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Deep technical articles and analysis.
Claude Code on AWS — 企业 AI 编码完全指南
2026 年，AI 编码已经从"锦上添花"变成了"基础设施"。Anthropic 的 Claude Code 正在以惊人速度席卷企业开发者市场——年化收入 $25 亿+，企业客户数已超 OpenAI。这篇文章从市场格局、产品能力、企业架构、成本分析到竞品对比，帮你一文搞懂 Claude Code on AWS 的全貌。
Claude Code on AWS — 企业培训内容
Claude Code 企业培训完整内容：为何选择 Claude、功能特性与用法、AWS Bedrock 企业价值、单人月成本估算、AI 编码工具对比。涵盖市场地位、技术领先、商业验证、Agentic 工作循环、Token 消耗原理、Prompt Caching 机制、权限模型、SDLC 全覆盖等关键内容。
VOD Deep Dive Part 1: Video Fundamentals — What Is a Video, Really?
The first installment of our 12-part VOD streaming series. Learn what video actually is at the byte level — pixels, resolution, frame rates, bitrate, I/P/B frames, GOP, color spaces, and HDR.
VOD Deep Dive Part 10: QoE Metrics — How to Measure What Users Actually Feel
QoE vs QoS, six core metrics (VST, RBR, VSF, EBVS, VPF, Avg Bitrate), data pipelines, multi-dimensional drill-down, troubleshooting cases, and when to buy vs build.
VOD Deep Dive Part 11: End-to-End Workflow — From Upload to Playback
The complete 10-step VOD production pipeline: upload, content moderation, probe, transcode, package, publish, CDN pre-warm, orchestration with Step Functions and Temporal, disaster recovery.
VOD Deep Dive Part 12: Building VOD on AWS — Services, Architecture, and Costs
Complete AWS VOD reference: MediaConvert, MediaPackage, CloudFront, S3, Step Functions, SPEKE DRM integration, Terraform IaC, real cost breakdowns, common pitfalls, and a production roadmap.
VOD Deep Dive Part 2: Video Codecs — Why a 4K Movie Fits in 5 GB
How video compression works, why H.264 still dominates, when to choose H.265 or AV1, per-title encoding, VMAF quality metrics, and hands-on ffmpeg examples.
VOD Deep Dive Part 3: Audio Fundamentals — Making Sound Small
How digital audio works: sampling rates, bit depth, channels, AAC vs Opus vs Dolby Atmos, multi-language tracks, loudness normalization, and practical ffmpeg recipes.
VOD Deep Dive Part 4: Container Formats — .mp4 Is Not a Codec
Containers vs codecs, MP4 internals (Box structure), the faststart trap, fragmented MP4, CMAF for unified HLS+DASH, segment length trade-offs, and subtitle formats.
VOD Deep Dive Part 5: Streaming Protocols — How HLS and DASH Actually Work
Why progressive download fails, how HLS two-level manifests and DASH MPD work, CMAF dual-manifest best practices, LL-HLS for low latency, and when to consider WebRTC.
VOD Deep Dive Part 6: Adaptive Bitrate — How Players Auto-Switch Quality
How ABR works under the hood: throughput-based, buffer-based (BBA), BOLA, MPC, and Pensieve algorithms. Plus practical engineering advice for bitrate ladders and short-form video.
VOD Deep Dive Part 7: CDN Distribution — Why It's Fast Everywhere
CDN architecture (Edge/Shield/Origin), caching strategies, request collapsing, signed URLs, pre-warming, JIT vs pre-packaging, multi-CDN strategies, HTTP/3, and cost estimation.
VOD Deep Dive Part 8: DRM Content Protection — Why Netflix Can't Be Screen-Recorded
Widevine, FairPlay, PlayReady explained. CENC/CBCS unified encryption, license flow, L1/L2/L3 security levels, HDCP, SPEKE integration, and lightweight protection for short-form video.
VOD Deep Dive Part 9: Video Players — From Manifest to First Frame
What happens inside a video player: Web (MSE/EME), iOS (AVPlayer), Android (ExoPlayer/Media3), TTFF optimization, buffering strategies, lip sync, and when to build vs buy.
Subtitle Position Detection with OpenCV and Amazon Nova
A hybrid CV + LLM pipeline for automatic subtitle detection — 6 iterations to reach 83% accuracy on multilingual video.
Amazon AI Strategy 2026: Why the Biggest Player Is the Least Visible
Custom chips, global infrastructure, massive investment — yet Amazon is invisible in the AI race. Here's what's really going on.
Claude Code vs OpenClaw: 510K vs 530K Lines Source Code Showdown
After Claude Code's source leak exposed 512K lines of TypeScript, we finally get a true apples-to-apples comparison with OpenClaw.
Complete Failed Request Logging and Async Replay with CloudFront and Lambda@Edge
A dual Lambda@Edge architecture for recording full request headers and body of failed requests — WAF blocks and origin errors — without modifying origin code, with async replay from S3.
WeChat x OpenClaw: Platform Strategy in the AI Agent Era
WeChat's native OpenClaw integration signals a major shift. Why the world's largest messaging app opening up to AI agents matters.
5 Pitfalls of Logging Failed Requests with CloudFront + Lambda@Edge
We built a dual Lambda@Edge setup for full request logging on CloudFront. Here are the 5 things that went wrong.
How AI Coding Agents Actually Work: A Source Code Deep Dive
We traced the source code of Amazon Q CLI and Claude Code to understand how AI coding agents really work under the hood.
Building an Enterprise Agentic AI Platform with Kiro and AWS
We built a full AI agent platform in one week using Kiro IDE — zero hand-written code. Here's exactly how.
OpenClaw vs Claude Code: Architecture and Strategy Compared
Two AI agent products, two radically different philosophies. A deep comparison of architecture, adoption, and what's next.
OpenClaw vs Claude Code Source Code: Two AI Agent Architectures
We compared 453K lines of OpenClaw TypeScript with Claude Code's 28K lines of Markdown. The architectures couldn't be more different.
Building Real-Time AI Audio-Video with Amazon Nova
Build a low-latency multimodal AI assistant with Amazon Nova, Transcribe, Polly, and the open-source TEN framework.
Claude Code vs Cursor vs Amazon Q: One Year Honest Review
After a year of daily AI-assisted coding — what actually works, what doesn't, and which tool wins for what.
Amazon QuickSuite: Natural Language Data Analysis Guide
Connect databases, build dashboards, and query data in plain English with Amazon QuickSuite — step by step.
Big Data on AWS Deep Dive (Part 10): Full Architecture Blueprint and Cost Breakdown
The complete end-to-end architecture for a social app's data warehouse and recommendation system on AWS — every service mapped, with real monthly cost estimates and optimization strategies.
Big Data on AWS Deep Dive (Part 9): SageMaker and the ML Platform — From Training to Production
A complete tour of SageMaker AI: Studio notebooks, Feature Store, Training Jobs, real-time Endpoints, Model Monitor, and how it all fits into the recommendation system MLOps workflow.
Big Data on AWS Deep Dive (Part 8): Online Feature Stores — DynamoDB, ElastiCache, and OpenSearch k-NN
How recommendation systems serve features at inference time: DynamoDB for user features, ElastiCache for hot caching, OpenSearch k-NN for vector recall, and Neptune for graph retrieval.
Big Data on AWS Deep Dive (Part 7): Recommendation System Fundamentals — Funnel, Two-Tower, and PIT
Understand the recommendation system funnel (recall → pre-rank → rank → re-rank), two-tower retrieval architecture, and why Point-in-Time correctness matters for training samples.
Big Data on AWS Deep Dive (Part 6): End-to-End Data Pipeline — From Source to Feature Store
Connect all the dots: trace a click event from client SDK through API Gateway, MSK, Firehose, S3, warehouse layers (ODS→DWD→DWS→ADS), to DynamoDB for real-time serving.
Big Data on AWS Deep Dive (Part 5): EMR, Glue ETL, Flink, and Pipeline Orchestration
Compare EMR Serverless, Glue ETL, Managed Flink, and choose the right compute engine. Then orchestrate data pipelines with MWAA (Airflow) and Step Functions.
Big Data on AWS Deep Dive (Part 4): Glue Catalog, Athena, and Lake Formation
How AWS Glue Data Catalog acts as the central directory for your data lake, and how Athena queries Parquet and Iceberg tables on S3 with serverless SQL.
Big Data on AWS Deep Dive (Part 3): Data Ingestion — DMS, Zero-ETL, Firehose, and MSK
Four data sources, four ingestion pipelines — learn CDC with DMS, Aurora Zero-ETL, Kafka on MSK, and Firehose micro-batching to land data into your S3 data lake.
Big Data on AWS Deep Dive (Part 2): S3, Parquet, and Apache Iceberg Explained
Master the storage foundation of modern data lakes — S3 object storage, Parquet columnar format, and how Iceberg adds ACID transactions to files on S3.
Big Data on AWS Deep Dive (Part 1): Data Lakes, Warehouses, and the Lakehouse Revolution
Understand the core big data concepts — data lake vs. data warehouse vs. lakehouse, OLTP vs. OLAP, and why modern analytics architectures converge on S3.
How to Build AI Agents for Ad Creative Generation
Automate ad copywriting, image, and video production with Strands Agents and Amazon Bedrock. A practical, code-first guide.
How to Build a RAG System with LangChain and Elasticsearch
A hands-on guide to building Retrieval Augmented Generation — from vector embeddings to context-enhanced LLM answers.
How to Build an AI Video Course Generator with Python
Turn PowerPoint slides into narrated video courses using LLMs, text-to-speech, and FFmpeg — fully automated.
How to Design a Full-Site Search Engine with Elasticsearch
Multi-source indexing, CDC sync, permission-aware search, hot keywords, and typeahead — a complete Elasticsearch architecture guide.
Building a Knowledge Base Search Engine with FSCrawler and Elasticsearch
Index PDFs, Word docs, and scanned files into Elasticsearch with FSCrawler. Covers OCR, custom mappings, and production setup.
Adding a Unique Index to a 15-Million-Row MySQL Table: A Production War Story
We added a unique index to a 15M-row live table and caused an outage. Here's what went wrong and the right way to do it.
DNS Deep Dive: From First Principles to Kubernetes
Understand DNS from dig traces to CoreDNS in Kubernetes. A practitioner's guide to debugging DNS in containers.
Building a Distributed Job Scheduler in Go
Design and ship a production task scheduler with Go, Machinery, Redis, and cron. Covers distributed locking and retry strategies.
How to Build API Monitoring with Grafana and Elasticsearch
Set up production API monitoring from scratch — Elasticsearch data source, Lucene queries, Grafana panels, and alerting rules.