COMPUTE SERVICES – DETAILED GIST
Amazon EC2
EC2 gives you virtual machines in the cloud. You choose the OS, CPU, RAM, storage, and networking.
You manage updates, patches, scaling logic, and security groups.
Used when you need full control over the server, custom software, or predictable compute workloads.
EC2 Auto Scaling
This service monitors your EC2 fleet and automatically adds or removes instances based on metrics like CPU or request count.
It helps you handle traffic spikes without manual intervention and saves money by scaling down when demand drops.
Tightly integrates with load balancers.
Elastic Load Balancing (ALB, NLB)
Load balancers distribute incoming traffic across multiple EC2 instances, containers, or IPs.
ALB works at Layer 7 (HTTP/HTTPS) and supports path-based or host-based routing.
NLB works at Layer 4 (TCP/UDP), is extremely fast, and is used for high-performance, low-latency workloads.
This improves fault tolerance and availability.
AWS Lambda
Lambda runs code in response to events without provisioning servers.
You upload a function, choose runtime, and AWS handles execution, scaling, patching, and availability.
It automatically scales to handle millions of requests.
Best for APIs, automation, data processing, scheduled tasks, and microservices.
AWS Elastic Beanstalk
A platform that deploys applications (Java, Node, Python, PHP, Go, Docker).
You upload code, and Beanstalk creates EC2 instances, load balancers, autoscaling, and monitoring.
You can override configs but generally it’s suited for developers who don’t want to manage infrastructure.
Amazon Lightsail
Simplified compute service with predictable monthly pricing.
Good for small websites, WordPress blogs, Minecraft servers, hobby apps, or simple databases.
Comes with preconfigured OS + software stacks.
AWS Batch
Manages batch computing jobs that need processing power.
It automatically provisions compute resources and schedules jobs efficiently.
Used for simulations, media rendering, big compute workloads.
AWS Outposts
AWS rack installed in your on-prem data center.
You can run AWS services (EC2, EBS, EKS) locally but with the same AWS APIs and tools.
Used when you need low-latency local processing or data residency.
AWS Serverless Application Repository
A catalog of prebuilt Lambda-based applications and components that you can deploy directly.
Useful for quickly adding serverless features without building from scratch.
AWS Wavelength
Brings AWS compute to telecom networks for ultra-low latency apps (gaming, AR/VR, IoT).
Used when milliseconds matter.
AWS Local Zones
AWS mini-regions placed closer to large cities.
Used for workloads needing low latency but not full Outposts.
CONTAINERS – DETAILED GIST
Amazon ECS (Elastic Container Service)
AWS’s native container orchestration service.
You define tasks (containers + config) and ECS schedules them on EC2 or Fargate.
It integrates tightly with IAM, ALB/NLB, CloudWatch, and ECR.
Good when you want a simpler alternative to Kubernetes while staying inside AWS.
Amazon EKS (Elastic Kubernetes Service)
Managed Kubernetes control plane.
AWS hosts and manages the Kubernetes API server, etcd, and control-plane components.
You manage worker nodes or use Fargate for serverless pods.
Ideal when you want portability (Kubernetes standard) or already know K8s.
AWS Fargate
Serverless compute engine for containers.
You run containers without launching EC2 instances.
Works with ECS and EKS.
AWS handles patching, provisioning, scaling, and security of underlying servers.
Use cases: microservices, lightweight APIs, event-driven container apps.
Amazon ECR (Elastic Container Registry)
Private container image registry fully managed by AWS.
Stores Docker images and integrates with ECS, EKS, CodeBuild, and CI/CD pipelines.
Handles vulnerability scanning and encryption.
AWS App Mesh
Service mesh for microservices running on ECS, EKS, EC2.
Provides traffic control, observability, and consistent communication.
Helps with retries, circuit breaking, service discovery, and monitoring.
Useful when you have many microservices and want centralized communication control.
AWS Cloud Map
Service discovery tool for microservices.
Services register themselves, and Cloud Map provides names and health checks.
Useful for large distributed systems.
AWS Copilot
Command-line tool to simplify deployment of containerized applications on ECS + Fargate.
Not deeply asked in exams but good for practical DevOps use.
NETWORKING & CONTENT DELIVERY – DETAILED GIST
Amazon VPC (Virtual Private Cloud)
Your private isolated network inside AWS.
You choose IP ranges, subnets (public/private), route tables, NACLs, and security groups.
It’s the backbone for almost all AWS services.
You control how your resources communicate with the internet, on-prem networks, and each other.
Subnets (Public + Private)
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Public subnet connects to the internet through an Internet Gateway.
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Private subnet stays isolated unless you use NAT.
Used to create secure, multi-tier architectures (web → app → database layers).
Route Tables
Tell subnets where to send traffic.
Every subnet must be associated with a route table.
Essential for controlling flow between VPC, subnets, NAT, IGW, TGW, etc.
Internet Gateway (IGW)
Allows communication between your VPC and the public internet.
Only subnets with IGW routes can be public.
NAT Gateway
Let instances in private subnets access the internet (for updates, APIs) without exposing them publicly.
Highly available and fully managed.
VPC Peering
Direct connection between two VPCs.
Good for small-scale, one-to-one communication.
No transitive routing.
Transit Gateway
A central hub that connects multiple VPCs, accounts, and on-prem data centers.
Replaces complex VPC peering meshes.
Used for large multi-VPC architectures.
AWS Direct Connect
A dedicated physical fiber line from your data center to AWS.
Lower latency, stable bandwidth, and more secure than VPN over the internet.
Often used by enterprises.
VPN (Site-to-Site / Client VPN)
Site-to-site: Connect your on-prem network to AWS over the public internet via encrypted tunnel.
Client VPN: Users connect individually to AWS resources securely.
PrivateLink
Lets you access AWS services, SaaS services, or your own services privately without internet.
Uses VPC endpoints (Interface Endpoints).
Great for secure internal communication.
VPC Endpoints
Private connections to AWS services without using the internet.
Two types:
-
Interface Endpoint (ENIs, PrivateLink)
-
Gateway Endpoint (S3, DynamoDB)
Reduces latency and increases security.
AWS Global Accelerator
Routes traffic over AWS’s high-speed global network instead of the public internet.
Improves performance and gives static anycast IPs for your application.
Helps with global users.
Amazon CloudFront
AWS CDN that caches your content at edge locations worldwide.
Speeds up websites, APIs, videos, and downloads.
Works well with S3, ALB, Lambda@Edge, and Shield.
Used to reduce latency, improve security, and absorb DDoS attacks.
AWS WAF (Web Application Firewall)
Applied on CloudFront, ALB, or API Gateway.
Blocks common web exploits like SQL injection or XSS.
Uses rules or managed rule sets.
AWS Shield
DDoS protection service.
-
Standard is free and protects against common attacks.
-
Advanced gives enhanced protection and 24/7 response.
CloudFront + Route 53 get strongest protection.
Network Firewall
Managed firewall inside your VPC.
Controls outbound and inbound traffic with deep packet inspection.
Good for enterprises needing strict security.
Route 53
AWS’s DNS service.
Used for:
-
Domain registration
-
DNS routing
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Health checks
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Failover
Supports routing policies like weighted, latency, failover, and geolocation.
High availability because it’s built across many edge locations.
Elastic Load Balancing (repeated for context)
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ALB: HTTP/HTTPS, path routing, host routing, works with microservices
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NLB: Ultra-fast, millions of requests/sec, TCP/UDP
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CLB: Legacy, rarely used today
Load balancers help distribute traffic and improve fault tolerance.
AWS Cloud WAN
Manages global wide area networks across multiple regions and branches.
Enterprises use it to unify global connectivity in a single AWS-controlled network.
AWS App Mesh (Networking layer for microservices)
Controls traffic routing between microservices.
Adds features such as retries, circuit breaking, and detailed telemetry.
Used with ECS/EKS/EC2 microservices.
STORAGE SERVICES – DETAILED GIST
Amazon S3 (Simple Storage Service)
Object storage for storing files, images, backups, logs, videos, datasets and application assets.
It’s designed for 11 nines durability and extreme scalability.
Data is stored as objects in buckets, and you access them through URLs or APIs.
You can configure lifecycle policies, encryption, versioning, cross-region replication, and storage classes.
S3 integrates deeply with CloudFront, Lambda, Athena, Glue, and most AWS services.
Why it’s important: core storage service + heavily tested in exams.
S3 Storage Classes
Different cost-performance tiers based on access frequency:
- Standard (frequent access)
- Standard-IA (infrequent)
- One Zone-IA (single AZ)
- Intelligent Tiering (auto moves data)
- Glacier Flexible Retrieval
- Glacier Deep Archive
Lifecycle rules automatically shift data to cheaper tiers.
S3 Glacier & Glacier Deep Archive
Cold storage for long-term archiving with extremely low cost.
Not meant for frequent access.
Retrieval can take minutes to 12 hours depending on class.
Used for compliance, backups, and historic data.
Amazon EBS (Elastic Block Store)
Block storage volumes attached to EC2 instances.
Behaves like a virtual hard drive.
Supports different volume types for performance (gp3, io1, st1).
Used for operating systems, databases, and low-latency workloads.
Provides snapshots (backups) stored in S3.
EBS Snapshots
Point-in-time backups of EBS volumes.
Incremental and stored in S3.
Used for disaster recovery, replication, and AMI creation.
Amazon EFS (Elastic File System)
Fully managed network file system for Linux workloads.
Automatically scales as you add/remove files.
Shared across multiple EC2 instances, containers, or on-prem via Direct Connect.
Ideal for web servers, CMS, shared storage, and multi-AZ workloads.
Key property: multi-AZ by default with high durability.
Amazon FSx Family
Managed file systems optimized for specific workloads:
FSx for Windows File Server
Fully managed Windows file system with SMB protocol.
Used by Windows applications needing native Windows file features.
FSx for Lustre
High-performance, low-latency file system for big data, HPC, and ML training.
Often paired with S3.
FSx for NetApp ONTAP
Enterprise-grade file system supporting NFS, SMB, iSCSI.
Used for migration of enterprise workloads.
FSx for OpenZFS
POSIX-compliant file system with high performance and snapshot features.
AWS Backup
Centralized backup service for AWS resources.
Supports EC2, EBS, RDS, DynamoDB, EFS, FSx, and on-prem backups.
Automates backup plans, retention rules, vaults, and compliance controls.
Useful when you need audit-ready, managed backup at scale.
AWS Snow Family
Physical devices for transferring huge amounts of data when network upload is slow.
Snowcone
Small device for edge computing + transferring few TBs.
Snowball Edge
Rugged device with compute + storage.
Used for data migration (tens of TB) and edge processing.
Snowmobile
A literal 45-foot shipping container for petabyte-scale transfer.
Used when you need to migrate entire data centers.
AWS Storage Gateway
Hybrid storage service that connects on-prem applications to AWS storage.
Three types:
- File Gateway – SMB/NFS shares → backed by S3
- Volume Gateway – Block storage with EBS snapshots
- Tape Gateway – Virtual tapes → backed by S3/Glacier
Used heavily in enterprise migrations.
Amazon DataSync
Fast data transfer service for copying data between on-prem servers, S3, EFS, FSx.
10x faster than regular copy tools.
Great for large-scale migrations.
AWS Transfer Family
Managed SFTP/FTP/FTPS server backed by S3 or EFS.
Used when clients or companies require file transfer protocols.
DATABASE SERVICES – DETAILED GIST
Amazon RDS (Relational Database Service)
Fully managed SQL database service.
Supports MySQL, PostgreSQL, MariaDB, Oracle, SQL Server.
AWS handles patching, backups, snapshots, replicas, and failover.
You choose instance size, storage, and AZ deployment.
Why people use RDS:
You get the power of SQL without managing servers manually.
Perfect for OLTP applications, websites, backend apps, and internal systems.
RDS Multi-AZ
Creates a synchronous replica in another AZ.
If the primary fails, RDS automatically fails over to the standby.
Ensures high availability, not scaling.
RDS Read Replicas
Asynchronous read-only copies of your primary database.
Used to offload read traffic.
Can exist across regions for global apps.
Important: They don’t provide automatic failover.
Amazon Aurora
AWS’s own high-performance relational database.
Compatible with MySQL and PostgreSQL, but up to 5x faster.
Storage automatically scales up to 128 TB.
Data is replicated across 6 copies in 3 availability zones.
Aurora comes in two forms:
- Aurora Serverless (auto-scaling DB, good for unpredictable workloads)
- Aurora Provisioned (more control + performance)
Ideal for enterprise apps, financial systems, SaaS platforms.
Amazon DynamoDB
Fully managed NoSQL key-value and document database.
Single-digit millisecond latency at any scale.
Automatically scalable, serverless, and pay-per-request.
Data is replicated across multiple AZs by default.
Used for:
- high-speed apps
- gaming
- e-commerce carts
- IoT
- real-time apps DynamoDB Streams enable event-driven workflows.
DAX (DynamoDB Accelerator)
In-memory cache for DynamoDB.
Gives microsecond response times.
Used when DynamoDB performance alone is not enough.
Amazon ElastiCache (Redis / Memcached)
In-memory caching service.
Improves performance by storing frequently accessed data in RAM.
Two engines:
- Redis – advanced features (pub/sub, streams, persistence)
- Memcached – simple, fast cache
Often used with:
- databases (reduces load)
- APIs
- high-traffic web apps
- session management
Amazon Redshift
A fast, scalable data warehouse used for analytical workloads (OLAP).
Optimized for large datasets and complex SQL queries across millions of rows.
Integrates with S3 via Redshift Spectrum for big data querying.
Used for BI dashboards, reporting, analytics, and big data pipelines.
Amazon Neptune
Graph database optimized for storing and querying highly connected data.
Supports two graph models:
- Property Graph
- RDF/SPARQL
Use cases:
- social networks
- fraud detection
- recommendation engines
- knowledge graphs
Amazon DocumentDB
Managed MongoDB-compatible document store.
Used when teams want MongoDB syntax but need AWS-managed reliability.
Works well for:
- JSON-heavy workloads
- content management
- catalogs
- user profiles
Amazon Keyspaces (Apache Cassandra)
Fully managed, serverless Cassandra-compatible NoSQL database.
Used for wide-column applications and massive scale workloads.
You get:
- no servers
- pay per request
- high availability by default
Often used by large-scale IoT, time-series, and large distributed apps.
Amazon Timestream
Time-series database optimized for sensor, IoT, app monitoring, and telemetry data.
Automatically manages data lifecycle (recent data stored in memory, old data in cost-efficient storage).
Use cases:
- IoT devices
- application metrics
- industrial telemetry
Amazon MemoryDB
Redis-compatible primary database, not just cache.
Stores data in memory for ultra-fast performance but adds durability with multi-AZ storage.
Used when Redis speed is needed with database reliability.
Amazon QLDB
Quantum Ledger Database.
Provides immutable, cryptographically verifiable transaction logs.
Used when you need tamper-proof audit history.
Typical use cases:
- banking
- supply chain
- compliance systems
Database Migration Tools
AWS DMS (Database Migration Service)
Migrates databases to AWS with minimal downtime.
Supports:
- homogeneous migrations (MySQL → MySQL)
- heterogeneous migrations (Oracle → PostgreSQL)
Schema Conversion Tool (SCT)
Converts database schemas during migration.
SECURITY, IDENTITY & COMPLIANCE – DETAILED GIST
AWS IAM (Identity and Access Management)
This is the core service for authentication and authorization in AWS.
You manage:
- Users
- Groups
- Roles
- Policies (JSON)
IAM decides who can access what and what they can do.
It works on least-privilege and is global (not region-specific).
Key features:
- MFA
- Access keys
- IAM roles for EC2, Lambda, ECS tasks
- Permission boundaries
- Identity-based and resource-based policies
IAM is foundational for everything on AWS.
IAM Roles
Temporary permissions given to AWS services or external identities.
Used when you don’t want hardcoded credentials.
Examples:
- EC2 role → gives an instance access to S3
- Lambda role → lets functions call DynamoDB
- SSO role → gives employees temporary console access
IAM Policies
JSON documents defining what actions are allowed or denied.
Attached to users, groups, or roles.
Two major types:
- AWS managed
- Customer managed (best for granular control)
AWS Cognito
Handles user sign-up, login, authentication, and identity federation for your applications.
Components:
- User Pools – user database + signup/login + MFA
- Identity Pools – get temporary AWS credentials for users
Used when you need secure login without building your own authentication backend.
Common use cases:
- mobile apps
- SaaS products
- websites with login systems
AWS KMS (Key Management Service)
Manages encryption keys (KMS keys).
You can generate, rotate, store, and control keys.
Integrated with almost all AWS services:
- S3
- EBS
- RDS
- DynamoDB
- Lambda
- SQS
- Secrets Manager
Supports symmetric and asymmetric keys.
AWS never exposes the plaintext key.
Used for: encryption, compliance, secure-by-default architectures.
AWS Secrets Manager
Stores sensitive data such as:
- database passwords
- API keys
- tokens
It can automatically rotate secrets (for RDS and others).
You retrieve secrets securely via API or environment variables.
More advanced and automated than Parameter Store.
SSM Parameter Store
Stores configuration values and secrets (optionally encrypted with KMS).
Cheaper than Secrets Manager but lacks automated rotation.
Common for storing:
- environment variables
- app configs
- small secrets
Used heavily in CI/CD and system automation.
AWS WAF (Web Application Firewall)
Protects against Layer 7 attacks:
SQL injection, cross-site scripting, bot traffic, app layer threats.
Applied at:
- CloudFront
- ALB
- API Gateway
- AppSync
Uses rule groups (managed or custom).
Essential for securing APIs and web apps.
AWS Shield
DDoS protection service.
Two tiers:
- Shield Standard – automatic, free, protects CloudFront, Route 53, ALB
- Shield Advanced – 24/7 DDoS response team, cost protection, deeper detection
Used heavily for large public-facing systems.
AWS CloudHSM
Dedicated hardware security module cluster under your control.
Gives full control over encryption keys.
Used for highly regulated industries:
- banking
- government
- healthcare
- organizations with PKI requirements
More complex than KMS but offers stronger compliance.
Amazon GuardDuty
Intelligent threat detection and continuous monitoring service.
It analyzes logs from:
- CloudTrail
- VPC Flow Logs
- DNS Logs
Detects unusual behavior like:
- compromised IAM credentials
- malware behavior
- suspicious API calls
- unexpected network flows
Very important for security posture.
Amazon Inspector
Automated vulnerability scanner for:
- EC2
- containers (ECR images)
- Lambda
Scans for:
- CVEs
- insecure configurations
- network reachability
Useful for DevSecOps workflows.
Amazon Macie
Scans S3 buckets to find sensitive data such as:
- PII
- credit card numbers
- personal details
Uses machine learning to classify data.
Helps with compliance audits.
Amazon Detective
Helps investigate security issues by analyzing data from GuardDuty, CloudTrail, and VPC logs.
Builds graphs that show relationships between events.
Used by security teams to understand the root cause of incidents.
AWS Security Hub
Central dashboard that aggregates findings from:
- GuardDuty
- Inspector
- Macie
- IAM Access Analyzer
- Partner tools (CrowdStrike, Palo Alto)
Provides a single place for security compliance checks.
Very useful for enterprise governance.
IAM Access Analyzer
Identifies resources that are publicly accessible or shared with other accounts.
Helps detect misconfigured policies.
AWS Certificate Manager (ACM)
Manages SSL/TLS certificates for free.
Used with:
- CloudFront
- ALB
- API Gateway
Handles automated renewal, making HTTPS setup easy.
Directory Services
AWS managed Active Directory.
Used when you need Windows authentication integration.
ANALYTICS SERVICES – DETAILED GIST
Amazon Athena
Serverless interactive query service that lets you query data directly from S3 using SQL.
You don’t need servers, clusters, or databases.
Just point Athena to your S3 bucket and run SQL queries.
Great for:
- log analysis
- quick data exploration
- ad-hoc queries
- analyzing CloudTrail logs
Powered by Presto under the hood.
AWS Glue
Serverless ETL and data catalog service.
Glue provides:
- Crawlers – scan S3 and auto-detect schema
- Data Catalog – central metadata store
- Glue ETL Jobs – transform data (PySpark/Python)
- Glue Studio – visual ETL tool
Essential for building data lakes.
Frequently used with Athena, EMR, and Redshift.
Amazon EMR (Elastic MapReduce)
Managed cluster platform for big data processing.
Runs frameworks like:
- Spark
- Hadoop
- Hive
- Presto
You choose instance types, cluster size, and scaling options.
Used for:
- big data analytics
- data pipelines
- ML preprocessing
- log processing
- massive distributed workloads
Can integrate with S3 as storage (decoupled architecture).
Amazon Kinesis – Real-Time Data Platform
Kinesis is for streaming data — logs, events, clicks, IoT signals.
Four major services:
1. Kinesis Data Streams
Real-time stream ingestion service.
Producers send data → consumers process it in near real-time.
Used for:
- analytics dashboards
- fraud detection
- clickstream processing
- logs & metrics
2. Kinesis Data Firehose
Fully managed delivery service for streaming data.
Automatically sends incoming data to:
- S3
- Redshift
- OpenSearch
- Splunk
Firehose runs without servers and scales automatically.
Good for log ingestion.
3. Kinesis Data Analytics
Run SQL or Java/Flink applications on real-time Kinesis streams.
Used for:
- real-time dashboards
- anomaly detection
- live metric transformations
4. Kinesis Video Streams
Streams video from cameras and devices to AWS for playback, ML, or analytics.
Amazon Redshift
AWS’s data warehouse for performing analytical queries on structured data at scale.
Optimized for OLAP workloads, complex joins, aggregations, and large datasets.
Key features:
- Columnar storage
- Massively parallel processing (MPP)
- Redshift Spectrum (query S3 directly)
Used for BI dashboards, reporting, and analytics workloads.
Integrates with:
- QuickSight
- Glue
- S3
- Kinesis
Amazon OpenSearch Service
Managed search and analytics engine based on Elasticsearch / OpenSearch.
Used for:
- log analytics
- full-text search
- monitoring dashboards
- application observability
Often paired with Logstash or Kinesis Firehose.
AWS QuickSight
BI dashboard service like Power BI or Tableau.
Creates charts, dashboards, and reports from data in:
- S3
- Redshift
- Athena
- RDS
- DynamoDB
Can be embedded into apps.
Pay-per-session pricing is cost-effective.
AWS Lake Formation
Helps build and secure data lakes quickly on S3.
Handles:
- permissions
- access control
- metadata
- ingestion
- governance
Simplifies the complex security model for data lakes.
AWS Data Exchange
Marketplace for buying or sharing datasets securely.
Used when you need third-party datasets (financial, geospatial, etc.)
AWS Glue DataBrew
No-code data preparation tool.
Helps clean, normalize, and transform data visually.
AWS Clean Rooms
Enables secure data collaboration without sharing raw data.
Useful for advertising and analytics where data privacy matters.
APPLICATION INTEGRATION – DETAILED GIST
These services help applications communicate, pass messages, trigger workflows, integrate events, and connect SaaS applications.
Let’s break each one down properly.
Amazon SQS (Simple Queue Service)
A fully managed message queue that decouples applications.
Producers send messages → SQS stores them → consumers process them asynchronously.
Key points:
- Highly scalable and reliabl
- Messages are stored redundantly across AZs
- Consumers pull messages (not pushed)
- Prevents request overload on backend services
- Supports Standard Queue (high throughput) and FIFO Queue (ordering + exactly-once)
Use cases:
- Decoupling microservices
- Buffering workloads
- Job processing systems
- Offloading heavy tasks (image processing, ML pipelines) SQS ensures that systems don’t break under load.
Amazon SNS (Simple Notification Service)
A pub/sub messaging service.
One message → multiple subscribers receive it.
Subscribers can be:
- SMS
- Mobile push
- HTTP endpoints
- Lambda
- SQS queues
Great for sending alerts or distributing messages to multiple systems.
Use cases:
- Fan-out patterns (SNS → multiple SQS queues)
- Alerts/notifications
- Triggering workflows in multiple systems
SNS is about notifications, SQS is about queues.
Amazon EventBridge
Event bus for routing events between services and applications.
You define rules based on incoming events → EventBridge forwards them to targets.
Targets include:
- Lambda
- Step Functions
- SQS
- SNS
- API Gateway
- EC2 / ECS tasks
- SaaS apps (Zendesk, Stripe, Auth0)
Use cases:
- Event-driven architectures
- Automated workflows
- Application monitoring
- SaaS integration
EventBridge is like the brain of event-driven cloud systems.
AWS Step Functions
Workflow orchestration service.
You break down a process into multiple steps and define how each step executes.
Supports:
- sequential steps
- parallel execution
- retries
- wait states
- branching logic
Each step can call:
- Lambda
- ECS tasks
- DynamoDB
- Glue
- SageMaker
- SNS / SQS
- API Gateway
Used for:
- long-running workflows
- microservice orchestration
- ML pipelines
- data processing pipelines
Step Functions helps you replace complex state machines in code with a visual workflow.
Amazon MQ
Managed message broker for enterprise systems using:
- ActiveMQ
- RabbitMQ
Important for organizations that already depend on traditional messaging protocols:
- JMS
- AMQP
- MQTT
- STOMP
Why it’s used:
- You don’t rewrite legacy systems
- AWS manages patching and scaling
- Smooth migration from on-prem to cloud
Unlike SQS/SNS, MQ supports long-lived connections and complex message routing.
Amazon AppFlow
Fully managed data integration service.
Moves data securely between SaaS apps and AWS.
Supports integrations with:
- Salesforce
- Slack
- Google Analytics
- Zendesk
- ServiceNow
- Marketo
- S3
- Redshift
Use cases:
- Syncing SaaS data into S3 for analytics
- Automating marketing data flows
- Sending updates from business apps to AWS
Best when you need no-code/low-code automation.
Amazon SWF (Simple Workflow Service)
Legacy workflow service.
Generally replaced by Step Functions, but still exists.
Used for:
- Complex, long-running human + machine workflows
- Systems needing manual approval steps Not heavily tested now, but good to know.
AWS AppConfig (part of SSM)
Used for application configuration management.
Roll out config changes safely with:
- validation
- gradual rollout
- rollback mechanisms
Useful in microservices and large distributed systems.
Amazon EventBridge Scheduler
Cron-like scheduled task runner with support for millions of schedules.
Better and simpler than CloudWatch Events for scheduling jobs.
MANAGEMENT, MONITORING & GOVERNANCE – DETAILED GIST
Amazon CloudWatch
Monitoring and observability service for metrics, logs, alarms, dashboards, and events.
CloudWatch gives you:
- Metrics (CPU, memory, requests, custom metrics)
- Logs (application logs, Lambda logs, system logs)
- Alarms (trigger actions when metrics cross thresholds)
- Dashboards (visualize performance in one place)
- CloudWatch Events / EventBridge (automation based on system events)
Use cases:
- Monitor EC2, RDS, Lambda, ECS, API Gateway
- Set alarms for auto scaling
- View logs from distributed services
- Trigger actions when issues appear
CloudWatch is the central monitoring system in AWS.
AWS CloudTrail
Records every API call made in your AWS account.
Tracks:
- who called what
- from where
- what resources were affected
- whether the call succeeded
Helps with:
- security audits
- compliance
- troubleshooting
- governance
CloudTrail Logs are usually stored in S3 and analyzed using Athena.
Every exam scenario involving “track changes” means CloudTrail.
AWS Config
Tracks configuration changes in your AWS resources over time.
Shows:
- what changed
- when it changed
- who changed it
- whether it violates a compliance rule
It also supports Config Rules, which check for:
- open S3 buckets
- unencrypted EBS volumes
- unrestricted security groups
- non-compliant resources
Used for compliance, auditing, and governance.
CloudTrail = API history
Config = resource configuration history
AWS Systems Manager (SSM)
A massive suite of tools for automation and operations.
Important features:
- SSM Agent on EC2/on-prem
- Run Command – execute commands on servers without SSH
- Session Manager – SSH-less shell access to EC2 (very secure)
- Parameter Store – config and secrets
- Patch Manager – automate OS patching
- Automation – run playbooks
- Inventory – track OS/software data
- State Manager – enforce configuration policies
Used heavily by DevOps and sysadmins.
AWS Trusted Advisor
Analyzes your AWS account and gives recommendations for:
- cost optimization
- security
- performance
- fault tolerance
- service limits
Trusted Advisor is like a cloud consultant built into AWS.
Free version gives basic checks.
Premium (Business/Enterprise support) gives full checks.
AWS Organizations
Manages multiple AWS accounts centrally.
Provides:
- multi-account structure
- consolidated billing
- service control policies (SCPs)
- account-level governance
- automatic provisioning of new accounts
Helps with enterprise setups, cost control, and strong security isolation.
Exam uses:
- blocking services for accounts → SCP
- central billing → Organizations
- multi-team isolation → separate accounts
AWS Control Tower
A layer built on top of Organizations to automatically set up:
- secure multi-account environment
- logging
- guardrails
- account factory
Basically “quick start for multi-account architecture.”
Used by enterprises and organizations starting fresh on AWS.
AWS Budgets
Set budgets and receive alerts when usage or spending exceeds thresholds.
Useful for:
- monthly cost control
- preventing bill shocks
- forecasting future cost
Works with Cost Explorer and emails/SNS alerts.
AWS Cost Explorer
Visualizes and analyzes your AWS spending.
Shows:
- cost trends
- service-wise breakdown
- daily/monthly usage
- cost anomalies
Helps optimize savings (especially EC2, S3, RDS).
AWS Health Dashboard
Shows health of AWS services and how outages impact your resources.
Two types:
- Service Health Dashboard – global AWS status
- Personal Health Dashboard – impact on your specific resources
Useful for incident monitoring.
AWS License Manager
Track and manage software licenses (Windows, SQL Server, Oracle).
Helps avoid license overuse and violations.
AWS Resource Groups & Tag Editor
Organizes and manages resources based on tags.
You can search by resource type, tags, region, etc.
Useful for:
- cost allocation
- environment separation
- bulk resource updates
AWS Well-Architected Tool
Provides automated reviews of your workloads based on the 6 WA pillars:
- operational excellence
- security
- reliability
- performance efficiency
- cost optimization
- sustainability
Used for optimizing cloud architecture.
Alright bro, here’s the full MIGRATION + TRANSFER section in the same medium-depth, clean, revision-friendly format.
MIGRATION & TRANSFER SERVICES – DETAILED GIST
These services help you move databases, servers, applications, and large datasets from on-prem or other clouds into AWS.
AWS DMS (Database Migration Service)
Fully managed service to migrate databases to AWS with minimal downtime.
Supports both:
- homogeneous migrations (MySQL → MySQL, PostgreSQL → PostgreSQL)
- heterogeneous migrations (Oracle → PostgreSQL, SQL Server → Aurora)
Key features:
- Source DB stays live during migration
- Replicates ongoing changes (CDC → Change Data Capture)
- Works with on-prem, EC2, and RDS sources
Common use cases:
- migrating production databases
- switching DB engines
- offloading reporting DBs
For schema conversion → use SCT (Schema Conversion Tool) with DMS.
AWS Application Migration Service (AWS MGN)
This is the primary service for lift-and-shift migrations.
It moves:
- full servers
- VMs
- on-prem workloads
- apps running on physical, VMware, Hyper-V, or cloud VMs
How it works:
- MGN agent replicates server disk blocks to AWS
- Creates an EC2 instance identical to your original server
- Supports test cutovers & production cutovers
Replaces the old Server Migration Service (SMS).
Best for:
- migrating entire infrastructures
- as-is migrations
- disaster recovery plan
AWS DataSync
High-speed data transfer between:
- on-prem → AWS
- AWS → on-prem
- across AWS storage services (S3, EFS, FSx)
It’s 10x faster than traditional copy tools (rsync, cp).
Supports transfers to/from:
- S3
- EFS
- FSx
- SMB/NFS on-prem storage
- Snow devices
Used for:
- large migrations
- incremental syncs
- backup jobs
- hybrid workloads
AWS Snow Family
Physical devices for moving huge amounts of data when internet transfer is too slow or impossible.
1. Snowcone
Small, rugged device (8 TB).
Used for:
- small datasets
- edge computing
- remote sites or IoT deployments
2. Snowball Edge (Storage Optimized / Compute Optimized)
Larger, rugged devices (80–210 TB).
Support compute functions (EC2, Lambda) for edge processing.
Used for:
- petabyte-scale migration
- edge ML/analytics
- remote environments without stable internet
3. Snowmobile
Massive 45-foot shipping container with 100 PB capacity.
Used for full datacenter migrations.
AWS Transfer Family
Managed transfer servers supporting traditional protocols:
- SFTP
- FTP
- FTPS
Backend storage is S3 or EFS.
Use cases:
- legacy enterprise transfers
- vendor/client file uploads
- automated integrations with S3-based systems
Completely replaces on-prem SFTP servers.
AWS Migration Hub
Central dashboard to track all migration activities across:
- DMS
- MGN
- DataSync
- third-party tools
Offers:
- progress tracking
- performance insights
- migration metrics
Used in large-scale enterprise migrations to keep everything organized.
AWS SMS (Server Migration Service) (Legacy)
Old service for migrating VMs to AWS.
Now replaced by Application Migration Service (MGN).
Good to know the name for exam purposes but not used in real-world anymore.
AWS SCT (Schema Conversion Tool)
Used when moving from one DB engine to another, like:
- Oracle → PostgreSQL
- SQL Server → Aurora
- MySQL → DynamoDB
It converts:
- tables
- indexes
- functions
- stored procedures
- views
Works together with DMS.
AWS CloudEndure (Legacy / DR)
Before MGN, CloudEndure was used for disaster recovery and migration.
Still appears in older materials but mostly replaced.
MACHINE LEARNING & AI SERVICES – DETAILED GIST
These services provide ML training, inference, AI-powered APIs, and data intelligence.
Amazon SageMaker
Full end-to-end machine learning platform.
It helps you:
- prepare data
- build models
- train models
- tune hyperparameters
- deploy models
- monitor models
You can use built-in algorithms or your own code (TensorFlow, PyTorch, Scikit-Learn).
Key components:
- SageMaker Studio – ML IDE
- Training Jobs – scalable distributed training
- Inference Endpoints – deploy models at scale
- Pipeline – CI/CD for ML
- Notebook Instances – Jupyter notebooks
- Feature Store – store/reuse ML features
- Ground Truth – labeling service
SageMaker is used when teams want managed ML without building infrastructure.
Amazon Rekognition
AI service for analyzing images and videos.
Capabilities:
- object detection
- face detection
- face comparison
- label detection
- text extraction from images
- unsafe content detection
Used for:
- security cameras
- user identity verification
- image moderation
- retail analytics
Fully managed, no ML expertise needed.
Amazon Comprehend
Natural Language Processing (NLP) service.
Understands text and can find:
- sentiment (positive/negative)
- key phrases
- entities (names, places, products)
- syntax
- topics
Use cases:
- customer feedback analysis
- social media analysis
- document understanding
- chatbot improvement
It’s serverless and powerful for text-based workloads.
Amazon Lex
Service to build chatbots and voice bots.
Uses the same technology as Alexa.
Features:
- natural language understanding
- automatic speech recognition
- context management
- connects with Lambda
Common uses:
- customer support bots
- booking assistants
- voice interfaces
Works with Contact Center (Amazon Connect).
Amazon Polly
Text-to-speech service.
Converts text into natural-sounding audio.
Useful for:
- IVR systems
- podcasts
- accessibility features
- voice-enabled apps
Supports many languages and tones.
Amazon Transcribe
Speech-to-text service.
Converts audio into accurate text.
Handles:
- multiple speakers
- noisy backgrounds
- custom vocabulary
Used for:
- call center transcription
- video subtitles
- meeting notes
- voice analytics
Often paired with Comprehend for sentiment analysis.
Amazon Translate
Language translation service.
Features:
- fast
- neural machine translation
- supports many languages
Used when you need real-time translation for apps, chats, websites.
Amazon Textract
Extracts text, tables, and form data from documents — PDFs, scans, images.
More advanced than OCR because it understands structure.
Use cases:
- invoice processing
- form automation
- ID verification
- document workflows
Often paired with Lambda or Step Functions for automated processing.
Amazon Forecast
Time-series forecasting using ML.
Same tech used by Amazon retail.
Used for:
- demand prediction
- inventory planning
- resource forecasting
You provide historical data → Forecast generates predictions.
Amazon Personalize
Creates personalized recommendations (like Amazon.com).
Used for:
- product recommendations
- movie/music suggestions
- personalized rankings
Integrates easily with websites and apps.
Amazon Kendra
Enterprise search engine powered by ML.
Can search across:
- SharePoint
- S3
- Google Drive
- databases
- internal documents
Understands natural language queries and returns relevant results.
Useful for companies with large document collections.
Amazon Fraud Detector
AI service to detect fraud in:
- online payments
- account creation
- transactions
- identity verification
You upload historical data → it learns fraud patterns.
Amazon SageMaker Ground Truth
Human-in-the-loop data labeling for ML datasets.
Can use Mechanical Turk or private workforce.
Used for creating training data for vision/NLP models.
Amazon Bedrock
Serverless platform for foundation models and generative AI.
Models from Amazon + third-party providers:
- Anthropic
- AI21
- Stability
- Meta LLaMA
- Amazon Titan models
Features:
- text generation
- chatbots
- embeddings
- summarization
- classification
- image generation
No infrastructure needed. Pay-per-use.
Lookout Services (ML-based anomaly detection)
AWS provides ML-powered “Lookout for X” services:
Lookout for Metrics
Automatically detects anomalies in time-series data.
Lookout for Vision
Detects defects in manufacturing (product quality control).
Lookout for Equipment
Predictive maintenance for industrial machines.
SERVERLESS + API SERVICES – DETAILED GIST
These services help you build serverless apps, APIs, and real-time data flows.
AWS Lambda (already covered earlier but summarizing in API context)
Runs code without servers.
Triggers come from:
- API Gateway
- S3
- DynamoDB Streams
- EventBridge
- SNS / SQS
- CloudWatch Events
Autoscaling, pay-per-invocation, and fully managed runtime.
Best for event-driven apps, automation, APIs, and microservices.
Amazon API Gateway
A fully managed service to create, publish, secure, and monitor REST APIs, HTTP APIs, and WebSocket APIs.
Key features
- integrates with Lambda, EC2, ECS, DynamoDB
- request validation
- throttling & rate-limits
- API keys and usage plans
- caching to improve performance
- IAM, Cognito, and Lambda authorizers for authentication
- can serve as the front door for microservices or serverless apps
Use cases:
- serverless APIs with Lambda
- backend for web and mobile apps
- real-time chat apps (WebSocket)
AWS AppSync
Managed GraphQL API service.
Handles data fetching for mobile/web apps in a single request using GraphQL schema.
Data sources:
- DynamoDB
- Lambda
- RDS
- Elasticsearch/OpenSearch
- HTTP APIs
Supports real-time subscriptions.
Common in modern frontend apps, SaaS dashboards, and real-time apps.
AWS Step Functions (already covered under integration but important for serverless)
Orchestrates workflows with steps, retries, branching, and sequencing.
You design flows visually, and Step Functions manage execution state.
Used for:
- serverless pipelines
- ML workflows
- ETL
- microservice workflows
Amazon EventBridge (brief recap in serverless context)
Event bus that routes events between AWS services and SaaS apps.
Used when:
- building event-driven architectures
- decoupling microservices
- triggering Lambda functions based on events
Amazon SQS + SNS (serverless messaging recap)
- SNS → broadcast notifications (push model)
- SQS → queue for processing (pull model)
Often used together in fan-out pattern.
AWS SAM (Serverless Application Model)
Framework to build serverless apps using simple config files.
Supports:
- Lambda
- API Gateway
- Step Functions
- DynamoDB
Lets you deploy full serverless stacks easily.
AWS CloudFront (Serverless Edge Logic)
With Lambda@Edge and CloudFront Functions, you can run code at global edge locations.
Used for:
- header manipulation
- redirects
- authentication
- caching control
Good for high-performance global applications.
Amazon Cognito (serverless authentication)
Fully managed signup, login, MFA, and identity federation for apps.
Often used with API Gateway + Lambda.
Serverless section done bro.
Next up:
DEVELOPER TOOLS – DETAILED GIST
These are CI/CD, code automation, version control, and DevOps tools from AWS.
AWS CodeCommit
Private Git repositories hosted on AWS.
Similar to GitHub or GitLab but fully managed inside AWS.
Integrates with CodeBuild, CodePipeline, IAM.
Used for secure enterprise source control.
AWS CodeBuild
Fully managed CI service to:
- compile code
- run tests
- build Docker images
- produce artifacts
Scales automatically and charges only for build minutes.
Often used with:
- CodePipeline
- ECR
- Lambda deployment
AWS CodeDeploy
Automates application deployments.
Supports:
- EC2
- On-prem servers
- Lambda
- ECS
Deployment types:
- in-place
- blue/green
Used for safe, automated rollouts with rollback support.
AWS CodePipeline
End-to-end CI/CD orchestration tool.
Defines workflow:
- source → build → test → deploy
Integrates with:
- CodeCommit
- GitHub
- CodeBuild
- CodeDeploy
- Lambda
- CloudFormation Used to automate full release pipelines.
AWS CodeArtifact
Managed package repository for:
- npm
- Maven
- PyPI
- NuGet
Helps teams manage dependencies securely.
AWS Cloud9
Cloud-based IDE that runs in the browser.
Has terminal, debugger, and all AWS CLI tools built-in.
Useful for:
- students
- remote teams
- serverless development
AWS X-Ray
Distributed tracing system to analyze how requests flow through applications.
Tracks:
- latency
- bottlenecks
- downstream calls
- errors in microservices
Used heavily in Lambda, API Gateway, ECS, EKS apps.
AWS CodeStar (less used now)
Unified interface for creating CI/CD project templates.
Integrates with CodeCommit, CodeBuild, CodeDeploy, CodePipeline.
Not widely used anymore but still exists.