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Amazon’s Tejas Patel on Distributed Systems, AI, and Managing Massive Scale, Podcast
At ITEXPO / MSP EXPO, Doug Green, Publisher of Technology Reseller News, spoke with Tejas Patel, Software Engineer at Amazon, for a technical deep dive into how one of the world’s largest platforms manages scale, reliability, and the growing role of AI in operations. Amazon operates in an environment defined by extreme traffic variability—from daily fluctuations to massive surges during Prime events. Patel explained that the company relies on distributed systems and microservices architecture to scale every layer of the stack, including databases, caching layers, and application servers. “We scale everything at a massive scale,” he noted, adding that AI-driven traffic prediction models help prepare systems for anticipated spikes, ensuring elasticity and resilience under pressure. Even with rigorous lower-environment testing and simulated traffic, real-world production environments introduce unpredictable behaviors. When outages or functional errors occur, the first priority is customer impact mitigation. “The short-term goal is to make our functionalities available for customers as soon as possible,” Patel said. After stabilizing services, engineering teams conduct root cause analysis and implement long-term fixes to prevent recurrence. On-call teams remain a core part of this model, though that may evolve. AI is increasingly part of that evolution. Patel described how AI systems can detect latency drops, identify anomalies, trigger workflows, and begin root cause investigations—sometimes before engineers are alerted. While still in a supervised phase, AI is gradually moving from passive support to more autonomous operational roles. “AI has a lot of protocols built where it can talk to all the systems,” he explained, envisioning a future where AI mitigates issues proactively while engineers oversee the broader architecture. For MSPs and channel professionals looking to understand large-scale technology environments, Patel emphasized the foundational importance of distributed systems. “Distributed system is everywhere,” he said. “It’s the backbone of a large-scale product.” As AI models and inference platforms continue to expand globally, scalable distributed infrastructure will remain essential to delivering reliable, uninterrupted user experiences. Visit https://www.amazon.com/
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