This new era is not without its challenges. The initial euphoria surrounding cloud computing has given way to a more nuanced reality, with many organizations grappling with "cloud dissatisfaction" due to rising costs and vendor lock-in. Simultaneously, the explosion of AI and Machine Learning (ML) workloads has introduced new architectural paradigms and performance requirements that legacy systems are ill-equipped to handle. The modern architect must, therefore, be a master of balance, weighing the benefits of cutting-edge technology against the practical realities of budget, security, and operational stability.
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