Control Plane vs Data Plane: A Concrete Pattern for Modern Backend Systems
How to split your system into 'think' (control) and 'do' (data) parts so you can move faster without risking your core traffic path.
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How to split your system into 'think' (control) and 'do' (data) parts so you can move faster without risking your core traffic path.
Show, in concrete terms, how to let AI agents touch real infrastructure without turning your cluster into a sandbox accident.
A hands-on guide to designing CI/CD pipelines that treat agentic AI (multi-step, tool-using agents) as first-class deployable units, not magical black boxes.
Show a practical way to move from guessing about LLM quality to measuring it using logs, labels, and simple experiments.
Show how to turn a chatty LLM into a safe JSON-producing service that other systems can trust.
How to design web services that slow down gracefully instead of crashing when traffic or downstream latency spikes.
How to design SaaS systems where many tenants share the platform but don't share failure modes, noisy neighbors, or data.
How to keep AI models on devices useful and safe after you ship them. Practical patterns for detecting drift, retraining, and safely rolling out updates to edge AIoT fleets.
How to train useful AI models across many devices without pulling all the raw sensor data into the cloud.
How to get thousands of devices securely online without manual setup, stickers, or spreadsheets. A complete guide to zero-touch provisioning for IoT fleets.