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  • edge computing
    Tudor Iordache - 26 Sep 2024

    How edge computing is transforming the future of technology

    Edge computing addresses a structural limitation of centralized cloud architecture: as the volume of connected devices and the demands of real-time AI grow, routing all data through distant data centers introduces latency, bandwidth costs and compliance risk that certain applications cannot absorb. The model's value is not uniform across industries or use cases; it is most consequential where response time, data residency or operational continuity are non-negotiable constraints. The convergence of edge infrastructure with AI inference is the most significant recent development, shifting the economics of AI deployment by enabling model execution closer to the data source rather than in centralized compute environments. Most mature deployments combine edge and cloud in hybrid architectures, with workload characteristics determining placement rather than a preference for one model over the other. The infrastructure decisions organizations make now will shape what AI-driven and real-time applications can feasibly be built and operated at scale over the next several years. The way data moves through digital infrastructure is changing. For years, the dominant model was straightforward: devices collect data, send it to a centralized cloud, wait for a response. That model worked well enough when the volume of connected devices was manageable and when milliseconds of latency were acceptable. Neither of those conditions holds today.
    Technology Featured
  • Infrastructure-as-a-code-iac-mvp
    Tudor Iordache - 12 Dec 2023

    Infrastructure as Code: the MVP decision that outlasts your MVP

    The conversations that surround a new product build tend to focus on the visible parts: which features ship in version one, what the design system looks like, how quickly the first users can be in front of it. These are the right things to discuss, and founders are equipped to discuss them. The decisions that get less attention sit underneath: how the cloud environment is set up, how new versions get deployed, how a second engineer hired six months from nowwill be able to work on the product without breaking it. These choices are usually made early, often in the first few weeks of a build, and they tend to stay in place far longer than anyone expects.
    Technology Idea to MVP Featured Startup Architecture
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