Multi-cloud AI strategies prevent vendor lock-in and optimize costs. After implementing multi-cloud for 20+ AI projects, I’ve learned what works. Here’s the complete guide to multi-cloud AI strategies. Figure 1: Multi-Cloud AI Architecture Why Multi-Cloud for AI Multi-cloud strategies offer significant advantages: Vendor independence: Avoid lock-in to single cloud provider Cost optimization: Use best pricing […]
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LLM Observability: Tracing, Metrics, and Logging for Production AI (Part 1 of 2)
Introduction: Observability is essential for production LLM applications—you need visibility into latency, token usage, costs, error rates, and output quality. Unlike traditional applications where you can rely on status codes and response times, LLM applications require tracking prompt versions, model behavior, and semantic quality metrics. This guide covers practical observability: distributed tracing for multi-step LLM […]
Read more →Cloud Native and Multi-Cloud Architecture: A Complete Guide to Modern Infrastructure
The evolution of cloud computing has fundamentally transformed how we architect, deploy, and operate applications. Cloud-native architecture and multi-cloud strategies are no longer optional—they’re essential for organizations seeking agility, resilience, and competitive advantage in the digital economy. This comprehensive guide covers cloud-native principles, multi-cloud strategies, Kubernetes orchestration, and practical implementation patterns with real-world examples. Cloud […]
Read more →AWS Step Functions Distributed Map: Massive Parallel Processing
AWS Step Functions Distributed Map, announced at re:Invent 2022, enables processing up to 10,000 concurrent items in a Map state—compared to the previous 40-item limit. This makes Step Functions viable for large-scale ETL, data processing, and batch workflows that previously required custom orchestration or EMR. This guide covers architecture patterns, S3 integration, and cost optimization […]
Read more →Azure Bicep: Infrastructure as Code Deep Dive
Azure Bicep is the next-generation language for Azure infrastructure as code, replacing ARM templates. With cleaner syntax, modules, and first-class tooling, Bicep significantly improves the IaC developer experience. This guide covers Bicep fundamentals, module patterns, deployment strategies, and migration from ARM templates. Bicep vs ARM Templates Feature ARM JSON Bicep Syntax Verbose JSON Clean DSL […]
Read more →Azure Durable Functions: Complete Orchestration Patterns Guide
Azure Durable Functions extends Azure Functions with stateful orchestration capabilities. Unlike Step Functions (JSON-based ASL), Durable Functions uses code—C#, JavaScript, Python, or PowerShell—to define workflows. This code-first approach enables IDE support, unit testing, and complex control flow. This comprehensive guide covers the core patterns: Function Chaining, Fan-Out/Fan-In, Human Interaction, and the Actor Pattern with Durable […]
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