Cloud computing has completely changes the way online business is conducted and the delivery of auspicious tools, software, apps and updates take place. Everything is fast paced and everything is segmented into dedicated portions for the professionals as well as the technologies to grab their complete essence and then compartmentalize them using continuous integration pipelines. AWS (amazon web services) can help you choose the best pipeline systems that can streamline the overall process of integration, containerization as well as deployment of already developed systems.
But as you already might have wondered that Docker is a working unit of DevOps based approach that is why it is best suited if you have acquire AWS DevOps certification training and then go for the certification to better streamline things over at your organization.
This is where the idea of having Docker comes into the play, not only with the help of Docker the idea of compartmentalization or containerization can be achieved but also the updates could also be rolled out to the professionals in a classic way steaming/blocking out all the hassle that accompany the process. As some of you might not be acquainted with the idea of what Docker and its esteemed working is therefore it is essential to first grab the essence of very topic which we are talking about.
What is Docker and benefits of using this technology?
It is a container based system using which the concept of agility can be taken to the next level because every segment of data would be tightly packed within the core of every container and specified authentication or code would be required to initiate the process of deployment. You can forget about the manual integration of the code to control various aspects of the apps and the software systems that you have installed or are going to regulate for deployment because everything is automated and doesn’t require any manual integration whatsoever.
This can make all your work extremely easy as you won’t have to sit there waiting for the servers to fill with requests and then write a code to initiate the process of deployment everything will be automated and as per the requests of the incoming clients. It is extremely important to include for the sake of the article that Kubernetes and Docker are very different when it comes to the fundamental roles they have to play but when it comes to automation they are really not that different but two different parts of the same process.
One of the key elements or features of this tool is that it eradicates the complex detailing and submitting of code to multiple aspects of apps and software systems and distributes it in a particular manner. Each container can be accessed by authorized personnel, and the code for the relative container can be initiated. This container oriented infrastructure, in reality, is the most tenacious and bold system to ensure consistent coding or distribution of updates within app and software deployment.
As you might have grabbed the essence of what Docker is, now is the time to move onto the next phase of this article which is deploying Docker with AWS CodePipeline systems.
Deploying Docker using CodePipeline
It is extremely difficult to pitch in the last code/programming integration only after the code has been packed within the Docker container. Nothing can be done after the completion of process of containerization and that is why it is extremely difficult for programmers and coding experts to do any revisions after that but with the help of the AWS CodePipeline systems things can be turned around in an amazing way.
AWS CodePipeline brings into the use of secured strategies that can help the professionals to build the Docker image and then do various manifestations even if the elements of the software/tool or an update are being packed within the container. Elastic container service for the deploying of the container image and Elastic container registry for the sake of storing the Docker image are the extensive parts of the AWS CodePipeline that can also be of huge help to the users. The whole process of deploying Docker systems is classified or broken into three variant steps as follows;
- Building Docker image with AWS CodeBuild
To be able to develop a Docker image you will have to provide with a source code to the AWS CodeBuild in the format of YAML. You will have to name the file specifically as buildspec.yml, once you have done that the program would load the file that you have just integrated and would start building the Docker image according to the instructions packed within source code. The whole process would only take seconds and a viable Docker image for the understanding of AWS systems and for successful deployment of Docker using pipelines will be up and running.
- AWS CodePipeline
Here you will need to go to the AWS CodePipeline and view/spectate the following five settings to get yourself a CodePipeline for Docker systems;
- Provide your pipeline with a dedicated name to which you would like to refer to it
- Provide with a repository name, branch name as well as with the source of your project code
- Choose the specific code build and then specify details like ‘runtime as Docker’
- Mention the elastic container service cluster and service name
After the completion of these steps you would have a pipeline which you can use to deploy the Docker.
- Testing the pipeline
The following thing that you need to do before deploying the pipeline along with Docker is to actually test it on various scores. Some of the tests which are done to make sure that everything is working fine do include unit testing, integration testing, regression as well as smoke testing. After all of these tests are complete and show no negative concerns then you can deploy the dedicated Docker image using that specified pipeline. You can also find the best DevOps course depending on your nature of professional need and whether or not you would like to work with AWS Codepipeline systems regarding your own IT industry