📋 JayJay's DevOps Diaries ..

Chronicling my journey through Cloud Native Infrastructure.. one step and tool at a time...

Jun 15, 2026 - 5 minute read - Linux AWS Study Notes

AWS Solutions Architect Certification – Consolidated Study Notes

Before you proceed: Like my other articles, these notes started as my own personal study material. I fed them to AI only for better flow, aesthetics, and to fill in small gaps. While the final result looks refined, it is not purely AI‑generated.

I wrote all the core content myself, following the ThinkCloudy AWS Solutions Architect curriculum and using specific YouTube tutorials as referenced below.

If you’d prefer to view the unadulterated version of my notes, they are found here

AWS QUICK REFERENCE GUIDE

Once again, these documents are currently incomplete as I am actively consolidating and adding more content as I progress through my studies.

Thanks for your understanding.

📝 My Background & Journey

For over a decade, I have worked across various roles as a Linux Systems Adminstrator, DevOps Engineer and Site Reliability Engineer (SRE). Throughout this time, I have designed, built, and maintained enterprise‑grade cloud infrastructure across major platforms including AWS, GCP, and Azure.

I have worked extensively with AWS over the years, and I’m confident in my hands‑on skill level and practical experience. However, one gap I’ve always wanted to close is earning the AWS Certified Solutions Architect – Associate certification along side other professional IT certification and that is exactly what I am working toward now.

To structure my learning, I have partnered with ThinkCloudy, an online training provider delivering one‑to‑one coaching covering the full AWS Solutions Architect curriculum, from fundamentals to advanced design principles.

Alongside my formal classes, I am supplementing my learning with:

  • Curated YouTube tutorials (including a few video below)
  • PDF cheat sheets and quick reference guides
  • Exam‑style practice questions
  • Hands‑on lab work

I have compiled these consolidated notes from my lessons, research, and self‑study — organizing everything into one place for easy revision, future reference, and exam preparation.

🎥 Primary Reference Video:

ENTIRE AWS SOLUTION ARCHITECT ASSOCIATE CERTIFICATION IN 1 HOUR!

Above is a video, I would used to structure and validate core concepts and service attributes. I would type them out, then feed it to AI for enhancements and Aesthetics

☁️ Core AWS Services & Key Attributes

🖥️ Amazon EC2 – Elastic Compute Cloud

Definition: Virtual servers in the cloud — resizable compute capacity to run workloads.

Key Features

  • Scaling Options:
    • Scale up/down: Change instance size (more CPU/RAM)
    • Scale in/out: Add or remove instances horizontally
  • Instance Types: Optimized for different workload requirements
  • Pricing Models:
    • On‑Demand: Pay‑as‑you‑go, no commitment
    • Reserved Instances: 1‑ or 3‑year term — significant discount
    • Spot Instances: Bid on spare capacity — lowest cost (up to 90% off)
    • Savings Plans: Flexible pricing model — commitment to spend, across regions/services
  • Networking: Works within your VPC; supports Elastic IPs, public/private addressing
  • Security:
    • Key Pairs: Secure SSH/RDP access
    • Security Groups: Stateful firewall rules at instance level
  • Monitoring: Integrated with Amazon CloudWatch for metrics, logs, and alarms
  • Storage Options:
    • EBS: Persistent block storage
    • Instance Store: Ephemeral storage — lost on stop/termination

EC2 Instance Families & Optimization

  • General Purpose (T2, T3, M5): Balanced compute, memory, and networking — ideal for web servers, small databases, dev/test
  • Compute Optimized (C5): High‑performance processors — batch processing, media transcoding, high‑performance web servers
  • Memory Optimized (R5): Large memory footprint — in‑memory databases, real‑time analytics
  • Storage Optimized (I3, D2): High disk throughput and IOPS — NoSQL, data warehouses, large‑scale databases
  • Accelerated Computing (P3, G4): GPUs/FPGAs — machine learning, graphics rendering, high‑performance computing
  • Specialized: High‑memory or high‑storage variants for very large workloads

Additional Capability

  • Auto Scaling: Automatically add/remove instances based on demand or schedule — maintains performance and cost efficiency

📦 Amazon S3 – Simple Storage Service

Definition: Object storage for storing and retrieving any amount of data, at any time, from anywhere.

Core Characteristics

  • Durability: 99.999999999% (11 9’s) — designed to survive data centre failures
  • Scalability: Unlimited storage capacity; grows automatically
  • Use Cases: Backup & restore, data lakes, big data analytics, static website hosting, content storage
  • Security & Compliance:
    • Access control (IAM policies, bucket policies, ACLs)
    • Encryption (at rest: SSE‑S3 / SSE‑KMS / SSE‑C; in transit: SSL/TLS)
    • Versioning & Object Lock — protection against accidental deletion or modification
    • Compliance programs: HIPAA, PCI‑DSS, GDPR, and more
  • Lifecycle Management: Automatically move data between tiers or expire objects to reduce costs
  • Data Transfer:
    • Transfer Acceleration: Fast uploads via CloudFront edge network
    • AWS Snowball / Snowmobile: Physical devices for petabyte‑scale offline transfer
    • AWS Direct Connect: Private, high‑speed network connection
  • Integration: Native integration with almost all AWS services (Lambda, Athena, Redshift, CloudFront, etc.)

S3 Storage Classes – Choose by Access Pattern

  1. S3 Standard: Frequent access — high durability & availability
  2. S3 Standard‑IA: Infrequent access — lower cost, same resilience
  3. S3 One Zone‑IA: Infrequent, non‑critical data — stored in single AZ; lower cost
  4. S3 Intelligent‑Tiering: Automatically moves data between access tiers based on usage
  5. S3 Glacier Flexible Retrieval: Long‑term archive — retrieval from minutes to hours
  6. S3 Glacier Deep Archive: Lowest cost — long‑term retention (12+ months); retrieval in 12–48 hours

🗄️ Amazon RDS – Relational Database Service

Definition: Fully managed relational database service — automates administration tasks.

  • Supported Database Engines
    • MySQL
    • PostgreSQL
    • MariaDB
    • Oracle Database
    • Microsoft SQL Server
    • Amazon Aurora (AWS‑built, high‑performance, compatible with MySQL & PostgreSQL)

Key Managed Features

  • Automated Provisioning & Patching: No manual OS or database software updates
  • Backups: Automated daily snapshots + point‑in‑time recovery (up to 35 days)
  • High Availability:
    • Multi‑AZ Deployment: Synchronous standby in another Availability Zone — automatic failover if outage occurs
    • Enhanced durability and uptime SLA
  • Scaling:
    • Compute: Resize instance class
    • Storage: Scale up automatically or on demand
  • Monitoring: CloudWatch metrics, Enhanced Monitoring, and Performance Insights
  • Security: Encryption at rest (KMS), encryption in transit, IAM authentication, VPC isolation