Perfect.
Today is the MOST IMPORTANT day in AWS for a Data Engineer.

If IAM clicks today, AWS will never feel confusing again.

📅 DAY 2 — AWS IAM (MASTER LEVEL)

Security, Roles, and How AWS Services ACTUALLY Work

AWS IAM

🎯 DAY 2 GOAL

By the end of today, you will:

  • Fully understand Users vs Roles vs Policies
  • Know how AWS services talk to each other
  • Design production-grade IAM
  • Answer any IAM interview question confidently
  • Never hardcode credentials again (CRITICAL)

🧠 PART 1 — IAM IS NOT JUST “PERMISSIONS”

❌ Beginner thinking

IAM = permissions to access AWS

✅ Architect thinking

IAM = identity + trust + authorization

IAM answers 3 questions:

  1. WHO are you?
  2. WHAT can you do?
  3. WHERE can you do it?

🧩 PART 2 — THE 3 CORE IAM BUILDING BLOCKS

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1️⃣ IAM USER — A HUMAN

👤 What it is

  • Represents a person
  • Has login / access keys

👤 Used for

  • You
  • Admins
  • CI/CD systems (sometimes)

📌 Golden rule

Humans = Users
AWS services ≠ Users ❌

2️⃣ IAM ROLE — AN AWS SERVICE

🧠 THIS IS THE BIGGEST CONFUSION POINT

👤 Role is:

  • NOT a person
  • NOT permanent
  • ASSUMED temporarily

📌 Used by

  • EC2
  • EMR
  • Glue
  • Lambda
  • Step Functions

🧠 Think:

“Role = job profile for an AWS service”

3️⃣ IAM POLICY — PERMISSION RULEBOOK

📜 JSON document that says:

  • Allow / Deny
  • Which actions
  • On which resources

Example:

{
  "Effect": "Allow",
  "Action": "s3:GetObject",
  "Resource": "arn:aws:s3:::my-bucket/*"
}

🧠 PART 3 — TRUST POLICY vs PERMISSION POLICY

(THIS IS INTERVIEW GOLD)

🔐 Trust Policy

WHO is allowed to assume this role?

Example:

{
  "Effect": "Allow",
  "Principal": {
    "Service": "ec2.amazonaws.com"
  },
  "Action": "sts:AssumeRole"
}

📌 Means:

EC2 is allowed to become this role

🔓 Permission Policy

WHAT can this role do?

Example:

{
  "Effect": "Allow",
  "Action": "s3:*",
  "Resource": "*"
}

🔥 MOST IMPORTANT LINE (MEMORIZE)

Trust policy decides WHO can assume the role
Permission policy decides WHAT the role can do

🧠 PART 4 — HOW AWS SERVICES ACCESS EACH OTHER (MAGIC EXPLAINED)

🔁 Example: Spark on EMR reading S3

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Spark Job
 → Runs on EMR
 → EMR has IAM Role
 → Role has S3 permissions
 → Access granted

🚫 No passwords
🚫 No access keys
✅ Secure, temporary credentials

🧠 PART 5 — REAL-WORLD IAM PATTERNS (DATA ENGINEER)

🔹 Pattern 1: EMR → S3

  • EMR has role: EMR-S3-Access-Role
  • Policy: Read/Write to data lake bucket

🔹 Pattern 2: Lambda → Glue

  • Lambda role:
    • glue:StartJobRun
    • logs:*

🔹 Pattern 3: Step Functions → Everything

  • Step Function role:
    • Invoke Lambda
    • Start Glue
    • Describe EMR

🧠 PART 6 — WHY HARDCODING AWS KEYS IS A CAREER KILLER

❌ Bad practice:

aws_access_key_id="ABC"
aws_secret_access_key="XYZ"

✅ Correct:

  • IAM Role
  • STS temporary credentials

📌 Interview elimination point

“We never hardcode AWS credentials; we use IAM roles.”

🧠 PART 7 — LEAST PRIVILEGE (SENIOR THINKING)

❌ Bad

"s3:*"

✅ Good

"s3:GetObject",
"s3:PutObject"

📌 Security + cost + compliance

🧪 DAY 2 MINI THINKING EXERCISE

Answer mentally:

  1. Why does Lambda use a role and not a user?
  2. Can an IAM role exist without a policy?
  3. Why are credentials temporary when using roles?

(If you want, send answers and I’ll review)

🎤 INTERVIEW STATEMENTS (USE THESE)

✔ “IAM roles provide temporary credentials via STS, which is more secure than static keys.”
✔ “Trust policy controls who can assume a role; permission policy controls allowed actions.”
✔ “AWS services should always communicate using IAM roles.”

🧠 DAY 2 MEMORY ANCHOR (SAVE THIS)

USER  = HUMAN
ROLE  = AWS SERVICE
POLICY = PERMISSION

Trust → WHO
Policy → WHAT

No Keys. Only Roles.

⏭️ DAY 3 PREVIEW — NETWORKING (ONLY WHAT YOU NEED)

Tomorrow we’ll cover:

  • VPC, Subnets, Routing
  • Public vs Private
  • Why EMR is private
  • Why Glue works without VPC
  • Networking interview traps

👉 No overload. Only data-engineer-relevant networking.

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DAY 3

We continue 🚀

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