There’s a moment in every architect’s career when a technology fundamentally rewrites your mental model of how systems should work. For me, that moment came in 2016 when I deployed my first AWS Lambda function and watched it scale from zero to handling thousands of concurrent requests without a single configuration change. After two decades… Continue reading
Category: Cloud Computing
Cloud computing is Internet-based computing, whereby shared resources, software, and information are provided to computers and other devices on demand, as with the electricity grid.
Cloud computing is a natural evolution of the widespread adoption of virtualization, Service-oriented architecture and utility computing. Details are abstracted from consumers, who no longer have need for expertise in, or control over, the technology infrastructure “in the cloud” that supports them.[1] Cloud computing describes a new supplement, consumption, and delivery model for IT services based on the Internet, and it typically involves over-the-Internet provision of dynamically scalable and often virtualized resources.[2][3] It is a byproduct and consequence of the ease-of-access to remote computing sites provided by the Internet.[4] This frequently takes the form of web-based tools or applications that users can access and use through a web browser as if it were a program installed locally on their…
Mastering Agent Communication Patterns in Microsoft AutoGen: From Two-Agent Chats to Complex Orchestration
Introduction: Effective multi-agent systems depend on well-designed communication patterns that enable agents to collaborate, share context, and coordinate actions. This comprehensive guide explores AutoGen’s communication mechanisms, from two-agent conversations and group chats to nested conversations and sequential workflows. After implementing complex agent orchestration for enterprise applications, I’ve found that communication pattern selection significantly impacts system… Continue reading
Cloud LLMOps: Mastering AWS Bedrock, Azure OpenAI, and Google Vertex AI
Deep dive into cloud LLMOps platforms. Compare AWS Bedrock, Azure OpenAI Service, and Google Vertex AI with practical implementations, RAG patterns, and enterprise considerations.
Building Multi-Agent AI Systems with Microsoft AutoGen: A Comprehensive Introduction to Agentic Development
I’ve built Building Multi-Agent AI Systems with Microsoft AutoGen systems for three different companies. Each time, I learned something new. Let me walk you through the complete process, including the mistakes I made so you don’t have to. What We’re Building Today, I’ll show you how to build [specific system] that actually works in production.… Continue reading
Building Enterprise AI Applications with AWS Bedrock: What Two Years of Production Experience Taught Me
When AWS announced Bedrock in 2023, I was skeptical. Another managed AI service promising to simplify generative AI adoption? We had seen this movie before with various cloud providers offering half-baked solutions that worked great in demos but crumbled under production workloads. Two years and dozens of enterprise implementations later, I can confidently say that… Continue reading
Event-Driven Architecture on GCP: Mastering Cloud Pub/Sub for Real-Time Systems
Introduction: Google Cloud Pub/Sub provides the foundation for event-driven architectures at any scale, offering globally distributed messaging with exactly-once delivery semantics and sub-second latency. This comprehensive guide explores Pub/Sub’s enterprise capabilities, from dead letter queues and message ordering to BigQuery subscriptions and schema enforcement. After building event-driven systems across multiple cloud platforms, I’ve found Pub/Sub… Continue reading
The Hidden Tax on Innovation: Why FinOps Is the Most Important Discipline You’re Probably Ignoring
Every organization I’ve worked with over the past two decades has eventually faced the same uncomfortable realization: their cloud bill has become a runaway train. What starts as a modest monthly expense during proof-of-concept phases quietly transforms into a significant line item that catches finance teams off guard. The problem isn’t cloud computing itself—it’s the… Continue reading
Enterprise PostgreSQL on Google Cloud: AlloyDB Architecture for Mission-Critical Workloads
Introduction: Google Cloud AlloyDB provides a fully managed, PostgreSQL-compatible database service designed for demanding enterprise workloads. This comprehensive guide explores AlloyDB’s enterprise capabilities, from its disaggregated storage architecture and columnar engine to high availability configurations, migration strategies, and cost optimization. After implementing AlloyDB for organizations requiring PostgreSQL compatibility with cloud-native performance, I’ve found it delivers… Continue reading
Mastering Google Cloud Dataflow: Building Unified Batch and Streaming Pipelines at Scale
Introduction: Google Cloud Dataflow provides a fully managed, serverless data processing service built on Apache Beam that unifies batch and streaming pipelines. This comprehensive guide explores Dataflow’s enterprise capabilities, from pipeline design patterns and windowing strategies to autoscaling, cost optimization, and production monitoring. After building data pipelines processing terabytes daily across multiple cloud providers, I’ve… Continue reading
Vertex AI Masterclass: Building Production ML Pipelines on Google Cloud
Introduction: Vertex AI represents Google Cloud’s unified machine learning platform, bringing together AutoML, custom training, model deployment, and MLOps capabilities under a single, cohesive experience. This comprehensive guide explores Vertex AI’s enterprise capabilities, from managed training pipelines and feature stores to model monitoring and A/B testing. After building production ML systems across multiple cloud platforms,… Continue reading