Advanced concepts in Cloud Platforms, page 3
Data Virtualization: One Query, Many Sources
Data virtualization creates a single logical database from many physical sources without moving the data. It's used for real-time integration across silos like SQL, NoSQL, and APIs.
Distributed Model Training: Splitting the Workload
Don't wait for one GPU to finish; use many. Distributed training splits a model's workload across multiple processors to finish faster. It's essential for massive deep learning models.
Model Drift: When Good Models Go Bad
A model is a snapshot of the world; model drift is the alarm that fires when the world changes but your snapshot has not. It detects when production data no longer statistically matches the training data, a common issue for models predicting user behavior.
Explainable AI (XAI): Why Did the Model Do That?
Explainable AI (XAI) translates a model's 'black box' decision into a human-readable reason. Use it to debug predictions, build user trust, or meet regulatory needs. The footgun: explanations are approximations of the model's logic, not absolute truth.
Circuit Breaker Pattern: Fail Fast, Not Hard
A circuit breaker wraps network calls to prevent cascading failures. It monitors for errors, and if a service seems down, it 'trips' to fail requests instantly without hitting the network. This gives the failing service time to recover.
The Sidecar Pattern: Offload and Isolate Application Logic
The Sidecar Pattern attaches a helper container to your main application, like a sidecar on a motorcycle. It offloads tasks like logging or proxying, letting you add features without changing the main app's code. The footgun is over-engineering a solution.
The Ambassador Pattern: Your App's Diplomatic Sidecar
The Ambassador pattern places a proxy next to your application to handle its network communication, like a diplomat. This adds modern features like monitoring, security, and retries to legacy apps or across languages without changing app code.
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