<ul data-eligibleForWebStory="true"><li>Serverless computing offers agility, scalability, and cost efficiency by abstracting infrastructure management but faces challenges like cold start latency and vendor lock-in.</li><li>Hybrid architectures, combining serverless with traditional services, mitigate cold start latency by using each model for their strengths.</li><li>AI/ML plays a proactive role in predicting demand, avoiding cold starts, and optimizing serverless resource allocation.</li><li>Multi-cloud deployments and abstraction layers combat vendor lock-in, providing flexibility and portability in serverless architectures.</li><li>The serverless landscape is evolving with AI/ML integration, hybrid approaches, and multi-cloud strategies, making it more resilient and performant.</li><li>The future of serverless includes advancements in predictive scaling, seamless multi-cloud integration, and enhanced observability tools.</li></ul>

Solving the Serverless Paradox: How Hybrid Architectures and AI/ML Enhance Performance and Portability

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