TechExplained

Straightforward explorations of engineering, architecture patterns, and the tech shaping tomorrow.

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architecture

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Edge Compute in Plain Words

Edge compute brings CPU and storage closer to where data is generated. Instead of hauling every request to a centralized region, you evaluate logic in lightweight runtimes that live near the user. The result is predictable latency and less data in transit. Early adopters ran only cache invalidations or feature flags at the edge. Today, full APIs, personalization engines, and even ML inference happen there. The trick is balancing stateful needs with the inherently stateless edge runtime model.

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Choosing an AI Runtime for Production

The AI stack is fragmenting into execution layers that prioritize either throughput, cost, or residency. Teams often chase hype instead of measuring constraintfit. Pick runtimes by clarifying latency budgets, concurrency spikes, and data boundaries first. Only then compare vendor SKUs, cold start profiles, and ops maturity.

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