As the demand for faster and more reliable content delivery escalates, Content Delivery Networks (CDNs) face significant challenges in managing content placement across their increasingly complex, multi-tiered structures to balance performance, complexity, and scalability, while addressing the transient nature of data and the unpredictability of internet traffic. Addressing these challenges, this study introduces a novel multi-tier CDN caching strategy that navigates spatial and temporal trade-offs in cache placement, considering the cache placement cost diminishes with the content lifetime, and the uncertainty of future data demands. We design a distributed online algorithm that evaluates each incoming request and places new caches when the total content delivery cost exceeds a threshold. Our competitive analysis shows a tight and optimal $\mathtt {Tiers}+1$ competitive ratio. Additionally, our algorithm has low complexity by passing $O(\mathtt {Tiers})$ number of reference messages for each request, which enhances its practical applicability. Empirical validation through numerical simulations and trace-driven experiments confirms the superiority of our approach to existing benchmarks in real-world CDN settings.