Designing RESTful APIs for LLMs requires careful consideration. After building 30+ LLM APIs, I’ve learned what works. Here’s the complete guide to RESTful AI API design. Figure 1: RESTful AI API Architecture Why LLM APIs Are Different LLM APIs have unique requirements: Async operations: LLM inference can take seconds or minutes Streaming responses: Need to […]
Read more →Search Results for: events
Azure Logic Apps: A Solutions Architect’s Guide to Enterprise Workflow Automation
After two decades of building enterprise integration solutions, I’ve watched workflow automation evolve from complex BizTalk orchestrations to elegant cloud-native services. Azure Logic Apps represents Microsoft’s vision for democratizing integration—enabling both citizen developers and seasoned architects to build sophisticated workflows without drowning in infrastructure concerns. This guide explores how to leverage Logic Apps effectively in […]
Read more →Azure Databricks: A Solutions Architect’s Guide to Unified Data Analytics and AI
The convergence of data engineering, data science, and machine learning has created unprecedented demand for unified analytics platforms that can handle diverse workloads without the complexity of managing multiple disconnected systems. Azure Databricks represents a compelling answer to this challenge—a collaborative Apache Spark-based analytics platform optimized for the Microsoft Azure cloud. Having architected data platforms […]
Read more →Azure Synapse Analytics: A Solutions Architect’s Guide to Unified Data Analytics
The modern enterprise data landscape demands more than traditional data warehousing or isolated analytics solutions. Organizations need unified platforms that can handle everything from batch ETL processing to real-time streaming analytics, from structured data warehousing to exploratory data science workloads. Azure Synapse Analytics represents Microsoft’s answer to this challenge—a comprehensive analytics service that brings together […]
Read more →Running LLMs on Kubernetes: Production Deployment Guide
Deploying LLMs on Kubernetes requires careful planning. After deploying 25+ LLM models on Kubernetes, I’ve learned what works. Here’s the complete guide to running LLMs on Kubernetes in production. Figure 1: Kubernetes LLM Architecture Why Kubernetes for LLMs Kubernetes offers significant advantages for LLM deployment: Scalability: Auto-scale based on demand Resource management: Efficient GPU and […]
Read more →Streaming LLM Responses: Building Real-Time AI Applications (Part 2 of 2)
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 […]
Read more →