This blog post focuses on the architecture and deployment of the AI-powered Chatbot solution that we described in our earlier blog post Custom AI Chatbot Development Using RAG. This solution is built for the AWS cloud but uses OpenAI as an LLM. We’ll dive deep into the CI/CD process and AWS deployment architecture of the backend application. AWS Deployment Architecture Our solution represents a rather typical configuration of a web project deployed to AWS. Click or tap on the picture […]

Starting a new software project or startup? Your initial decision could significantly impact your future success: choosing between monolithic and microservices architecture. Initially, a monolithic approach may be advantageous, providing simplicity in development, deployment, and testing, and enabling faster product launches. However, as your business expands, your software demands will grow. Shifting to a microservices architecture becomes a crucial, yet challenging, strategy. What obstacles might you encounter, and what factors should influence your choice? We’ll share insights from our experience […]

Discover the scalable multi-tenant backend architecture and robust CI/CD process at the heart of the client-server solution we developed for our major pharmaceutical customer. Initially crafted to assist asthma patients with medication adherence, this app also enables doctors to monitor treatment progress remotely. The market success of this solution led our customer to strategically scale it, offering it to other healthcare providers under a white labeling model. To technically achieve this strategy, we needed to develop a scalable, distributed backend […]

Our customer, a leading provider of end-to-end digital solutions for enhanced patient experiences, approached us with several challenges resulting from their rapidly growing customer base. These challenges included: Difficulty in expanding their software development team and many infrastructural environments to keep up with the growth; Inefficiency in legacy CI/CD pipelines and long deployment times; Difficulty in meeting new regulatory requirements and improving overall digital security; Lack of observability and efficient troubleshooting; Long release cycles and difficulty in setting up new […]

Recently, the ABCloudz team migrated a customer’s database from Apache Cassandra to Amazon DynamoDB. As part of this project, we needed to run multiple tests to ensure perfect quality for our delivery. However, we faced a problem in setting up the test environment. Even though we were using AWS CloudFormation templates for the EC2 instances, it was taking over 30 mins to get the dev/test environment setup. In addition, our developers couldn’t run parallel regression testing. So, we decided to leverage Docker to automate the environment set up.
In this blog post, we will share our experience with using Docker for automating a NoSQL database migration dev/test environment.