The proliferation of spam emails continues unabated and challenges the security of digital communication systems, thus necessitating robust detection mechanisms. This paper develops an exhaustive spam detection system based on cloud computing resources as well as advanced ML models. The ability of AWS to scale up to take on a variety of data makes it perform real-time spam detection. The central contribution is a hybrid approach of ML based on logistic regression, SVM, random forests, and LSTM. This can address challenges including but not limited to scalability, adaptability to ever-evolving spam patterns, as well as real-time processing. Detailed evaluation and analysis show vast improvement in terms of detection accuracy and scalability at higher levels, which makes it a very effective solution for modern detection challenges against spam. Integration with cutting-edge security tools will help the system combat all possible threats.