Serverless Showdown: Cloud Run vs Cloud Functions vs App Engine – Choosing the Right GCP Compute Platform

Serverless Showdown: Cloud Run vs Cloud Functions vs App Engine Choosing the Right GCP Compute Platform for Your Workload I’ve deployed applications to all three GCP serverless platforms—Cloud Run, Cloud Functions, and App Engine. Each has strengths, but choosing wrong costs time and money. I’ve seen teams spend weeks migrating from App Engine to Cloud […]

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The Type Revolution: How Python’s Gradual Typing Transformed My Approach to Building Production Systems

Executive Summary Five years ago, I would have dismissed Python type hints as unnecessary ceremony for a dynamically typed language. Today, I cannot imagine building production systems without them. This shift did not happen overnight—it came from debugging production incidents at 3 AM, onboarding new team members to complex codebases, and watching refactoring efforts spiral […]

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Orchestrating Chaos: Why AWS Step Functions Became My Secret Weapon for Building Resilient Distributed Systems

Three years ago, I inherited a distributed system that processed insurance claims across twelve microservices. The orchestration logic lived in a tangled web of message queues, retry handlers, and compensating transactions scattered across multiple codebases. When something failed—and in distributed systems, something always fails—debugging meant correlating logs across a dozen services while the business waited […]

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Data Quality for AI: Ensuring High-Quality Training Data

Data quality determines AI model performance. After managing data quality for 100+ AI projects, I’ve learned what matters. Here’s the complete guide to ensuring high-quality training data. Figure 1: Data Quality Framework Why Data Quality Matters Data quality directly impacts model performance: Accuracy: Poor data leads to poor predictions Bias: Biased data creates biased models […]

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