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 […]
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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 […]
Read more →Azure Event Grid: A Solutions Architect’s Guide to Event-Driven Architecture
Event-driven architecture has become the backbone of modern distributed systems, enabling applications to respond to changes in real-time while maintaining loose coupling between components. Azure Event Grid represents Microsoft’s fully managed event routing service, designed to simplify the development of event-based applications at scale. After implementing Event Grid across numerous enterprise projects, I’ve gained deep […]
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