Integrating Advanced IT Systems A Comprehensive Study on Modern Information Technology Management

Abstract

The study determines the effectiveness of IT system integration through an evaluation of critical performance indicators from DevOps together with AWS and Azure deployment. The research employs exploratory data analysis to find major differences in integration results between organizations which shows that DevOps performance matters alongside deployment time duration and resource consumption along with cloud scalability capabilities. The evaluation between Amazon Web Services and Azure shows that scalability runs best in AWS yet Azure provides superior reliability as organizations need to determine their cloud platform through operational requirements. The influence of predictive accuracy was enhanced through the implementation of machine learning models namely Logistic Regression, Random Forest, and Support Vector Machine (SVM) which evaluated integration success. The Random Forest model produced the best results (89.4%) by determining deployment time, resource usage and DevOps efficiency as the key performance factors. IT system integration outcomes receive substantial improvement from process enhancement, resource control practices and artificial intelligence deployments within DevOps environments. The research findings create important business needs that require affordable cloud infrastructure design with robust security systems alongside data-based IT decision making. Technological advancements that include automated resource scaling together with hybrid cloud optimization and AI-driven DevOps operations will boost integration effectiveness thus producing more resilient IT systems that adapt better to dynamic technological environments.