In this blog post, we will introduce our custom multi-cloud CI/CD (continuous integration and continuous delivery) pipeline, built to facilitate the deployment of applications across various cloud environments. Our solution allows seamless deployments with minimal customization, ensuring faster results and reduced costs for our clients. Whether working with AWS, Azure, or Google Cloud, we can deliver a consistent deployment process that simplifies development, operations, and scaling.
The driving problem behind this solution is simple: our clients operate in diverse environments and rely on different cloud platforms. We often have multiple projects where clients utilize AWS, Azure, GCP, or even combinations of these. As a DevOps team, our challenge was to create a standardized, unified CI/CD solution capable of efficiently deploying to any cloud environment with minimal adjustments. We wanted to avoid the lock-in effects of each vendor’s distinct tools while leveraging the common underlying technologies that all clouds use, like Docker containers.
Our custom CI/CD pipeline is built on modularity and cloud-agnostic principles, offering flexibility to deploy consistently on any cloud. In this post, we’ll show how our solution works, beginning with the foundational architecture, followed by a detailed look at deploying our AI Universal Core Chat solution in AWS. Let’s dive in.
Cloud-agnostic CI/CD solution with modular approach
All major cloud providers – AWS, Azure, GCP – use common technologies that our DevOps engineers harnessed to build a universal CI/CD pipeline. Docker containers are at the core of this system, enabling application components to run seamlessly, regardless of the cloud provider used. We designed a base configuration that we can replicate across platforms, which reduces complexity and allows faster deployments.
Click or tap on the picture to open it in full size
This modularity is the key to flexibility. Each part of the deployment – from source code build to container registry, through to deployment to a cloud environment – is treated as an independent module. As a result, we can tailor which components are handled by our custom tools versus a given cloud’s native services, enabling a balanced approach between customization and efficiency. Below, we’ll use a sample deployment on AWS to demonstrate this system in action.
Example of deploying AI Universal Core Chat on AWS
To illustrate our CI/CD solution, we’ll explore deploying our AI Universal Core Chat (a RAG-based AI Chatbot solution) on AWS. The key components involved in this deployment example include the backend application running on Amazon EC2, the Neo4j vector database, and Amazon Elastic Container Registry (ECR) for managing Docker images.
The deployment starts with the backend application, which is packaged in Docker containers. The Docker image, containing the application and its dependencies, is tagged and uploaded to Amazon ECR. Environment files – containing sensitive details like database access keys and connection settings – are stored separately to maintain security. Our custom utilities ensure that these environment files are securely prepared, transmitted, and applied to the deployed application.
Click or tap on the picture to open it in full size
From there, the deployment process is straightforward: the EC2 instance running Docker pulls the container image from ECR, and our orchestration tools ensure it is properly configured for the environment. The containerized Neo4j instance is also deployed alongside each backend.
Adaptable cross-cloud CI/CD pipeline solution
The modularity of our pipeline allows us to easily adapt it to other cloud environments. If the AI Universal Core Chat solution needs to be deployed on Azure or Google Cloud instead of AWS, our CI/CD pipeline ensures that only minimal changes are necessary. For instance, we replace Amazon EC2 instances with Azure Virtual Machines or Google Compute Engine, and Amazon ECR with Azure Container Registry or Google Container Registry. This flexibility means that switching cloud environments can take as little as a few hours of work, with no disruption to the core functionality.
The result is a consistent deployment process that meets our clients’ specific cloud preferences while maintaining the highest standards of efficiency and security. By using a cloud-agnostic design, we help businesses avoid vendor lock-in and achieve maximum agility when scaling their applications across multiple environments.
Ready to scale up? Let’s connect
Our custom CI/CD pipeline is built for efficiency, scalability, and flexibility—ready to support your needs no matter which cloud platform you’re using. With a modular, cloud-agnostic approach, we cut down on deployment times, reduce costs, and keep you free from vendor lock-in. Whether it’s AWS, Azure, GCP, or a mix, we’ve got you covered.
Want to know more? We’d love to show you how our CI/CD solution can simplify your deployments and accelerate your projects. Contact us to schedule a consultation.
