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Enabling Ci/Cd Pipeline for Container-Based Workloads


DevOps is a combination of development and operations. It aims to create a faster development environment without sacrificing software quality. In the containerization process, source code goes through a series of transformations to produce Docker images that eventually get provisioned as docker containers.

Containers are lightweight and isolated services; they typically automatically support more accessibility to test, troubleshoot, and fix throughout the development lifecycle.

Consequently, Containers can be deployed consistently in multiple environments and are easy to transfer from one team to another, which helps foster cross-organizational collaboration.

Common use cases for Containerization workloads

  • Modernizing the legacy application development practices to the container-based platform.
  • Move pipelines and workflows across multiple microservices and applications with ease.
  • DevOps Enables compliance with industry standards and organizational policies while shipping releases faster to production.
  • Minimize errors during the build, deploy, test, and release process of a new software release

CI/CD Pipeline Architecture

DevOps with containers: the workflow

  1. A developer makes changes to the application source code.
  2. The code change is committed to a source control repository, such as GitHub.
  3. To start the continuous integration (CI) process, a GitHub webhook triggers a Jenkins project build.
  4. The Jenkins build job uses a dynamic build agent in AWS Kubernetes Service to perform a container build process.
  5. A container image is created from the code in source control and is then pushed to an AWS/Docker Container Registry.
  6. Using the process of continuous deployment (CD), Jenkins deploys an updated container image to the Kubernetes cluster.
  7. The web application uses Dynamo DB as its back end. Both Dynamo DB and AWS Kubernetes Service (EKS) report metrics to AWS Monitor.
  8. A Grafana instance provides visual dashboards of the application performance based on the data from AWS Monitor.


Tools Canvas

Containerization Infrastructure and Configuration as Code

Kubernetes is declarative. YAML configuration files can be created and stored in a Git repository and track all its changes like all other code.

Continuous Deployment Pipeline with No Downtime

The objective of the pipeline is to perform a set of tasks that will deploy a fully tested and functional service or application to production.

The need for frequent deployments is handled beautifully by Kubernetes by its container orchestration mechanism.

Easy Rollbacks 

Kubernetes framework automates rollouts, and rollbacks become simplified through version control and its declarative approach. 

When new code is ready to push to a container, the new desired state is defined, and Kubernetes orchestrates creating new containers and removing existing ones. 

If a problem arises, the immutable nature of Kubernetes containers allows easy rollbacks to the previous state.

On-Demand Infrastructure

Kubernetes, through the use of the configurations, can easily scale infrastructure up and down based on the resource needed to handle the workloads of the application. And it is elastic by nature.

Run Everywhere Pipelines

With Kubernetes architecture, we can easily migrate Containers and pipelines to anywhere in the same cloud or all on-premises.

Containerization Considerations


As part of the Amazon Kubernetes Service cluster, application traffic is distributed to one or more containers (pods) that run the application as individual microservices.

This approach to running containerized applications in Kubernetes provides a highly available infrastructure for the applications.


Amazon Elastic Kubernetes Service (EKS) lets to scale the number of cluster’s worker nodes to meet the applications workload demands. 

As the application increases, the EKS cluster can scale out the number of Kubernetes nodes.


Amazon Elastic Kubernetes Services (EKS) for your application. Built into Kubernetes architecture and its components are resilient by nature.

Kubernetes components monitor and restart the containers (pods) if there is an issue. Combined with running multiple Kubernetes nodes, applications can tolerate a pod or node being unavailable.

Security and Security Threats in Containers:

The Containerized environment must be foolproof for the potential risks and threats. and must be protected throughout its lifecycle (Development, build, deploy, run),

Access and Authorization Exploits:

Providing access to authorized users and blocking all other users accessing the platform. And encrypting K8’s configuration files (for example, web. config and appsettings.json), particularly in a containerized setup.

Container Image Vulnerabilities:

Security mechanism to prevent malicious attacks is the key.

Detecting code vulnerabilities, outdated packages, malicious code, and other harmful threats during the build stage can improve security dramatically. 

Monitoring CI/CD Pipelines, End-to-End:

  • Monitor health of the CI/CD build pipeline and setup cognitive, proactive alerts spanning various tools.
  • Assess performance and quality of deployments in a unified way across multiple tools
  • Monitoring the pipeline performance and reporting on issues, this scenario combines Amazon Monitoring Service (CloudWatch) with Grafana for visual dashboards. Or Extending build pipeline monitoring to include application monitoring (Nagios) and container monitoring (Kubernetes)
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