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Welcome!

Hello Folks, Lawrence served as Cloud Support Engineer at Amazon Web Service

Focus on:

  • Amazon Direct Connect
  • Amazon VPN
  • Amazon ELB
  • Amazon Global Accelerator
  • Amazon Route53
  • Amazon WAF
  • Amazon CloudWatch
  • Amazon ECS
  • Amazon EKS
  • AWS Cloudformation
  • AWS CDK
  • AWS CodeCommit
  • AWS CodeBuild
  • AWS CodeDeploy

Contact Me📱

K.JDong | Youtube K.JDong | Twitter K.JDong | Telegram

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Lawrence Chen's Projects

2021-aws-certified-sap icon 2021-aws-certified-sap

It is for someone who interested in high-level architecting knowledge on AWS, I passed on 2021 08/16

2022-azure-az-104-certification icon 2022-azure-az-104-certification

An Azure administrator often serves as part of a larger team dedicated to implementing an organization's cloud infrastructure. A candidate for this exam should have at least six months of hands-on experience administering Azure, along with a strong understanding of core Azure services, Azure workloads, security, and governance. In addition, this role should have experience using PowerShell, Azure CLI, Azure portal, and Azure Resource Manager templates.

2022-cpp-learning-path icon 2022-cpp-learning-path

This is a project I started specifically for myself to learn C++ programming language, to record my daily learning process and the problems I encountered.

2nugoodshopping icon 2nugoodshopping

This is my side-project for someone who has been tortured by not knowing where to put second-hand clothes

aerial-imagery icon aerial-imagery

Data Science Research Project: Map poverty using satellite images.

alexademolab icon alexademolab

This demo is for alexa dev to get start they first serverless repo

amazon-ec2-user-guide icon amazon-ec2-user-guide

The open source version of the Amazon EC2 User Guide for Linux. To submit feedback or requests for changes, submit an issue or make changes and submit a pull request.

amazon-ecs-nodejs-microservices icon amazon-ecs-nodejs-microservices

Reference architecture that shows how to take a Node.js application, containerize it, and deploy it as microservices on Amazon Elastic Container Service.

amazon-sagemaker-examples icon amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

aws-cdk icon aws-cdk

The AWS Cloud Development Kit is a framework for defining cloud infrastructure in code

aws-cli icon aws-cli

Universal Command Line Interface for Amazon Web Services

aws-modern-application-workshop icon aws-modern-application-workshop

A tutorial for developers that want to learn about how to build modern applications on top of AWS. You will build a sample website that leverages infrastructure as code, containers, serverless code functions, CI/CD, and more.

aws-sagemaker icon aws-sagemaker

In this tutorial, you will learn how to use Amazon SageMaker to build, train, and deploy a machine learning (ML) model. We will use the popular XGBoost ML algorithm for this exercise. Amazon SageMaker is a modular, fully managed machine learning service that enables developers and data scientists to build, train, and deploy ML models at scale.

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