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Fast-AWS

  • This repo covers AWS Hands-on Labs, sample architectures for different AWS services with clean demo/printscreens.

Why was this repo created?

  • It shows/maps AWS services in short with reference AWS developer documentation.
  • It shows AWS Hands-on LABs with clean demos. It focuses only AWS services.
  • It contributes to AWS open source community.
  • Hands-on lab will be added in time for different AWS Services and more samples (Bedrock, Sagemaker, ECS, Lambda, Batch, etc.)

Quick Look (How-To): AWS Hands-on Labs

These hands-on labs focus on how to create and use AWS components:

Table of Contents

Motivation

Why should we use / learn cloud?

  • Faster Development: Rapid provisioning of resources accelerates product development and testing.
  • Access to Advanced Technologies: Utilize AI, ML, big data analytics, and other tools without building infrastructure from scratch.
  • Flexibility in Work Models: Enable remote and hybrid work setups with cloud-based tools.
  • High Demand: Cloud skills are highly sought after in the job market, leading to better career opportunities and higher salaries.
  • Career Paths: Cloud knowledge is applicable in various roles, including developer, architect, data scientist, and DevOps engineer.
  • Future-Proofing Skills: Cloud is a foundational technology for emerging trends like AI, IoT, and edge computing.
  • Operational Savings: Minimized costs for hardware maintenance, upgrades, and energy consumption.
  • Scalability Without Cost Burden: Scale resources up or down based on needs, avoiding overprovisioning.
  • Global Reach: Deliver applications and services worldwide with minimal latency using cloud regions and content delivery networks.
  • Disaster Recovery: Built-in redundancy and backup solutions ensure business continuity during failures.
  • Improved Collaboration: Cloud platforms facilitate real-time collaboration across teams and geographies.
  • Comprehensive Ecosystem: Familiarize yourself with cloud providers like AWS, Azure, Google Cloud, and their services.
  • Certifications and Recognition: Earn globally recognized certifications that validate your skills.
  • Community Support: Access vast resources, communities, and forums to accelerate your learning.

Why should we use / learn AWS?

  • Industry Leader: AWS is the largest cloud provider, holding a significant market share, making AWS skills highly valuable.
  • In-Demand Certifications: AWS certifications are globally recognized and often lead to better job opportunities and higher salaries.
  • Diverse Roles: AWS knowledge applies to various roles like cloud architect, developer, DevOps engineer, and data scientist.
  • Future-Proof Career: AWS continues to innovate, ensuring longevity in its relevance and utility.
  • Extensive Services: Offers 200+ fully featured services, including computing, storage, AI/ML, analytics, IoT, and databases.
  • Custom Solutions: Provides tools for various industries like healthcare, finance, gaming, and e-commerce.
  • Comprehensive Documentation: AWS offers detailed tutorials, guides, and examples for users of all levels.
  • Active Community: Join a global network of AWS professionals, forums, and meetups for support and collaboration.
  • AWS Training: Gain access to structured training programs and certifications for systematic skill-building.
  • First-Mover Advantage: AWS has years of experience and maturity, ensuring reliability
  • Continuous Innovation: AWS consistently introduces new services and updates to meet evolving needs.

AWS Services In-Short

There are more than 200 AWS services. Popular services are listed in short.

1. Compute Services

Amazon EC2

Amazon EC2 Auto Scaling

Amazon Lightsail

AWS App Runner

AWS Batch

AWS Elastic Beanstalk

AWS Amplify

AWS Lambda

AWS Outposts

AWS Parallel Computing Service

AWS Serverless Application Repository

AWS Wavelength

2. Container Services

Amazon Elastic Container Registry

Amazon Elastic Container Service (ECS)

Amazon Elastic Kubernetes Service (EKS)

AWS App2Container

AWS App Runner

AWS Fargate

3. Storage Services

Amazon Simple Storage Service (S3)

Amazon S3 Glacier storage classes

Amazon Elastic Block Store (EBS)

Amazon Elastic File System (EFS)

Amazon FSx for Lustre

Amazon FSx for NetApp ONTAP

Amazon FSx for OpenZFS

Amazon FSx for Windows File Server

Amazon File Cache

AWS Backup

AWS Elastic Disaster Recovery (DRS)

AWS Snowball

AWS Storage Gateway

4. Database Services

Amazon Aurora

Amazon Aurora DSQL

Amazon Aurora Serverless V2

Amazon DocumentDB (with MongoDB compatibility)

Amazon DynamoDB

Amazon ElastiCache

Amazon Keyspaces (for Apache Cassandra)

Amazon MemoryDB

Amazon Neptune

Amazon RDS

Amazon Timestream

Amazon Redshift

5. Data Analytics Services

Amazon Athena

Amazon OpenSearch Service

Amazon EMR

Amazon FinSpace

Amazon Kinesis Analytics

Amazon Neptune Analytics

Amazon Data Firehose

Amazon Managed Service for Apache Flink

Amazon Managed Streaming for Apache Kafka

Amazon QuickSight

AWS Data Exchange

AWS Glue

AWS Lake Formation

6. Integration Services

AWS Step Functions

Amazon API Gateway

Amazon AppFlow

Amazon EventBridge

Amazon Managed Workflows for Apache Airflow

Amazon MQ

Amazon Simple Notification Service (SNS)

Amazon Simple Queue Service (SQS)

AWS AppSync

7. Cloud Financial Management Services

AWS Cost Explorer

AWS Billing Conductor

AWS Billing and Cost Management

8. Management & Governance Services

Amazon CloudWatch

Amazon Managed Grafana

Amazon Managed Service for Prometheus

AWS CloudFormation

AWS CloudTrail

AWS Command Line Interface

AWS Compute Optimizer

AWS Config

AWS Control Tower

AWS Health Dashboard

AWS License Manager

AWS Management Console

AWS Managed Services (MS)

AWS Organizations

AWS Proton

AWS Service Catalog

AWS Systems Manager

AWS Trusted Advisor

AWS User Notifications

AWS Well-Architected Tool

9. Security, Identity, & Compliance Services

AWS Identity and Access Management (IAM)

Amazon Cognito

Amazon Detective

Amazon GuardDuty

Amazon Inspector

Amazon Macie

Amazon Security Lake

Amazon Verified Permissions

AWS Artifact

AWS Audit Manager

AWS Certificate Manager

AWS CloudHSM

AWS Directory Service

AWS Firewall Manager

AWS Key Management Service

AWS Network Firewall

AWS Resource Access Manager

AWS Secrets Manager

AWS Security Hub

AWS Shield

AWS IAM Identity Center

AWS WAF

10. Networking Services

Amazon VPC

Amazon VPC Lattice

Amazon API Gateway

Amazon CloudFront

Amazon Route 53

AWS App Mesh

AWS Cloud Map

AWS Cloud WAN

AWS Direct Connect

AWS Global Accelerator

AWS Private 5G

AWS PrivateLink

AWS Transit Gateway

AWS Verified Access

AWS Client VPN

AWS Site-to-Site VPN

Elastic Load Balancing (ELB)

11. Migration Services

AWS Migration Hub

AWS Application Discovery Service

AWS Application Migration Service (MGN)

AWS Database Migration Service

AWS DataSync

AWS Migration Acceleration Program

AWS Optimization and Licensing Assessment

AWS Transfer Family

AWS Snowball

12. Internet of Things Services

AWS IoT Core

AWS IoT Device Defender

AWS IoT Fleet Hub for AWS IoT Device Management

AWS IoT Events

AWS IoT FleetWise

AWS IoT Greengrass

Amazon Kinesis Video Streams

FreeRTOS

Amazon Location Service

AWS Device Farm

13. Artificial Intelligence Services

Amazon Q

Amazon Bedrock

Amazon SageMaker AI

Amazon SageMaker Unified Studio

AWS App Studio

Amazon Augmented AI

Amazon CodeGuru

Amazon Comprehend

Amazon Comprehend Medical

Amazon Fraud Detector

Amazon Kendra

  • Reinvent enterprise search with ML

  • It is a managed information retrieval and intelligent search service that uses natural language processing and advanced deep learning model.

  • Unlike traditional keyword-based search, Amazon Kendra uses semantic and contextual similarity—and ranking capabilities—to decide whether a text chunk or document is relevant to a retrieval query.

  • Document: https://docs.aws.amazon.com/kendra/latest/dg/what-is-kendra.html

    image

Amazon Lex

AWS HealthLake

Amazon Personalize

Amazon Polly

Amazon Rekognition

Amazon Textract

Amazon Translate

Amazon Transcribe

AWS Hands-on Labs

HANDS-ON-01: Provisioning EC2s on VPC, Creating Key-Pair, Connecting EC2

  • This sample shows:

    • how to create Key-pairs (public and private keys) on AWS,
    • how to create EC2s (Ubuntu 20.04, Windows 2019 Server),
    • how to create Virtual Private Cloud (VPC), VPC Components (Public Subnet, Internet Gateway, Route Table) and link to each others,
    • how to create Security Groups (for SSH and Remote Desktop).
  • Go to the Hands-On:

HANDS-ON-02: Provisioning Lambda, API Gateway and Reaching HTML Page in Python Code From Browser

  • This hands-on shows:

    • how to create Lambda function with Python code,
    • how to create lambda role, policy, policy-role attachment, lambda api gateway permission, zipping code,
    • how to create api-gateway resource and method definition, lambda - api gateway connection, deploying api gateway, api-gateway deployment URL as output
    • details on AWS Lambda, API-Gateway, IAM.
  • Go to the Hands-On:

HANDS-ON-03: EBS and EFS Configuration with EC2s

  • This hands-on shows:

    • how to create EBS, mount on Ubuntu and Windows Instances,
    • how to create EFS, mount on Ubuntu Instance,
    • how to provision VPC, subnet, IGW, route table, security group.
  • Go to the Hands-On:

HANDS-ON-04: Provisioning ECR, Pushing Image to ECR, Provisioning ECS, VPC, ELB, ECS Tasks, Service on Fargate Cluster

HANDS-ON-05: Provisioning ECR, Lambda and API Gateway to run Flask App Container on Lambda

  • This hands-on shows:

    • how to create Flask-app-serverless image to run on Lambda,
    • how to create ECR and to push image to ECR,
    • how to create Lambda function, Lambda role, policy, policy-role attachment, Lambda API Gateway permission,
    • how to create API Gateway resource and method definition, Lambda - API Gateway connection, deploying API Gateway.
  • Go to the Hands-On:

HANDS-ON-06: Provisioning EKS with Managed Nodes using Blueprint and Modules

HANDS-ON-07: Provisioning CodeCommit, CodePipeline and Triggering CodeBuild and CodeDeploy Container in Lambda

  • This hands-on shows:

    • how to create code repository using CodeCommit,
    • how to create pipeline with CodePipeline, create S3 bucket to store Artifacts for codepipeline stages' connection (source, build, deploy),
    • how to create builder with CodeBuild ('buildspec_build.yaml'), build the source code, create a Docker image,
    • how to create ECR (Elastic Container Repository) and push the build image into the ECR,
    • how to create Lambda Function (by CodeBuild automatically) and run/deploy container on Lambda ('buildspec_deploy.yaml').
  • Go to the Hands-On:

SAMPLE-08: Provisioning S3 and CloudFront to serve Static Web Site

  • This hands-on shows:

    • how to create S3 Bucket,
    • how to to copy the website to S3 Bucket,
    • how to configure S3 bucket policy,
    • how to create CloudFront distribution to refer S3 Static Web Site,
    • how to configure CloudFront (default_cache_behavior, ordered_cache_behavior, ttl, price_class, restrictions, viewer_certificate).
  • Go to the Hands-On:

HANDS-ON-09: Provisioned Gitlab Runner on EC2, connection to Gitlab Server using Docker on-premise

  • This hands-on shows:

    • how to run Gitlab Server using Docker on WSL2 on-premise,
    • how to redirect external traffic to docker container port (Gitlab server),
    • how to configure on-premise PC network configuration,
    • how to run EC2 and install docker, gitlab-runner on EC2,
    • how to register Gitlab runner on EC2 to Gitlab Server on-premise (in Home),
    • how to run job on EC2 and returns artifacts to Gitlab Server on-premise (in Home).
  • Go to the Hands-On:

HANDS-ON-10: Implementing MLOps Pipeline using GitHub, CodePipeline, CodeBuild, CodeDeploy, Sagemaker Endpoint

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