Cloud-native has been one of the hottest topics in software development for quite some time. Some developers simply refer to it as the hype that will fade away with time. Others believe it is the future of software development.
Whatever the future holds, cloud-native is today one of the most important developments in the software business. Furthermore, it has already altered our perspectives on designing, deploying, and operating software products.
But exactly, what is cloud-native?
Cloud-native is much more than simply signing up with a cloud provider and running your existing applications on it. Cloud-native has an impact on your application's design, implementation, deployment, and operation.
It is a method of developing software applications as microservices and running them on a containerized and dynamically orchestrated platform to make use of the benefits of the cloud computing model.
"Cloud-native computing leverages an open-source software stack to be: – Containerized," according to the Cloud Native Computing Foundation, an organization that strives to create and accelerate the adoption of the cloud-native programming paradigm. Each component (applications, processes, etc.) has its own container. This makes repeatability, transparency, and resource isolation easier.
— Dynamically choreographed. Containers are actively scheduled and managed to make the best use of available resources.
— Microservices-centric. Microservices are subsets of applications. This considerably improves application agility and maintainability."
Let's be honest: "Leverage the benefits of the cloud computing model" sounds fantastic. However, if you're new to cloud-native computing, you're undoubtedly wondering what all the fuss is about. You may also be wondering how it influences how you implement your program.
Let's have a look at the various components.
The core idea behind containers is to bundle your software with everything needed to run it into a single executable package, such as a Java VM, an application server, and the application itself. The container is then executed in a virtualized environment, isolating the confined application from its surroundings.
The key advantage of this method is that the application is no longer dependent on the environment. The same container can easily be run on your development, test, or production systems. Furthermore, if your application design allows for horizontal scalability, you can start and stop multiple instances of a container to add or remove instances of your application based on current user demand.
The Docker project is the most common container implementation at the moment. It's so prevalent that the phrases Docker and container are often used interchangeably. Keep in mind that the Docker project is only one implementation of the container concept and that it may be superseded in the future.
The first step is to deploy your application and all dependencies into a container. It overcomes your past deployment issues, but if you want to fully benefit from a cloud platform, you'll face new hurdles.
Starting more nodes or shutting down operating application nodes based on your system's current load will be difficult. You must do the following:
Keep track of your system.
Trigger a container's launch or shutdown and ensure that the essential configuration parameters are in place.
Distribute the workload among the active application instances.
Distribute authentication secrets among your containers.
Manually accomplishing all of this takes a significant amount of time and work. Furthermore, it is too slow to respond to unanticipated changes in system load. You must have the necessary tools in place to do all of this automatically. To automate responses to unexpected changes, many orchestration solutions are constructed, with popular alternatives being Docker Swarm, Kubernetes, Apache Mesos, and Amazon's ECS.
Now that we've established all of the infrastructure and management, it's time to discuss the modifications that cloud-native brings to your system's design. Cloud-native applications are created as microservices architecture. I'm sure you've heard of that architectural approach, and I've published a series of posts on it on this site.
This architectural style's overarching goal is to construct a system of several, relatively tiny applications. These are known as microservices, and they operate together to give your system's entire functionality. Each microservice provides a single function, has well-defined boundaries and API, and is developed and maintained by a small team.
This approach provides several benefits, such as:
To begin with, it is far easier to implement and understand a smaller program that delivers a single capability than it is to build a massive application that does everything. The method shortens development time and makes it much easier to adjust the service to changing or new requirements. You don't have to be concerned about the unanticipated consequences of a seemingly minor alteration. It also allows you to concentrate on the development task at hand.
Microservices also enable more effective scaling. When I talked about containers, I indicated that if there was a spike in user requests, you could simply create another container. This is referred to as horizontal scaling. You can practically perform the same thing with any stateless application, regardless of size. You can send the next user request to any available application instance as long as the application does not store any state.
Even while you can scale a monolithic application or a system of microservices, in the same way, scaling a system of microservices is frequently much cheaper. You simply need to scale the microservice that receives a lot of traffic. You don't need to add any more instances of the other services as long as the rest of the system can handle the existing demand.
Scaling a monolithic application is entirely different. If you need to enhance the capacity of a single feature, you must launch a new instance of the entire monolith. This may not seem like a big concern, but in the cloud, you pay for the use of hardware resources. Even if you just use a small portion of the monolith, you must still acquire extra resources for the remaining, unused portions.
As you can see, microservices allow you to use cloud resources more efficiently and minimize your cloud provider's monthly fee.
Challenges Introduced by Microservices
Microservices eliminate some of the complexity from the services and improve scalability, but you're now creating a distributed system. This adds a significant amount of complexity to the system.
To keep this extra complexity to a minimum, try to avoid any dependencies between your microservices. If that is not practicable, you must ensure that dependent services can discover one other and communicate effectively. You must also deal with delayed or unavailable services so that they do not disrupt the entire system. In Communication Between Microservices: How to Avoid Common Problems, I go into greater detail on the communication between microservices.
‘The dispersed architecture of your system also makes monitoring and managing your system in production much more difficult. Instead of a few monoliths, you must now supervise a system of microservices, and each service may have multiple instances running in parallel. When you need to monitor more application instances, utilize a tool like Retrace to gather data from all systems.Building microservices
It is not required to use a specific framework or technology stack to build a microservice, but it makes the process much easier. Specific frameworks and technology stacks provide a plethora of ready-to-use capabilities that have been thoroughly tested and are suitable for usage in production scenarios.
There are other solutions accessible in the Java world, including the popular Spring Boot and Eclipse Microprofile.
Spring Boot, as the name suggests, combines the well-known Spring framework with a number of other frameworks and modules to address the additional issues of the microservice architecture.
The Eclipse Microprofile is based on the same concept, however, it employs Java EE. Several Java EE application server providers collaborate to provide a set of specs as well as numerous, interchangeable implementations.
Cloud-native computing ideas and principles presented a new approach to creating complicated, scalable systems. Even if your application is not hosted on a cloud platform, these new principles will influence how you create applications in the future.
Containers greatly simplify the distribution of an application. During the development process, use containers to share apps across team members or to run programs in multiple contexts. After all, tests have been completed, the same container may be easily deployed to production.
Microservices present new difficulties and transfer your focus to the design of each component while providing a new approach to structure your system. Microservices improve encapsulation and enable the creation of maintainable components that may be readily adapted to new requirements.
If you decide to use containers to run a production system of microservices, you'll need an orchestration solution to help you manage the system.
Build the best cloud-native services with Retrace
Cloud-native, whether a fad or not, provides adaptable options for software products based on project requirements. In fact, numerous businesses use microservices to implement their software solutions.
When using cloud services, a tool like a Retrace can help you monitor performance. Retrace is a code-level APM solution that can manage and monitor the performance of your app throughout the software development lifecycle, as well as provide other useful capabilities such as log management, error tracking, and application performance metrics.
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