Introduction: Waiting 10-30 seconds for an LLM response feels like an eternity. Streaming changes everything—users see tokens appear in real-time, creating the illusion of instant response even when generation takes just as long. Beyond UX, streaming enables early termination (stop generating when you have enough), progressive processing (start working with partial responses), and better error […]
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Azure Data Factory: A Solutions Architect’s Guide to Enterprise Data Integration
Enterprise data integration has evolved from simple ETL batch jobs to sophisticated orchestration platforms that handle diverse data sources, complex transformations, and real-time processing requirements. Azure Data Factory represents Microsoft’s cloud-native answer to these challenges, providing a fully managed data integration service that scales from simple copy operations to enterprise-grade data pipelines. Having designed and […]
Read more →GraphQL for AI Services: Flexible Querying for LLM Applications
GraphQL provides flexible querying for LLM applications. After implementing GraphQL for 15+ AI services, I’ve learned what works. Here’s the complete guide to using GraphQL for AI services. Figure 1: GraphQL Architecture for AI Services Why GraphQL for AI Services GraphQL offers significant advantages for AI services: Flexible queries: Clients request exactly what they need […]
Read more →Prompt Injection Defense: A Complete Guide to Sanitization, Detection, and Output Validation
Prompt injection represents one of the most critical security vulnerabilities in LLM applications. As organizations deploy AI systems that process user inputs, understanding and defending against these attacks becomes essential for building secure, production-ready applications. Understanding Prompt Injection Attacks Prompt injection occurs when an attacker crafts malicious input that manipulates the LLM into ignoring its […]
Read more →Azure Event Hubs: A Solutions Architect’s Guide to Real-Time Data Streaming
Real-time data streaming has become essential for modern enterprises that need to process millions of events per second while maintaining low latency and high reliability. Azure Event Hubs stands as Microsoft’s fully managed, big data streaming platform, designed to handle massive throughput scenarios that traditional messaging systems simply cannot address. Having architected numerous streaming solutions […]
Read more →LLM Monitoring and Alerting: Building Observability for Production AI Systems
Introduction: LLM monitoring is essential for maintaining reliable, cost-effective AI applications in production. Unlike traditional software where errors are obvious, LLM failures can be subtle—degraded output quality, increased hallucinations, or slowly rising costs that go unnoticed until the monthly bill arrives. Effective monitoring tracks latency, token usage, error rates, output quality, and cost metrics in […]
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