For years, integrating AI agents with enterprise data meant writing brittle, custom OpenAPI schemas and complex integration logic. In 2026, the open-source Model Context Protocol (MCP) acts as the ‘USB-C for AI.’ Here is the architectural retrospective on securely deploying MCP Servers via AWS Serverless to connect Amazon Bedrock and Q Developer instantly to secure proprietary data.
Read more →Category: Architecture
Amazon Nova Models: The Honest 15-Month Enterprise Evaluation
When AWS launched the Amazon Nova foundation models, the pressing question was simple: Can this replace Anthropic Claude in production? 15 months later, the enterprise architecture data is clear. Nova Micro dominates latency routing, Nova Lite owns mass multimodal extraction, but tiering up to Claude for deep frontier reasoning remains the optimal cost-performance strategy. Here is the operational reality of the Nova family in 2026.
Read more →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 →Amazon Bedrock Data Automation: Intelligent Document Processing Without the Pipeline Plumbing
Intelligent Document Processing (IDP) used to mean brittle pipelines of OCR, specific regular expressions, and custom Lambdas. Bedrock Data Automation changes the paradigm: declare a schema via a Blueprint, and let generative AI extract structured data from messy, unstructured multi-modal inputs. Here is the practitioner evaluation of migrating from Textract pipelines to BDA.
Read more →Amazon S3 Tables & Apache Iceberg: Native Lakehouse in S3 — 14 Months Later
Amazon S3 Tables promised to eliminate the operational scaffolding of Apache Iceberg on S3 — automatic compaction, native REST catalog, managed snapshot lifecycle. Fourteen months after the re:Invent 2024 announcement, this is the enterprise practitioner assessment: what teams migrated from traditional S3 + Glue Catalog setups, the Lake Formation column masking gap that affects regulated workloads, and the migration decision framework for data engineering teams evaluating the switch.
Read more →Amazon EKS Auto Mode: How AWS Finally Solved the Node Management Problem
EKS Auto Mode reached GA in January 2025, promising to eliminate worker node management overhead from Kubernetes operations. Fourteen months later, this is the practitioner verdict: what Auto Mode actually manages, where the Karpenter relationship stands, the real migration path from Managed Node Groups, honest cost benchmarks, and the specific workload categories for which Auto Mode is not the answer.
Read more →