Enterprise GenAI integrations are fatally exposed when treating foundation models like standard REST APIs. Integrating Claude 3.5 Sonnet directly to heavy UI components results in chronic HTTP timeouts. By early 2026, the industry standard relies on DynamoDB streams, EventBridge, and AWS Step Functions. Here is the practitioner blueprint for robust, asynchronous LLM orchestration at scale.
Read more →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…
Amazon Bedrock Flows vs Step Functions: When Visual AI Orchestration is the Right Answer
When Amazon Bedrock Flows debuted, it looked conspicuously like AWS Step Functions rebuilt for GenAI. 15 months later, the architectural divide is strictly enforced. Bedrock Flows handles ephemeral, cognitive prompt chains; Step Functions handles durable business transactions. This is the blueprint for the Hybrid Orchestration Pattern separating AI intent from Systemic persistence.
Read more →From AI Pilots to Production Reality: Architecture Lessons from 2025 and What 2026 Demands
A Beginning-of-Year Reflection for Enterprise Architects and Technical Leaders As we step into 2026, it’s worth pausing to reflect on the seismic shifts that defined enterprise architecture in 2025—and the hard lessons learned when AI hype met production reality. What began as breathless excitement around generative AI and LLMs has matured into a more nuanced […]
Read more →2025 in Review: The Infrastructure Readiness Lesson
2025 taught enterprise technology leaders a critical lesson: infrastructure readiness matters more than model capability. This year-end review explores platform engineering, data governance, healthcare AI breakthroughs, and five predictions for 2026.
Read more →Building Interoperable Healthcare Data Systems for AI: A Complete Guide to FHIR, Standards, and Governance
Healthcare AI fails when data remains siloed. This article explores how FHIR, SNOMED CT, and platform thinking enable interoperable healthcare data systems for AI at scale, with insights from EU, UK, and Ireland initiatives.
Read more →Azure Container Apps Dynamic Sessions: Secure Code Execution for AI Agents
AI agents that can write and execute code introduce significant security risks—from data exfiltration to resource abuse. Azure Container Apps Dynamic Sessions provides a solution: ephemeral, sandboxed execution environments that isolate agent-generated code from your production infrastructure. This comprehensive guide explores how to implement secure code execution for AI code interpreters, automated testing agents, and […]
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