Modern software development uses CI/CD pipelines to speed up software systems' delivery timelines. Most technical teams face pipeline system expansion as a critical engineering hurdle. The paper presents a detailed framework for the automation of CI/CD pipelines, which combines Terraform and GitLab specifically to achieve maximum scalability and efficiency. Organizations can create affordable and secure cloud infrastructure deployment management through a GitLab CI/CD platform integrated with Infrastructure as Code (IaC) frameworks. This allows them to manage infrastructure deployment simultaneously with application deployments while ensuring repeatability. Application and process efficiency and automated infrastructure deployment stem from the connection between IaC technology and GitLab CI/CD tools. The document shows deployment processes by demonstrating actual code, which helps organizations gain competence in tool usage. During the actual implementation of the framework, deployment speed increased by 55%, as the framework reduced infrastructure costs by 25% and improved deployment reliability to 70%. Terraform and GitLab work together to transform DevOps operational frameworks based on the provided results. Implementing such a framework enables organizations to optimize their DevOps workflows, lowering manual tasks while expanding their CI/CD pipeline capabilities. The paper presents essential best practices and integration methods that provide essential knowledge about present-day software development requirements for automated deployments.

Content-Based Image Retrieval (CBIR) plays a crucial role in efficiently searching and retrieving images from vast databases. This comprehensive survey investigates the application of color and texture features in CBIR systems. We explore the evolution of CBIR technology, delve into various color and texture feature extraction techniques, and examine their impact on retrieval performance. The study provides valuable insights into the state of the art in CBIR, offering a foundation for researchers and practitioners seeking to enhance image retrieval using color and texture features.