https://yennj12.js.org/yennj12_blog_V4/tags/aws/Recent content in AWS on YennJ12 Engineering BlogHugo -- gohugo.ioen-usSat, 04 Jul 2026 12:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/ai-fde-essential-guide-part3-zh/Tue, 26 May 2026 17:01:52 +0900https://yennj12.js.org/yennj12_blog_V4/posts/ai-fde-essential-guide-part3-zh/前言 企業級 AI 整合與部署是 AI FDE 最具挑戰性的工作之一。需要處理複雜的企業架構、安全合規要求、數據整合與系統可靠性問題。本文將深入探討雲端平台部署策略、企業安全框架、RAG 架構設計與數據管道建構等核心技術。 1. 雲端平台部署策略 Google Cloud Platform (GCP) 深度整合 Vertex AI 生產部署： 1from google.cloud import aiplatform 2from google.cloud.aiplatform import gapic 3import yaml 4 5class GCPAIDeploymentManager: 6 def __init__(self, project_id: str, region: str = "us-central1"): 7 self.project_id = project_id 8 self.region = region 9 10 # 初始化 Vertex AI 11 aiplatform.init( 12 project=project_id, 13 location=region, 14 staging_bucket=f"gs://{project_id}-ml-staging" 15 ) 16 17 def deploy_custom_model(self, model_config: dict): 18 """部署客製化模型到 Vertex AI""" 19 20 # 創建容器映像 21 container_spec = { 22 "image_uri": model_config["container_image"], 23 "env": [ 24 {"name": "MODEL_NAME", "value": model_config["model_name"]}, 25 {"name": "MODEL_VERSION", "value": model_config["version"]}, 26 {"name": "BATCH_SIZE", "value": str(model_config.https://yennj12.js.org/yennj12_blog_V4/posts/crypto-quantitative-trading-part3-production-deployment/Sat, 24 Jan 2026 22:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/crypto-quantitative-trading-part3-production-deployment/Deploy cryptocurrency trading strategies to production. Master walk-forward analysis, parameter optimization, live trading integration, real-time monitoring, and machine learning enhancements. Complete production-ready system with AWS deployment and comprehensive risk controls.https://yennj12.js.org/yennj12_blog_V4/posts/kubernetes-autoscaling-complete-guide-part3-hands-on-hpa-demo/Sun, 09 Nov 2025 16:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/kubernetes-autoscaling-complete-guide-part3-hands-on-hpa-demo/Part 3 of the Kubernetes Autoscaling series: Hands-on tutorial demonstrating Horizontal Pod Autoscaler with a real Apache-PHP application. Includes complete AWS CDK infrastructure code, Kubernetes manifests, load testing, and step-by-step deployment guide.https://yennj12.js.org/yennj12_blog_V4/posts/auto-agent-system-part4-production-zh/Sat, 04 Jul 2026 12:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/auto-agent-system-part4-production-zh/「在我電腦上跑得起來」和「能給一群人用」之間,隔著四道牆: 你看得到它在做什麼嗎(可觀測性)?它打包起來多大、部署多快(image)? 它能自動擴縮、掛了會自己重啟嗎(部署)?誰能用、能用什麼由誰決定(權限)? 這一篇,就是 agent_auto_system 翻過這四道牆的過程。 前三篇我們把系統的「能力」講完了:架構(Part 1)、可靠性引擎(Part 2)、實戰任務(Part 3)。這一篇談的是另一個維度——生產化(productionization):讓這套系統能被真實地、多人地、可維運地跑起來。四個主題,對應四個 merged PR。 一、Langfuse 可觀測性:在唯一的漏斗上掛 trace 對應 PR #19:feat(harness): add Langfuse LLM-observability integration Part 2 我們反覆強調:LLM 的「錯」不是當機,而是品質退化——HTTP 200,但答案是編的。你需要一種能看見「品質」的監控,這就是 LLM 可觀測性,而 Langfuse 是這個領域的代表工具。 這個 PR 最漂亮的地方,是它的 PR 描述本身就是一堂架構課: 「CrewAI 1.x 直接呼叫各家原生 provider SDK(不走 litellm),所以要把 Langfuse 掛在 executor——這個已經知道 model、tokens、cost、eval score、status 的唯一漏斗。」 拆解這句話為什麼重要: 很多人以為的 Langfuse 接法: 在「LLM 呼叫的那一行」自動攔截(靠 litellm 之類的中介層) 但 CrewAI 1.x 直接打原生 SDK,沒有那個中介層可攔 │ ▼ 聰明的做法:不在「呼叫點」攔,而在「執行點」記 │ ▼ executor 是所有任務的必經之路,而且它手上早就有: model + tokens + cost + eval score + status → 在這裡發一條 trace,一次到位、還帶品質分數 ┌─────────────────────────────────────────────────┐ │ executor.https://yennj12.js.org/yennj12_blog_V4/posts/sentiment-driven-stock-trading-aws-cdk-twitter/Sat, 24 Jan 2026 14:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/sentiment-driven-stock-trading-aws-cdk-twitter/Build an intelligent US stock trading system using AWS CDK that analyzes real-time X.com posts, performs sentiment analysis with ML models, and executes trades based on social media sentiment for configured stocks like TSLA, GOOG, and more.https://yennj12.js.org/yennj12_blog_V4/posts/bitcoin-trading-system-aws-cdk-ml-predictions/Sat, 24 Jan 2026 10:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/bitcoin-trading-system-aws-cdk-ml-predictions/Build a production-ready automated Bitcoin trading system using AWS CDK that integrates ML models from Bedrock and HuggingFace for price prediction and executes trades based on real-time market events.https://yennj12.js.org/yennj12_blog_V4/posts/centralized-grafana-prometheus-monitoring-aws-cdk/Sat, 17 Jan 2026 11:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/centralized-grafana-prometheus-monitoring-aws-cdk/Comprehensive guide to architecting a production-ready centralized Prometheus + Grafana monitoring platform using AWS CDK that aggregates metrics from multiple services, clusters, and infrastructure components with federation, remote storage, and advanced alerting.https://yennj12.js.org/yennj12_blog_V4/posts/ai-music-generation-aws-cdk-infrastructure/Sat, 17 Jan 2026 09:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/ai-music-generation-aws-cdk-infrastructure/Complete guide to architecting a production-ready AI music generation platform on AWS using CDK, comparing SageMaker and Bedrock approaches with detailed pros, cons, and implementation strategies for generating music from text prompts.https://yennj12.js.org/yennj12_blog_V4/posts/deploying-apache-superset-production-aws-cdk-ecs-fargate/Sat, 10 Jan 2026 11:00:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/deploying-apache-superset-production-aws-cdk-ecs-fargate/Comprehensive guide to architecting a highly available, production-grade Apache Superset deployment using ECS Fargate, RDS PostgreSQL, and AWS CDK for enterprise business intelligence at scale.https://yennj12.js.org/yennj12_blog_V4/posts/aws-dynamodb-complete-guide-optimization/Mon, 29 Sep 2025 10:02:35 +0800https://yennj12.js.org/yennj12_blog_V4/posts/aws-dynamodb-complete-guide-optimization/Introduction Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. This comprehensive guide explores DynamoDB’s architecture, data structures, indexing strategies, and advanced optimization techniques to achieve maximum performance for your applications. DynamoDB Architecture Overview Core Architecture Components graph TB subgraph "DynamoDB Service Architecture" APP[Application Layer] SDK[AWS SDK] API[DynamoDB API] subgraph "DynamoDB Core" AUTH[Authentication & Authorization] ROUTER[Request Router] METADATA[Metadata Service] subgraph "Storage Layer" PARTITION1[Partition 1] PARTITION2[Partition 2] PARTITION3[Partition 3] PARTITIONN[Partition N] end subgraph "Index Layer" GSI[Global Secondary Indexes] LSI[Local Secondary Indexes] end end subgraph "Infrastructure" SSD[SSD Storage] REPLICATION[Multi-AZ Replication] BACKUP[Automated Backups] end end APP --> SDK SDK --> API API --> AUTH AUTH --> ROUTER ROUTER --> METADATA ROUTER --> PARTITION1 ROUTER --> PARTITION2 ROUTER --> PARTITION3 ROUTER --> PARTITIONN PARTITION1 --> SSD PARTITION2 --> SSD PARTITION3 --> SSD PARTITIONN --> SSD SSD --> REPLICATION REPLICATION --> BACKUP DynamoDB vs Traditional Databases Feature DynamoDB Traditional RDBMS MongoDB Data Model Key-Value & Document Relational Tables Document Schema Schema-less Fixed Schema Flexible Schema Scaling Horizontal (Auto) Vertical (Manual) Horizontal (Manual) Consistency Eventually Consistent ACID Transactions Configurable Query Language PartiQL & APIs SQL MongoDB Query Language Performance Single-digit millisecond Variable Variable Management Fully Managed Self-Managed Self/Managed Options DynamoDB Data Structures Primary Key Structures DynamoDB supports two types of primary keys:https://yennj12.js.org/yennj12_blog_V4/posts/aws-vpc-complete-guide-enterprise-networking/Mon, 29 Sep 2025 08:35:54 +0800https://yennj12.js.org/yennj12_blog_V4/posts/aws-vpc-complete-guide-enterprise-networking/Introduction Amazon Virtual Private Cloud (VPC) is the foundation of AWS networking, providing isolated virtual networks within the AWS cloud. This guide explores VPC types, enterprise network design patterns, VPC peering strategies, and practical Java implementations for production environments. AWS VPC Fundamentals What is AWS VPC? AWS VPC lets you provision a logically isolated section of the AWS Cloud where you can launch AWS resources in a virtual network that you define.https://yennj12.js.org/yennj12_blog_V4/posts/aws-load-balancer-complete-guide-comparison/Mon, 29 Sep 2025 08:28:29 +0800https://yennj12.js.org/yennj12_blog_V4/posts/aws-load-balancer-complete-guide-comparison/🎯 Introduction AWS Load Balancers are critical components for building highly available, fault-tolerant, and scalable applications in the cloud. They distribute incoming traffic across multiple targets, ensuring optimal resource utilization and system reliability. This comprehensive guide explores all AWS Load Balancer types, their unique features, and when to use each one for maximum effectiveness. Understanding the nuances between Application Load Balancer (ALB), Network Load Balancer (NLB), Gateway Load Balancer (GWLB), and Classic Load Balancer (CLB) is essential for architecting robust cloud solutions that can handle varying traffic patterns and requirements.https://yennj12.js.org/yennj12_blog_V4/posts/nyc-taxi-big-data-pipeline-spark-kafka-streaming/Sat, 27 Sep 2025 10:00:00 +0000https://yennj12.js.org/yennj12_blog_V4/posts/nyc-taxi-big-data-pipeline-spark-kafka-streaming/Complete guide to building a production-ready data engineering pipeline for processing NYC taxi trip records using Apache Spark, Kafka streaming, Hadoop ecosystem, and AWS cloud infrastructure.https://yennj12.js.org/yennj12_blog_V4/posts/building-production-kubernetes-platform-aws-eks-cdk/Sat, 30 Aug 2025 15:19:09 +0800https://yennj12.js.org/yennj12_blog_V4/posts/building-production-kubernetes-platform-aws-eks-cdk/Deep dive into architecting a comprehensive Kubernetes platform on AWS EKS with integrated data processing, monitoring, and observability using infrastructure as code.https://yennj12.js.org/yennj12_blog_V4/posts/scalable-wordpress-ecs-fargate-architecture/Sun, 10 Aug 2025 16:08:16 +0800https://yennj12.js.org/yennj12_blog_V4/posts/scalable-wordpress-ecs-fargate-architecture/Comprehensive guide to deploying production-ready WordPress on AWS ECS Fargate, exploring containerization strategies, infrastructure decisions, and scalability patterns for high-traffic content management systems.https://yennj12.js.org/yennj12_blog_V4/posts/building-serverless-url-shortener-aws-cdk/Sun, 10 Aug 2025 15:55:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/building-serverless-url-shortener-aws-cdk/Deep dive into designing and building a production-ready URL shortener using AWS serverless services, exploring architectural tradeoffs, and implementing with AWS CDK.https://yennj12.js.org/yennj12_blog_V4/posts/building-centralized-logging-opensearch-aws-cdk/Sun, 15 Dec 2024 14:30:00 +0800https://yennj12.js.org/yennj12_blog_V4/posts/building-centralized-logging-opensearch-aws-cdk/Deep dive into architecting a production-ready centralized logging solution using OpenSearch, Kinesis Data Firehose, and AWS CDK for comprehensive Kubernetes cluster observability.