The holy grail of code developers: What Lies Between Continues Integration Continues Deployment (CICD) to Dockers, Containers, and Kubernetes
In product development processes, the most important thing for developers is continuity – it’s important to save the process through the entire development duration while it’s being run and tested.
The ideal scenario is activating an automated mechanism that will know how to take the code in development, compile it, and execute automated test mechanisms to ensure that the code is written and saved correctly. Only after that will it be possible to integrate it where it was intended. As soon as the process will be automated, the number of errors will drop substantially.
The CI/CD methodology – Continuous Integration, Continuous Delivery, Continuous Deployment, sets clear key rules for the development process that enables completely different people to reach the same common ground, work in a unified standard, and achieve the goals under the defined schedule and budget. And just as importantly, it enables young professionals to learn and develop with the organization.
CI/CD methodology enables the use of automation tools when developing code. Every process in a project, no matter how big or small needs to start automatically to reduce human error. In the automation process, several essential steps occur that must not be skipped: testing for typing errors in the code (static analysis), unified code tests (Unitests), integration tests, and code packaging.
What is a docker? How does it activate containers?
A docker is a software platform that enables to build, share, and run applications inside containers. To better understand the need for this kind of platform in an organization, let’s assume that you have a system that is built up from several components: a database, a web server, an application server, and small services that help the application to run, and more.
Without a docker, you might run into several problems with this kind of system. First of all, in the development environment: it’s possible that you would like to try and develop a new version of the system in front of a newer version of the database. However, you still need to keep the old database installed on your computer to fix bugs in the production environment.
The same problem exists with every one of the infrastructure components – server upgrade, the programming language version, or libraries. All of these can cause clashes when you try to combine several versions on the same development machine. When a new developer enters the team, he might find himself spending an entire day installing things. Installing every part and infrastructure of the system on a new machine becomes more complex as the number of components increases.
In the same manner, when moving to deployment, you might run into other problems: a hard time adding or downloading “servers” from the network – because each server needs to hold all of the infrastructure components to run the system.
Existing servers’ utilization problem due to global installment – it is possible that your server is “vacant” enough most of the time to run another system component, but this component requires a different version of the database, and you don’t want to cause any clashes.
Docker knows how to solve a large chunk of these problems by using containers. Each container holds one app or more, and the docker itself knows to “activate” these containers in a semi-isolated environment. It’s not a separate virtual machine but something much lighter. The processes and files are saved directly on the present machine but separately from the main system. In a sense, the developers give the app a feeling that it’s running alone, even though it’s running with many other apps.
It’s important to mention that the separation between containers is not complete – if a certain container wants to break your server or listen to other containers, it can do it. That’s why it’s important to remember that a docker is not a virtual machine, and it’s important to operate only containers you trust.
How does Kubernetes fit in?
Kubernetes, a Container Orchestration framework, is a type of cloud environment. You tell it what to run, and it runs it. You “feed” it with containers (Docker or rkt) and settings – and it “takes care of the rest”. And yes, you need to assign Kubernetes a few servers (nodes) for the containers to run. In addition, you need to assign a few more servers to run the master nodes – the “brain” of the cluster. Because of this, you can say Kubernetes enables a newer and higher level of efficiency when using hardware resources.
For developers working on On-Premises systems without cloud technology, moving to Kubernetes is a huge improvement. The transition from using a “virtual machine cloud” to Kubernetes is as dramatic.
In conclusion, which tool is recommended to get the most out of Containers, Dockers, CI/CD, and Kubernetes?
With Talend Data Fabric, a tool that was built with an open-source-based architecture and fast and efficient code development paradigms, you can build the same Docker with a click of a button or with an automated CI/CD mechanism without the need to write any code or customize the development.
The tool generates code and doesn’t require designated running components (it can generate JAR or SPARK). This enables running processes “to run” 10 times as fast, and even more, compared to competing products. With this architecture, mechanisms were built that enable clients to maintain the processes easily (Continuous Integration) and quickly thanks to testing mechanisms and version control, enabling the creation of new versions of an existing process and transferring it to production in just a few minutes.
Talend Data Fabric offers complete automation, preserving the investment in development, an open solution with no need for a designated run–time server, converting Legacy processes with Metadata Bridge, and an integrative solution with the world of Big Data, so that time-to-market duration of development is faster than ever before.
By: Beni Fitoussi, CTO at Aqurate