Cloud-native applications are specifically designed to take advantage of the features and benefits of the cloud. They differ from traditional applications in a few key ways: they’re more modular, they use microservices instead of monolithic architectures, and they rely on containers for deployment.
Developing cloud-native applications involves a lot of processes and tools, like application performance monitoring, continuous integration and delivery, and a good container registry like the Docker Registry by JFrog.
In this article, we’ll walk you through the steps involved in developing a cloud-native application. Ultimately, this will help you develop your applications more efficiently and effectively.
Table of Contents
Step 1: Composing Cloud-Native Apps
The first step in developing a cloud-native application is to compose it using microservices.
A microservice is a small, independently deployable unit that performs a single task. When multiple microservices are combined, they can work together to form a complete application.
Advantages of Microservices
One of the benefits of using microservices is that they can be deployed and scaled independently, which gives you a lot of flexibility when it comes to scaling your application.
Another benefit is that microservices are easier to maintain than monolithic applications because each service can be developed and maintained by a separate team.
If you need to make a change to one service, you don’t have to redeploy the entire application.
Step 2: Developing Cloud-Native Applications
Once you’ve composed your application using microservices, the next step is to develop each service.
When developing cloud-native applications, it’s important to keep a few things in mind:
* Make sure each service is loosely coupled and can be deployed independently.
* Develop each service using a 12-factor app methodology.
* Use containers for packaging and deployment.
The 12-Factor App Methodology
The 12-factor app methodology is a set of guidelines for developing cloud-native applications.
It includes 12 factors that should be taken into account when developing cloud-native applications:
- A single codebase tracked in revision control, used for both production and development.
- Explicitly declare and isolate dependencies.
- Store config in the environment.
- Treat backing services as attached resources.
- Strictly separate build and run stages.
- Execute the app as one or more stateless processes.
- Export services via port binding.
- Scale out via the process model.
- Maximize robustness with fast startup and graceful shutdown.
- Keep development, staging, and production as similar as possible.
- Treat logs as event streams.
- Run admin/management tasks as one-off processes.
Step 3: Testing & Deployment of Cloud-Native Applications
The next step in the process is to test and deploy the developed cloud-native application.
When testing cloud-native applications, it’s vital that you use a continuous integration and delivery (CI/CD) pipeline. This will help ensure that your application is deployed correctly and securely.
There are many different CI/CD tools available, but some of the most popular ones include Jenkins, Travis CI, and CircleCI.
Once you’ve set up your CI/CD pipeline, you can then deploy your application to a cloud platform like AWS, Azure, or Google Cloud Platform.
Use a Container Orchestration Tool
You should try to use a container orchestration tool like Kubernetes or Docker Compose when deploying to the cloud. This will help you manage your application’s containers and ensure that they’re deployed correctly.
Kubernetes is a popular choice for container orchestration, but it can be complex to set up and manage. If you’re just starting out, you may want to try Docker Compose, which is a simpler alternative.
Step 4: Monitoring & Logging for Cloud-Native Applications
Once your application is up and running in the cloud, you need to make sure that it’s being monitored and that all the logs are being collected.
Some of the most popular tools available for monitoring and logging include Prometheus, Grafana, and ELK Stack.
Prometheus is a popular open-source monitoring solution, while Grafana is a popular open-source graphing and visualization tool.
ELK Stack is a combination of three different tools: Elasticsearch, Logstash, and Kibana. In addition to this, diagnostic analytics, which plays a dedicated role in different business industries, can also be adopted to monitor performance and identify problems.
These tools will help you keep track of your application’s performance and ensure that any errors or issues are discovered and resolved quickly.
Developing cloud-native applications is a great way to improve the scalability and performance of your application.
By following the steps outlined in this article, you can be sure that your application is developed correctly and deployed securely. Additionally, using a CI/CD pipeline and container orchestration tool will help simplify the process of testing and deploying your application.
Finally, don’t forget to set up monitoring and logging to keep track of your application’s performance and ensure that any problems are identified and fixed as soon as possible.