Cloud-Native Is One Of The Hottest Topics Related To Software Development. Some Developers Describe Cloud Native As A Passing Fad That Will Disappear After A While, But Others See It As The Future Of Software Development.

Currently, cloud-native is one of the biggest trends in the software industry, which has changed the attitude of developers and companies towards the development, deployment, and implementation of cloud-based software products.

What is Native Cloud?

Cloud-native is a computer software development mechanism that natively uses cloud computing infrastructure and services. Still, cloud-native is a more profound concept than the use of resources hosted in cloud computing infrastructure and used by applicable software company Pivotal, which developed the Spring framework and provides cloud services, says in this connection: “A native cloud is an approach to building and running applications that take full advantage of cloud computing .”

The Cloud Native Computing Foundation, an organization that is trying to introduce the cloud-native programming pattern as a standard paradigm to the software world, describes cloud-native as an open source software stack that has the following three characteristics:

• Containerized: Each section that includes programs, processes, etc., is packaged in its containers. It facilitates reproducibility, transparency, and separation of resources.

• Dynamically Orchestrated: Configurations are dynamically adjusted so containers can be scheduled and managed to use resources best. 

• Microservices-oriented: Applications are divided into microservices to become more agile and maintainability of applications. 

Both definitions are similar and indicate that cloud-native is a solution that allows us to create applications as microservices and deploy them on a containerized and dynamic platform to take advantage of the cloud computing model. While cloud-native and software running on this platform are doing great, some developers are still not well-informed about cloud computing and its potential benefits. To properly understand the above technology, we must have basic information about its underlying components.

Containers

A container is virtualization software that runs at the operating system level and includes any dependencies the software needs to run. The most important reason for the existence of containers is to implement an environment for transferring software from one processing environment to another for execution without facing the usual complications. The main idea behind containers is to package your software with all the dependencies it needs, such as the Java Virtual Machine, the server application, and the application itself, in an executable module. Next, the container and the application run in a virtualized environment.

The main advantage of the above approach is the non-dependence of the program on the execution environment and the portability of the container. You can run the container on development, test, or production systems without requiring special modifications.

If the application design supports horizontal scaling, you can run or suspend multiple instances of the exact container or add or remove different cases of the application based on current user demand.

Currently, the Docker project is the most popular container in the computing world. Interestingly, the increasing popularity of this technology has made some users use Docker and Container instead of each other. However, remember that the Docker project is only one implementation of the container concept and may be replaced by better options in the future. If you’re interested in using Docker, it’s best to start with the free community version.

You can install Docker on your local desktop and create your containers and deploy your first application to a container. Once the work on the project is finished, the next step is to go through the quality assurance process to ensure everything is working smoothly and then deploy it in its final form.

One of the biggest concerns that software developers have is the inability to properly run an application that works in a test environment without problems but faces many problems in a production environment. Some dependencies need to be updated to run correctly.

A container contains all the essentials that an application needs. Interestingly, the container keeps only the essential modules required to run the program, so it does not waste space.

Docker can run an application and its dependencies in a virtual container running on Linux, Windows, or Mac. What Docker does is package applications. These packages are called containers.

A container is a standard software module that packages the code and all its dependencies. This way, the application runs faster and more reliably in different computing environments.

Each container prepares an isolated environment similar to a virtual machine. Unlike virtual machines, Docker containers do not run a complete operating system but share the host’s kernel and perform software-level virtualization.

For example, imagine three Python-based applications will host on a single server, which can be a physical or a virtual machine. Also, imagine that each program uses a different version of Python and libraries and dependencies.

Since installing different versions of Python on the same machine is impossible, it will not be possible to host these three programs on a single computer. It is where Docker comes in.

In the above scenario, the problem can solve by using three separate physical machines, which would cost you a lot to purchase the systems. Another approach is configuring one physical machine to host three virtual machines simultaneously. Regardless of which solution is chosen, the costs related to the provision and maintenance of hardware are heavy.

Docker technology is presented to solve this problem optimally and at a lower cost. Some experts believe that the future software development process will be based on cloud computing.

Orchestration

Deploying the application with all its dependencies in a container is the first step to solving the problems, but if you want to take full advantage of a cloud platform, you will face new challenges. Starting up additional nodes or shutting down running nodes based on the current system load is not a simple task, as you need to do the following to manage this process properly:

•  Check the system (server) that is serving.

•  Start or stop a container. 

•  Make sure all required configuration parameters are in the container.

•  Balance the load between different running application instances.

•  Share an authentication mechanism between containers.

Doing all this requires a lot of effort. In addition, it is not possible to react quickly to unexpected changes in server resource consumption, so you need to have the right tools in place to do all this automatically.

Solutions are used to automate reactions to unexpected changes. Orchestration-based solutions emerged. Popular options in this field include Docker Swarm, Kubernetes, Apache Mesos, and Amazon ECS.

When applications are hosted on cloud infrastructure, it becomes challenging to manage each host system and abstract the complexity of the underlying platform.

Coordination is a general term that refers to container scheduling, cluster management, and technical issues related to hosts. One of the essential issues to pay attention to is the issue of scheduling, which refers to the ability of an administrator to load a file service on a host system and determine how to run a specific container.

Here, cluster management is the process of controlling a group of hosts. This management can include adding and removing hosts from a cluster, getting information about the current state of hosts and containers, and starting or stopping processes.

Cluster management is closely related to scheduling because scheduling tools must access all cluster hosts to schedule services. For this reason, the same device is used in most cases.

One of the most significant responsibilities of a scheduler is host selection. If an administrator decides to run a service (container) on a cluster, the scheduler is responsible for automatically selecting a host in most cases. The administrator can propose containers to the scheduler based on specific needs or interests, but the scheduler is responsible for enforcing these requirements.

Microservices

Now that we have an overview of infrastructure and management tools, it’s time to talk about the changes cloud-native brings to systems architecture. A microservice refers to independent software services that provide specific business functions to an application.

These services can be maintained, monitored, and distributed independently. Microservices are built on a service-oriented architecture. Here there is an important concept called SOA called Services Oriented Architecture, which allows applications to communicate with each other on a single system or when distributing applications on several methods in a network. Each microservice has little connection with other services.

Microservices architecture is naturally used with large and complex applications where multiple development teams can work independently to deliver a business function. Microsoft’s cloud office or customer relationship software (CRM) is an excellent example in this field. Cloud-native applications are also built as a system of microservices.

The general idea of ​​this architectural style is to implement a system based on multiple and relatively small applications that work together to provide the functionality required by applications. Each microservice provides specific functionality and has a particular API and API developed and managed by a software team.

This architecture has a significant advantage; Instead of building one extensive program that does everything, a program is divided into smaller parts, each responsible for doing a specific task. In such a situation, monitoring the application performance becomes more straightforward, the development process becomes faster, and it becomes easier to adapt the service to changed or new needs. In addition, you no longer need to worry about unexpected reactions of the application to a seemingly minor change.

Scaling

Microservices facilitate the principle of scaling so that you can quickly launch another container whenever you experience an increase in user requests. This technique is called horizontal scaling. You can use this technique in conjunction with stateless applications and send user requests to an instance of an existing application. In the microservice architecture, all services located on different machines can communicate with each other.

The above mechanism allows us to add new functions to the services and use the automatic continuous delivery and distribution process. In this case, applications become more stable because each feature can be tested and distributed independently.

Considering that each service is hosted on an isolated process if a service faces a bottleneck problem and needs a lot of resources, it is possible to move it to other machines and servers without any impact on the performance of the service or other services.

When more users use an application feature, that service can scale by distributing it to servers with more processing power or by using cache without affecting other services. Another advantage is that scaling at the level load native and containers provides ease of maintenance of application code.

As a result, the time needed to deliver new versions and costs is reduced.

In addition, code reusability is increased because a feature is hosted as a service, and multiple services can use the same feature instead of re-implementing the code each time. Service-oriented architecture offers the possibility of using a wide range of technologies to meet needs.

For example, R or Python are software data analysis packages that can be distributed and hosted separately. At the same time, C# can implement services, while NodeJS can use on the server side, and AngularJs and ReactJs can use to implement the user interface.

Scaling is the opposite of monolith architecture. It is possible to scale an application based on a monolithic architecture, but in most cases, it is cheaper to scale a system based on a microservices architecture. Microservices allow you to use cloud resources more efficiently and pay less monthly for the services you need. You only need to mount the microservice that receives a lot of loads and spread the traffic across virtual machines in the cloud.

Challenges related to microservices

Microservices try to remove the complexity around services and provide better scalability, but be aware that you are looking to implement a distributed system, which introduces new deployment challenges and more complexities at the system level. To reduce additional complexity, try to minimize any dependencies between microservices.

If it is impossible to remove all dependencies, ensure that the related services can identify and communicate with each other through the correct communication channels. Additionally, identify and troubleshoot unavailable or slow services that negatively impact the system.

How do we solve problems related to microservices?

The distributed nature of systems in the cloud makes it more difficult to manage systems and applications because you have to work a system of microservices, each of which may have multiple instances running in parallel. Use a tool like a Retrace to collect systems information when you need to monitor additional cases of applications.

The structure of microservices

There is no need to use a specific framework or technology stack to build a microservice, although some technologies make the process easier. Specific frameworks and technology stacks offer various out-of-the-box features that are well-tested and can be used in production environments. For example, in the Java world, there are many different options, with Spring and Eclipse Microprofile being the most popular.

Spring Boot integrates the popular Spring framework with several other frameworks and libraries to handle the additional challenges of microservice architecture.

Eclipse Microprofile has similar functionality but uses Java EE. In general, Java EE-based server application companies offer a variety of interchangeable specifications and implementations so that developers can best take advantage of the benefits of cloud-native development.

last word

The native cloud has introduced a new solution for implementing complex and scalable systems, which will fundamentally change the world of application development in the future.

Deploy production. After testing is complete, you can quickly deploy the container you worked on in the background. For example, containers simplify the distribution of an application, allowing you to use containers during the development process to share applications between team members or to run applications in different environments.

On the other hand, microservices offer a new way to structure systems. Still, they create new challenges that force you to design components separately and pay attention to every detail when designing applications deployed in the cloud. However, microservices improve orchestration and allow you to implement maintainable features that can adapt to new needs.

Finally, remember that if you use containers to run a microservices system in the execution environment, you need a coordinating solution to help you manage the system.

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