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AWS Series: Multi-part series on AWS Cloud and related guidelines

In this multi-part AWS series, I intend to cover the general aspects of AWS in simple terms, the business case for cloud, some deep dives where required, migration strategy, AllOps, security by design framework, reference architectures, and/or demo, and more. I am putting up a Lego bricks approach with multiple layers (in conjunction with the OSI / TCP/IP Layer) and will be adding several Reference architectures (for Web, Batch, Mobile, Data Lake, Big Data, Machine Learning, etc) after assorting and categorizing these Lego pieces. Along the way, I will also discuss the adoption of cloud for different sizes of organizations and building a cloud for scale and how best can make it built to last and at the same time extend it to handshake with other cloud providers to enable Poly Cloud / Multi-Cloud based adoption for the organization.


I take the layering approach for designing AWS cloud. These layers are essentially divided into 4 groups (1) The Must have stack (2) The Input Stack (3) The Processing Stack and (4) The Output Stack.

AWS Cloud series includes the below which is loosely mapped to the OSI layer.

OSI & TCP / IP Layer

Part 1: Cloud Models

1. Understanding and Deep Dive into Cloud Models

Models: IAAS / PAAS / SAAS / Serverless

Deployment Models: Public cloud, Poly Cloud, Multi-Cloud, Private Cloud, Hybrid cloud, Third-party dedicated Data Centres, Shared cloud services.

2. Key differences of various cloud models

3. Migration, SLA, and AllOps of different cloud models

4. Putting a business case for cloud and why it is important?

Links to Part 1 of the Article:

Cloud Models

Business case for Cloud

Cloud Deployment Models (Part1 & Part2)

AWS Cloud Migration (Pre-cursor & Migration)

Part 2: Security Layer

This section discusses the following

1. Understanding and Deep Dive of Security Architecture

Login: IAM, Cognito, Secrets Manager, Single Sign-on, MFA, ACM

Web Apps: Guard Duty, WAF, Shield, Certificate Manager

Data: Encryption at Rest (for EBS/EFS volume, Encryption, S3 SSE), Encryption at Transit, TDE, KMS (CMK)

Firewall / ACLs: Security Groups, NACL.

Data Loss Prevention (DLP): Amazon Macie

Governance & Risk: AWS Security Hub, AWS Compliance centre

2. How to build a Security by Design framework and Security-First approach for your organization.

3. How much of a Security Layer is required for the organization

Links to Part 2 of the article:

AWS Series #2: Cloud Security Roadmap

AWS Series #2: AWS Security Layer — Login

AWS Series #2: AWS Security Layer — Network & Web Apps

AWS Series #2: AWS Security Layer — Data

AWS Series #2: AWS Security Layer — Firewall

Part 3: Infrastructure and Network Layer

1. Understanding and Deep Dive of Infrastructure and Network layer

Infra & Network: Region, VPC, Availability Zone

Request / Response: CloudFront, Route 53, API Gateway

Links: Direct Connect | Private Link | VPC Private Gateway

Gateways: Internet Gateway, Storage Gateway, Transit Gateway, VPC Customer Gateway

Load Balancer: ALB / ELB / CLB

2. How to design load balancing across different region and your customers for your organization

Part 4: Sourcing & Streaming Layer

1. Understanding and Deep Dive of sourcing and streaming layer

Sourcing: SFTP, DMS & SCT

Streaming: Kinesis Data Stream, Kinesis Firehose, Kinesis Data Analytics, Kinesis Video, MSK (Managed service Kafka), SQS

2. Distributed system architecture using Streaming

3. How you should choose a Streaming service for your organization

Part 5: Ingestion Layer

1. Understanding and Deep Dive of Ingestion layer

ETL: Glue ETL, Data Pipeline, ETL using a Step function

2. How you should choose a Ingestion layer for your organization

Part 6: Data Stack Layer

1. Understanding and Deep Dive of Database Layer

Data Stack @ AWS

Part 6a: Database Layer

RDBMS: RDS, Redshift, Snowflake (hosted)

Graph Database: Neptune

NoSQL: DynamoDB, Document DB, Elastic Cache

Query / Analysis: Redshift Spectrum, Athena, Elastic Search

Part 6b: Data Lake Layer

1. Understanding and Deep Dive of Database Layer

Sourcing & Streaming Layer, Data Lake, Querying, Visualization

Part 6c: Big Data Layer

Collection: Kinesis, Kafka | MSK, Greengrass (IoT Core), AWS Snowball, SQS, DMS, Direct Connect

Storage: EMR FS, S3, S3 Glacier, Dynamo DB, Elasticache

Processing: EMR HDFS, Lambda, AWS ML / Sage Maker, Glue, EMR, Data Pipeline.

Analysis: Athena, Elastisearch, Redshift

Visualization: QuickSight

Security: IAM, KMS

Part 6d: Data Science Layer

Amazon Sage Maker, Amazon ML, Rekognition, Polly, Texteract, Log analytics

2. Which Data Stack @ AWS should be chosen for your organization?

Data is in the center and all the applications are built around data in order to facilitate the business with performance and decision making.

Part 7: Configuration, Path, and IAC Layer

1. Understanding and Deep Dive of Configuration and IAC layer

AWS Config, Cloud Formation, Terraform (3rd party), Ansible, AWS System manager

2. Multi-Cloud and Infrastructure as code

Part 8: Application Layer

1. Understanding and Deep Dive of Application Layer

Server based: EC2 | EC2 Image Builder

Serverless: Lambda | Step Functions, Elastic Beanstalk

DevOps / CI/CD Layer: CloudGuru, Cloud9, Code Build, Code Commit, Code Deploy, Code Pipeline.

DataOps, MLOps / AIOps: on AWS using third-party solutions.

Architecture Patterns: Event-driven (Microservices), Time based, etc.,

Containers: ECS, EKS| ECR, ELK, Fargate

Part 9: Consumption Layer

1. Understanding and Deep Dive of Consumption Layer

Web App Delivery: CloudFront

Mobile Applications: Amplify

Database / Querying: Database Layer, Quicksight

Files: Data Lake (S3), Delta Share (Databricks integrated)

Part 10: Backup & Recovery Layer

1. Understanding and Deep Dive of backup and recovery Layer

AWS Backup, Amazon S3 Glacier

2. Backup and recovery for the application server and database server for your organization — best approach.

3. Multi-Cloud as backup and recovery option.

Part 11: Messaging Layer

1. Understanding and Deep Dive of messaging Layer

SNS, SES, PinPoint, Amazon Connect

2. Which is your best messaging layer for your organization

3. How to enable messaging across distributed architecture and multi-cloud / hybrid cloud architecture.

Part 12: Monitoring Layer

1. Understanding and Deep Dive of monitoring Layer

Cloud Watch, Cloud Trail, Trusted Advisor, Compute Optimize, AWS Inspector

2. How to enable distributed tracing and monitoring for microservices design pattern | Containers architecture.

3. How to enable monitoring across multi-cloud / hybrid cloud.


Link to Azure Series Multi part parent article.

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All the views expressed here are my own views and does not represent views of my firm that I work for. Data | Big Data | Cloud | ML