected. Schemas updates can be challenging in a monolithic application because different components of the application may all interact with the same information, making any changes to it risky.

Variety of Options:

Teams can choose any technology that fits the need of their service. For instance they can choose MySQL or MongoDB for the database, with Django and Python, Docker, Redis and so on. They have the option of choosing the framework, language, database and the kind of tools necessary for their service.

Fault Isolation:

Microservices can become unavailable, but the entire application won’t go down as long as any upstream microservices can handle faults correctly (for example, by implementing circuit breaking).

Cons:

With every benefit comes a challenge and every opportunity creates a threat. We have the same story for microservices.

Testing and Development:

It requires a different approach to writing a small service that relies on other dependent services than it takes to write a traditional monolithic or layered application. Existing tools are not always designed to deal with service dependencies. Refactoring across service boundaries can be challenging. Testing service dependencies can also be challenging, especially when the application is rapidly evolving.

Issues of Decentrlization:

Decentralized microservices have many advantages, but they can also cause problems. the application may become difficult to maintain if you use so many different languages and frameworks. Standardizing project-wide functionality without overly restricting teams’ flexibility may be helpful. this is especially true for cross-cutting functions like logging.

Network congestion and latency:

There will be more interservice communication if there are many small, granular services. Furthermore, if the chain of service dependencies becomes too long (service A calls service B, which then calls service C.), the increased latency can become a problem. The design of APIs must be carefully considered. avoid overly chatty APIs, consider serialization formats, and find ways to use asynchronous communication methods like queue-based load levels.

Data integrity:

Due to each microservice being responsible for its own data persistence, data consistency can be a challenge. Embrace eventual consistency when possible.

Management:

In addition to mature DevOps practices, microservices require correlated logging across services. To log a single user operation, multiple service calls must be correlated.

Versioning:

It is possible for multiple services to be updated at any given time, so if you don’t carefully design things, you may experience problems with forward compatibility and/or backward compatibility.

Various Skill Set:

Since any microservice require various talents, it is important to determine whether the team is skilled and experienced enough to handle microservices.

Microservice Use Cases:

A microservice architecture is built using Java, especially Spring Boot, to speed up application development. microservice architectures are often compared with service-oriented architectures. they both have the same objective, which is to separate monolithic applications into smaller components, but they have different approaches. Here are some microservices architecture examples:

Website migration:

It is possible to migrate a monolithic website to a microservices platform based on cloud computing and containers.

Media content:

Object storage systems offer scalable storage for images and videos, and they can be served directly to web or mobile devices using a microservices architecture.

Transactions and invoices:

Despite not being able to process payments, orders can be processed independently, so payments can continue to be accepted even if invoicing does not work.

Data processing:

Existing modular data processing services can be extended to the cloud with the help of a microservices platform.

Conclusion

In this article, you learned about Microservices what they, their architecture, design, implementation, benefits, challenges, and use cases. Microservices are so common these days and companies and startups are hiring developers with different expertise who can handle a part of the microservice development. These are of course various parts with their own specific skill set that requires a team of developers.

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What is a Web Socket API?

A WebSocket API is a modern technology that can establish a two-way interactive communication session between a user’s browser and a server. By using this API, you can send messages to a server and receive event-driven responses without polling the server. Most commonly, WebSocket is a duplex protocol that is used in client-server communications. Client-server communication is bidirectional, which means it goes back and forth between the client and the server.

What is a Web Socket?

A WebSocket is a computer communications protocol that provides full-duplex communication channels over a TCP connection. Through the use of the WebSocket, the connection lasts until one party decides to end it. A connection that is broken at one end prevents the other party from communicating with the first party. To initiate a connection, WebSocket needs HTTP support. When it comes to perfect streaming of data and other unsynchronized traffic, it serves as the spine for advanced web application development.

In contrast to half-duplex alternatives such as HTTP polling, WebSockets deliver real-time data transfer from and to a web server with low overhead. Messages can be passed back and forth while maintaining the connection, as the server has a standardized way to send content to the client without being requested by the client first. In this way, The client and server can have an ongoing two-way conversation. For the environments where non-web Internet connections are blocked using a firewall, communications are usually done over TCP port number 443 (or 80 for unsecured connections). WS (WebSocket) and WSS (WebSocket Secure) are two new uniform resource identifiers (URIs) that identify unencrypted and encrypted connections, respectively, in the WebSocket protocol specification. Aside from the scheme name and fragment (i.e. # is not supported), all other URI components follow URI generic syntax.

When do we Need a Web Socket API?

To maximize the potential of WebSockets, one must be fully aware of their utility and avoid bad scenarios to take full advantage of them. The followings are the use cases of the web socket:

1‍. Developing a real-time trading web application:

WebSocket is most commonly used in real-time application development, allowing the client to view data continuously. Due to the continuous transmission of this data by the backend server, WebSocket allows this data to be transmitted or pushed continuously in the already open connection. With WebSockets, data is transmitted quickly and the performance of the application is boosted. A real-life example of such a WebSocket utility is in the bitcoin trading website. WebSockets play an important role in data transfer between a backend server and a client.

2.‍ Developing Messaging Apps:

For operations such as one-time exchanges and publishing/broadcasting messages, chat application developers use WebSocket. Communication becomes simple and quick when WebSocket connections are used for sending and receiving messages.

3.‍ Game Development:

The server must receive the data unremittingly during application development, without requesting UI updates. An application using WebSockets can achieve this without disrupting its UI.

Don’t forget to keep your operational hassles at bay by knowing the cases where WebSocket should not be used, now that you know where it should not be used. If old data fetching is needed or if data is needed only once, then WebSocket shouldn’t be used. Instead, HTTP protocols should be used in these circumstances.

Web Socket Protocol

In WebSocket protocol, various discrete chunks of data are carried out with each data chuck; the protocol also implements various frame types, portions of data, and payload lengths to ensure its proper functioning. To comprehend WebSocket protocol in detail, one must understand its building blocks. the foremost bits are listed below. A WebSocket’s Fin Bit is the fundamental bit. it is automatically generated when a connection starts. the RSV1, RSV2, and RSV3 bits are a bit reserved for future opportunities. ‍‍The opcode consists of a number that describes how the payload data of a specific frame is understood. The most common opcode values are 0x00, 0x0, 0x02, 0x0a, 0x08, and so on.
A mask bit is activated when one bit is set to 1. For all the payload data, WebSocket requires that the client select a random key. A masking key, when combined with payload data, assists in XORing payload data; in addition to preventing cache misinterpretation or cache poisoning, masking is important from the application API security perspective. Let’s understand its crucial components in detail now:

Payload len

Describes the total length of the encoded payload data in WebSocket; Payload len is displayed when the encoded data length does not exceed 126 bytes; Once the payload data length exceeds 126 bytes, additional fields are displayed.

Masking-key

Client frames are masked with a 32-bit value. When the mask bit is 1, the masking key appears. when it’s 0, the masking key doesn’t appear.

Payload data

A payload is any kind of data related to an application or extension. This data is used during the early handshakes between the client and server. ‍

Web Socket API vs RESTful API

RESTful API and Web Socket API can be compared in so many different ways. RESTful API is stateless and thus we have no data storage whereas web socket API is stateful and data can be stored. RESTful API is one directional while the web socket API is bi-directional. Moreover, REST API follows the request-response model, whereas the Web socket API uses the Full Duplex model. Furthermore, HTTP request in REST API contains headers like head section, and title section. On the other hand, Web Socket API has no overhead and it is suitable for real-time applications. A new TCP connection will be set up for each HTTP request in a REST API, whereas in the Web Socket API, Only a single TCP connection is enough. To retrieve data in a RESTful API, it all depends upon the HTTP methods that are being used. While, in the web socket API, it depends upon the IP address and port number to retrieve the data. More to add, Web socket API is much quicker than the REST API.

Differences between Websocket and HTTP:

Due to the fact that HTTP and WebSocket are both used for application communication, people often get confused and find it difficult to decide which to use. Take a look at the below-mentioned text and gain a better understanding of HTTP and WebSocket. As already mentioned, WebSocket is a bidirectional and framed protocol. whereas HTTP is a unidirectional protocol that acts on top of TCP. Due to WebSocket’s capability to transmit data continuously, it’s primarily used for developing real-time applications. HTTP, however, is stateless and can be used to build RESTful and SOAP applications. WebSocket is a protocol that allows communication at both ends, making it a faster protocol. HTTP, on the other hand, is a stateless protocol that is used to develop RESTful and SOAP applications. Soap can still be implemented via HTTP, but REST is widely used. HTTP must construct separate connections for separate requests. once the request is completed, the connection automatically breaks. WebSocket uses a unified TCP connection, which must be terminated by one party. Until it happens, the connection remains active.

How do Web Socket APIs work?

For a quick overview, WebSocket handshakes begin with WS or WSS, which are equivalent to HTTP or HTTPS, respectively. Using this scheme, both servers and clients are expected to follow the standard WebSocket connection protocol. A WebSocket connection is established by upgrading the HTTP request, which includes headers such as Connection: Upgrade, Upgrade WebSocket, Sec-WebSocket-Key, etc.

Conclusion

In this article, you learned about all the details of web socket API. What it is, How it works, its differences with HTTP and REST API, and its use cases. Web Socket API is very useful when it comes to an interactive and dynamic application that needs a quick response to the client. Examples of this kind of application could be in designing web-based games, trading websites, chat applications, and so on.

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What is a Linux server? And Why do we Use it?

Linux servers are widely used today and considered among the most popular due to their stability, security, and flexibility, which outperform standard Windows servers. These servers are built on the Linux operating system. And as these operating systems are open-source, users benefit from a strong community of resources and advocates. But that is not the only reason why these servers are so popular, they are also designed to handle more intense storage and operational needs of larger organizations and their software. In summary, Linux servers offer businesses a low-cost option for delivering content, apps and services to their clients and at the same time, they are efficient, standard, and secure.

What is a Linux Server?

A Linux server is a variant of the Linux operating system whose major benefit of using compared to closed-source software like Windows is that the former is fully open-source. This helps keeps setup and maintenance costs low, as even many of the proprietary variants of the standard Linux OS (such as Debian, CentOS, Ubuntu, and Red Hat) give users significant flexibility in terms of set up, operation, and maintenance of their servers.
In addition to that, Linux Servers are generally lighter to run on both physical and cloud servers because they don’t require a graphics interface. Contrary to Windows, most Linux variants are fully command-line based, making it a lightweight solution that prioritizes functionality and optimized performance over ease of use.
Another benefit of a Linux server includes the ability to maintain almost 100% uptime as most servers don’t need to be taken offline to apply updates or correct errors. Moreover, Linux is excellent at multitasking management, allowing it to handle multiple applications at the same time.

What Are the Use Cases of Linux Servers?

Linux servers are some of the most popular around the world for a number of reasons. Unlike Windows and other proprietary software, Linux is significantly more affordable and gives you more control over how to configure your servers to get started. This includes the ability to handle multiple applications on the same server and at the same time without any downtime. Some of the major use cases of the Linux servers are as follows:

1. Because of the reduced resource requirements for Linux servers, you can theoretically manage a variety of tools from a single location including BI tools, analytics, and operations applications.
2. Additionally, it’s an excellent tool for software developers and even IT teams as Linux is famously known for the degree of control it delivers to users.
3. Linux gives IT staff full root access to their servers, allowing teams to set everything from the most basic parameters to more complex permission systems that limit overlap and reduce the need for hands-on management.
4. For the organizations that develop SaaS tools or live applications, Linux has got 0% downtime, stability and efficiency means that if properly configured, it can generally continue operating without any interruption until it is manually shut down or experiences a hardware failure.

What are the Pros and Cons of Linux Web Servers

Pros:

1. Free of charge.
2. Administrators benefit from the freedoms offered by the system’s administration.
3. Supports cooperative work, without normal users being able to damage the program’s core.
4. Rarely the target of cybercriminals.
5. Rarely experiences security errors, and even so they can be easily dealt with.
6. Few demands on your hardware.
7. Integrated remote function for remote administration.

Cons:

1. Complex operation
2. Some third-party programs can only be installed by the administrator
3. Porting for Linux distributions are not the focus of many hardware and software engineers
4. The update process can sometimes be very complex
5. Not all versions come with long-term support
6. Several professional programs do not work with Linux

What are the Linux server distributions?

There are several distributions for the Linux servers just as there are several different ones for the Linux Operating systems. But you need to notice that not all the variants of Linux Operating systems can be used as a server. For instance, Linux Mint is one of the popular and user-friendly variants of the Linux operating systems, but it cannot be used as a Linux server and it is not also recommended to use Ubuntu servers on it for various security reasons.

Some of the Linux server distributions are as follows:

1. Ubuntu Server: Best Linux server distribution for scalability.
2. Debian: Great Linux server distro with multi-architectural support.
3. OpenSUSE: Best Linux server variant for long-term support.
4. Fedora Server: Best Linux server distribution for fast-moving tech adoption.
5. Fedora CoreOS.
6. Red Hat Enterprise Linux (RHEL).
7. CentOS.

Linux Servers in Comparison with Windows Servers:

Linux and Windows servers can be compared from several points of view. In terms of cost, Linux servers are much more cost-efficient compared to windows which requires purchasing a license. If ease of use matters to you more than anything else, then windows is certainly a better option as it has a user interface whereas Linux servers operate with the command-line interface. In terms of remote access, on Windows terminal server/client needs to be installed and configured. On the other hand, on Linux OS there is already an existing integrated solution (terminal and shell). From the hardware support point of view, on Windows, New hardware is generally included on Windows systems, whereas hardware drivers for Linux distributions are usually only available later. In terms of security, Windows is very prone to user errors; an integrated interface is seen as a potential point of attack. On the other hand, on Linux OS, security gaps or breaches are handled quickly. However, Regular users have no access to basic system settings.

Pros and Cons of Windows Web Servers:

Pros:

1. Beginner-friendly, intuitive operations through a graphic user interface.
2. Drivers for up-to-date hardware are quickly and easily available.
3. Supports a large number of third-party applications.
4. Easy and optional automatized system updates.
5. Possible to solve technical problems via system recovery.
6. Guaranteed long-term support.
7. Compatible with exclusive and popular Microsoft programs like Sharepoint or Exchange.

Cons:

1. High licensing costs, which increase with each user.
2. Often security-related errors.
3. Vulnerable to malware.
4. Resource intensive (particularly due to mandatory GUIs).
5. Large user error potential.
6. Not suitable as a multi-user system.
7. The way the proprietary system works is not completely disclosed.

Wrapping Up

In this article, you learned about Linux Servers, What they are, where they are used, their pros and cons, their different distributions, and their comparison with Windows servers. Most IT pros and companies these days decide to use Linux servers over Microsoft Windows for various reasons. The most important of which is the fact that Linux servers are more cost-efficient and secure, and they have nearly zero percent downtime which helps the companies have their several online applications up and running even at the time of updating. However, we cannot say that Linux servers are 100 percent preferred over windows servers. It is totally up to the IT professionals to decide what kind of server is the most appropriate one for their use case.

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How do RESTful APIs work? An Insightful Guide

RESTful APIs are the kind of APIs that follow the constraints of a REST architectural style. We have covered a full article on the background architecture of this kind of API, its pros and cons, and its principles. This article focuses mainly on the way the REStful APIs work, client requests, and server responses in these APIs. If you want to get familiar with the way these APIs work and then use different frameworks, follow along with the article to get familiar with the backbone architecture of a RESTful API.

How do RESTful APIs work?

Just the same as browsing the internet, in a RESTful API, The client contacts the server by using the API when it requires a resource. The API developers explain how the client should use the REST API in the server application API documentation. The process that happens in RESTful API, goes like this. First, The client sends a request to the server and writes the request in a format that has been mentioned in the documentation, so that the server can understand. Then, the server confirms if the client has the right to make a request by authenticating him or her. Afterward, the server receives and processes the request internally. And finally, it returns a response containing the request acceptance or rejection and if the request has been accepted, it also returns what the client has requested.

What does the client request look like in a RESTful API?

All the RESTful API requests need to contain the following three main components:
1. URI
2. Method
3. HTTP Headers

What is URI? And how is it used in a client request?

URI is the acronym for Unique Resource Identifier. The server identifies each resource with a URI. In REST services, the server typically performs resource identification by using a URL (an acronym for Uniform Resource Locator). The URL specifies the path to the resource. A URL is similar to the website address that you enter into your browser to visit any webpage. The URL is also called the request endpoint and clearly specifies to the server what the client requires.

Method

RESTful APIs are often implemented using the HTTP (Hypertext Transfer Protocol) methods. These methods do a certain action on the server by telling it what it needs to do to the server. The followings are the four HTTP common methods that is also used in a RESTful API:

1. GET:

Clients use GET to access resources that are located at the specified URL on the server. They can cache GET requests and send parameters in the RESTful API request to instruct the server to filter data before sending. By using the GET request, the client queries the necessary items from a database.

2. POST:

Clients use the POST request to send data to the database. They include the data representation with the request. Sending the same POST request multiple times has the side effect of creating the same resource multiple times.

3. PUT:

Clients use PUT to update existing resources on the server. Unlike POST, sending the same PUT request multiple times in a RESTful web service gives the same result and it does not create new resources.

4. DELETE:

Clients use the DELETE request to remove the resource. A DELETE request can change the server state. However, if the user does not have appropriate authentication, the request fails.

HTTP headers

Request headers are the metadata exchanged between the client and server. For instance, the request header indicates the format of the request and response, provides information about request status, and so on.

DATA

REST API requests might include data for the POST, PUT, and other HTTP methods to work successfully.

Parameters

RESTful API requests can include parameters that give the server more details about what needs to be done. The following are some different types of parameters:
Path parameters that specify URL details.
Query parameters that request more information about the resource.
Cookie parameters that authenticate clients quickly.

RESTful API authentication methods?

A RESTful web service must authenticate requests before it can send a response. Authentication is the process of verifying identity. For example, you can prove your identity by showing an ID card or driver’s license. Similarly, RESTful service clients must prove their identity to the server to establish trust.
RESTful API has four common authentication methods:

HTTP authentication

HTTP defines some authentication schemes that you can use directly when you are implementing REST API. The following are two of these schemes:

Basic authentication

In basic authentication, the client sends the user name and password in the request header. It encodes them with base64, which is an encoding technique that converts the pair into a set of 64 characters for safe transmission.

Bearer authentication

The term bearer authentication refers to the process of giving access control to the token bearer. The bearer token is typically an encrypted string of characters that the server generates in response to a login request. The client sends the token in the request headers to access resources.

API keys

API keys are another option for REST API authentication. In this approach, the server assigns a unique generated value to a first-time client. Whenever the client tries to access resources, it uses the unique API key to verify itself. API keys are less secure because the client has to transmit the key, which makes it vulnerable to network theft.

OAuth

OAuth combines passwords and tokens for highly secure login access to any system. The server first requests a password and then asks for an additional token to complete the authorization process. It can check the token at any time and also over time with a specific scope and longevity.

What does the RESTful API server response contain?

REST principles require the server response to contain the following main components:

Status line

The status line contains a three-digit status code that communicates request success or failure. For instance, 2XX codes indicate success, but 4XX and 5XX codes indicate errors. 3XX codes indicate URL redirection.
The following are some common status codes:
200: Generic success response
201: POST method success response
400: Incorrect request that the server cannot process
404: Resource not found
Message body

Message body

The response body contains the resource representation. The server selects an appropriate representation format based on what the request headers contain. Clients can request information in XML or JSON formats, which define how the data is written in plain text. For example, if the client requests the name and age of a person named John, the server returns a JSON representation as follows:
‘{“name”:”Mohamad”, “age”:27}’

Headers

The response also contains headers or metadata about the response. They give more context about the response and include information such as the server, encoding, date, and content type.

Conclusion

In this article, you learned about the way the RESTful APIs work, client requests, and server responses in these APIs. By knowing the way the RESTful API works, you can use any kind of framework or language to write a microservice or an API using the REST architecture. Flask, Django, PHP, or any other kind of language or framework or micro-framework can help you create this kind of API. One of the most popular and simple applications created using the RESTful API is CRUD (Create, Read, Update, Delete) application and it can be used for creating a user database or a website or a web application.

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Getting Started with Nginx on Linux: a Complete Tutorial

Nginx

Nginx pronounced Engine-Ex, is a popular and open-source, lightweight, and high-performance web server software that also acts as a reverse proxy, load balancer, mail proxy, and HTTP cache. Nginx is easy to configure in order to serve static web content or to act as a proxy server.It can be deployed to also serve dynamic content on the network using FastCGI, SCGI handlers for scripts, WSGI application servers or Phusion Passenger modules, and it can serve as a software load balancer. Nginx uses an asynchronous event-driven approach, rather than threads, to handle requests. Nginx’s modular event-driven architecture can provide predictable performance under high loads.
In this tutorial, we are going to get started with Nginx on Linux and use the terminal commands to install and configure a test on it. You will get familiar with all the codes and commands for setting Nginx up and running on your operating system.

What you need to get started:

1. This tutorial is based on Linux. If you are working with Ubuntu 20.04 Linux or Linux Mint, or any other OS of the Linux family, you have a suitable operating system for the following tutorial.
2. A user account with sudo or root privileges.
3. Access to a terminal window/command line

Getting Started with Nginx

1. Installation

First off, you need to update software repositories. This helps make sure that the latest updates and patches are installed. Open a terminal window and enter the following: sudo apt-get update Now, to install Nginx from Ubuntu repository, enter the following command in the terminal: sudo apt-get install nginx If you are on Fedora, you should instead enter this command to install Nginx. sudo dnf install nginx And if you are on CentOS or RHEL, the installation is done using this command: sudo yum install epel-release && yum install nginx finally, we test the installation success by entering: nginx -v If the installation has been successful, You should get a result like this: nginx version: nginx/1.18.0 (Ubuntu)

2. Controlling the Nginx Service

Next, we should get familiar with the controlling commands. Using these commands, you will be able to start, enable, stop and disable the Nginx. First off, we should check the status of Nginx service. To do so, you can use the following command: sudo systemctl status nginx And you can see the result:

As you can it is activated and up and running. If it is not activated, you can first start by entering this command in the terminal: sudo systemctl start nginx And then, you will be able to enable it using the following command: sudo systemctl enable nginx If you want to stop the Nginx web service, you can first stop it: sudo systemctl stop nginx And then disable it: sudo systemctl disable nginx Also, if you want to reload the Nginx web service, you can use the following command: sudo systemctl reload nginx And for a hard restart, there is a command as below: sudo systemctl restart nginx

3. UnComplicated Firewall Commands:

Nginx needs access through the system’s firewall. To do this, Nginx installs a set of profiles for the Ubuntu default ufw (Uncomplicated Firewall). To display the available Nginx profiles use this command: sudo ufw app list And you can see the result. Neglect the results other than that of Nginx.

To get Nginx access through the default Ubuntu firewall, enter the following: sudo ufw allow 'nginx http' Then you need to refresh the firewall settings by entering: sudo ufw reload For https traffic, enter: sudo ufw allow 'nginx https' And for both you can use: sudo ufw allow 'nginx full'

4. Running a Test

To begin running a test, you should first make sure that the Nginx service is running, by checking the status as mentioned earlier. Open a web browser, and enter the following web address: http://127.0.0.1 And you should be able to see the following result containing a page with a welcome statement.

Now, if the system does not have a graphical interface, the Nginx Welcome page can be loaded in the terminal using curl: sudo apt-get install curl By entering the following command, you should be able to see the Welcome page contents in the terminal: curl 127.0.0.1 And the result is as expected:

5. Configuring a Server Block

In Nginx, a server block is a configuration that works as its own server. By default, Nginx has one server block preconfigured. It is located at /var/www/html. However, it can be configured with multiple server blocks for different sites.
Note that in this tutorial, we will use test_domain.com for the domain name. This may be replaced with your own domain name.
In a terminal, create a new directory by entering the following command: sudo mkdir -p /var/www/test_domain.com/html Use chmod to configure ownership and permission rules: sudo chown –R $USER:$USER /var/www/test_domain.com
sudo chmod –R 755 /var/www/test_domain.com
Open index.html for editing in a text editor of your choice (we will use the Nano text editor): sudo nano /var/www/test_domain.com/html/index.html You will see the HTML code like below in it. You edit it if you like, but we will keep it this way.

Press CTRL+o to write the changes, then CTRL+x to exit.
Now, open the configuration file for editing: sudo nano /etc/nginx/sites-available/test_domain.com Enter the following code in it: server {
listen 80;
root /var/www/test_domain.com/html;
index index.html index.htm index.nginx.debian.html;
server_name test_domain.com www.test_domain.com;
location / {
try_files $uri $uri/ =404;
}
}
So that you have the following result:

Press CTRL+o to write the changes, then CTRL+x to exit.
Next, create a symbolic link between the server block and the startup directory by entering the following: sudo ln –s /etc/nginx/sites-available/test_domain.com /etc/nginx/sites-enabled Afterward, you should restart Nginx by running the following command: sudo systemctl restart nginx Then, open /etc/hosts for editing: sudo nano /etc/hosts You will see the following result:

Next, enter this command after the last line: 127.0.1.1 test_domain.com www.test_domain.com So that it becomes like this:

Now if you open a browser window and navigate to test_domain.com (or the domain name you configured in Nginx). You should see the message you entered in HTML file you opened with nano. Notice that there were already an HTML script in there and we didn’t change it. But anyway, if you have changed the HTML file, you will see the result of your edition different from ours:


Conclusion

In this tutorial, we have provided the guidelines for installing, starting, and setting Nginx up and running on Linux. Also we tested the configuration and in the end, we configured an Nginx server block. We hope you enjoyed this quick Nginx configuration tutorial and it has been helpful for you.

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