[Modify/Add] Add Databases & Analytics, and Other Compute Service Doc.

README.md

@@ -21,6 +21,10 @@
   - Scalability & High Availability, Vertical Scalability, Horizontal Scalability, High Availability, High Availability & Scalability For EC2, Scalability vs Elasticity (vs Agility), What is load balancing?, What’s an Auto Scaling Group?
 - [Amazon S3](./sections/s3.md)
   - S3 Use cases, Amazon S3 Overview - Buckets, Amazon S3 Overview - Objects, S3 Websites, S3 Storage Classes, S3 Object Lock & Glacier Vault Lock, Shared Responsibility Model for S3, AWS Snow Family, What is Edge Computing?, Snow Family - Edge Computing, AWS OpsHub, Hybrid Cloud for Storage, AWS Storage Gateway
+- [Databases & Analytics](./sections/databases.md)
+  - Databases Intro, Relational Databases, NoSQL Databases, Databases & Shared Responsibility on AWS, AWS RDS Overview, Amazon Aurora, Amazon ElastiCache Overview, DynamoDB, Redshift Overview, Amazon EMR, Amazon Athena, Amazon QuickSight, DocumentDB, Amazon Neptune, Amazon QLDB
+- [Other Compute Section](./sections/other_compute.md)
+  - What is Docker?, ECS, Fargate, ECR, What’s serverless?, Why AWS Lambda ?, Amazon API Gateway, AWS Batch, Batch vs Lambda, Amazon Lightsail, Lambda Summary
 
 ## Practice Exams ( dumps )
 

sections/databases.md

@@ -0,0 +1,306 @@
+# Databases & Analytics
+
+- [Databases \& Analytics](#databases--analytics)
+  - [Databases Intro](#databases-intro)
+  - [Relational Databases (SQL)](#relational-databases-sql)
+  - [NoSQL Databases](#nosql-databases)
+    - [NoSQL data example: JSON](#nosql-data-example-json)
+  - [Databases \& Shared Responsibility on AWS](#databases--shared-responsibility-on-aws)
+  - [AWS RDS Overview](#aws-rds-overview)
+    - [Advantage over using RDS versus deploying DB on EC2](#advantage-over-using-rds-versus-deploying-db-on-ec2)
+    - [RDS Deployments](#rds-deployments)
+    - [RDS Deployments: Read Replicas, Multi-AZ](#rds-deployments-read-replicas-multi-az)
+    - [RDS Deployments: Multi-Region](#rds-deployments-multi-region)
+  - [Amazon Aurora](#amazon-aurora)
+  - [Amazon ElastiCache Overview](#amazon-elasticache-overview)
+  - [DynamoDB](#dynamodb)
+    - [DynamoDB Accelerator (DAX)](#dynamodb-accelerator-dax)
+    - [DynamoDB Global Tables](#dynamodb-global-tables)
+  - [Redshift Overview](#redshift-overview)
+  - [Amazon EMR (Elastic MapReduce)](#amazon-emr-elastic-mapreduce)
+  - [Amazon Athena](#amazon-athena)
+  - [Amazon QuickSight](#amazon-quicksight)
+  - [DocumentDB (with MongoDB Compatibility)](#documentdb-with-mongodb-compatibility)
+  - [Amazon Neptune](#amazon-neptune)
+  - [Amazon QLDB](#amazon-qldb)
+  - [Amazon Managed Blockchain](#amazon-managed-blockchain)
+  - [AWS Glue](#aws-glue)
+  - [DMS - Database Migration Service](#dms---database-migration-service)
+  - [Databases \& Analytics Summary](#databases--analytics-summary)
+
+## Databases Intro
+
+- Storing data on disk (EFS, EBS, EC2 Instance Store, S3) can have its limits
+- Sometimes, you want to store data in a database…
+- You can structure the data
+- You build indexes to efficiently query / search through the data
+- You define relationships between your datasets
+- Databases are optimized for a purpose and come with different features, shapes and constraint
+- **Managed Databases**: AWS takes care of maintenance, backups, and security for databases.
+- **Benefits**: Reduced operational complexity, built-in high availability, disaster recovery, scalability, and enhanced security.
+- **Types**:
+  - **Relational Databases** (SQL)
+  - **NoSQL Databases**
+  - **Data Warehousing**
+  - **In-memory Caching**
+
+## Relational Databases (SQL)
+
+- **Structured Data**: Stored in predefined schema tables, managed with SQL.
+- **Use Cases**: Transactional applications, financial systems.
+- **Examples**: MySQL, PostgreSQL, Oracle, SQL Server, MariaDB.
+
+## NoSQL Databases
+
+- **Flexible Schema**: No predefined schema, designed for fast and scalable data storage.
+- **Use Cases**: Real-time applications, IoT, mobile apps.
+- Benefits:
+  - Flexibility: easy to evolve data model
+  - Scalability: designed to scale-out by using distributed clusters
+  - High-performance: optimized for a specific data model
+  - Highly functional: types optimized for the data model
+- **Examples**: DynamoDB, MongoDB (DocumentDB), Key-value, document, graph, in-memory, search databases
+
+### NoSQL data example: JSON
+
+- JSON is a common form of data that fits into a NoSQL model
+- Data can be nested
+- Fields can change over time
+- Support for new types: arrays, etc…
+
+```json
+{
+  "name": "Abc",
+  "age": 30,
+  "cars": [
+    "Ford",
+    "BMW",
+    "Fiat"
+  ],
+  "address": {
+    "type": "house",
+    "number": 23,
+    "street": "Abc Road"
+  }
+}
+```
+
+## Databases & Shared Responsibility on AWS
+
+| **AWS Responsibility**                      | **Customer Responsibility**                      |
+| ------------------------------------------- | ------------------------------------------------ |
+| Infrastructure management, backups, patches | Data security, encryption, access controls (IAM) |
+| Availability and failover                   | Data management, monitoring, performance tuning  |
+
+## AWS RDS Overview
+
+- **RDS (Relational Database Service)**: Fully managed service for relational databases.
+  - It’s a managed DB service for DB use SQL as a query language.
+  - Supports **MySQL**, **PostgreSQL**, **MariaDB**, **Oracle**, **SQL Server**.
+  - Handles **backup**, **patching**, **high availability** (Multi-AZ), and **scaling**.
+
+### Advantage over using RDS versus deploying DB on EC2
+
+- RDS is a managed service:
+  - Automated provisioning, OS patching
+  - Continuous backups and restore to specific timestamp (Point in Time Restore)!
+  - Monitoring dashboards
+  - Read replicas for improved read performance
+  - Multi AZ setup for DR (Disaster Recovery)
+  - Maintenance windows for upgrades
+  - Scaling capability (vertical and horizontal)
+  - Storage backed by EBS (gp2 or io1)
+- BUT you can’t SSH into your instances
+
+### RDS Deployments
+
+- **Read Replicas**: Improves read performance, **asynchronous** replication.
+- **Multi-AZ**: Automatic failover, high availability for production environments.
+- **Multi-Region**: Disaster recovery across regions, global availability.
+
+### RDS Deployments: Read Replicas, Multi-AZ
+
+| Read Replicas                       | Multi-AZ                                          |
+| ----------------------------------- | ------------------------------------------------- |
+| Scale the read workload of your DB  | Failover in case of AZ outage (high availability) |
+| Can create up to 5 Read Replicas    | Data is only read/written to the main database    |
+| Data is only written to the main DB | Can only have 1 other AZ as failover              |
+
+![Read Replicas Multi-AZ](../images/read_replicas_multi_AZ.png)
+
+### RDS Deployments: Multi-Region
+
+- Multi-Region (Read Replicas)
+  - Disaster recovery in case of region issue
+  - Local performance for global reads
+  - Replication cost
+
+![Multi-Region](../images/multi_region.png)
+
+## Amazon Aurora
+
+- **Amazon Aurora**: High-performance RDS database.
+  - Compatible with **MySQL** and **PostgreSQL**.
+  - **5x faster** than MySQL, **3x faster** than PostgreSQL.
+  - **Auto-scaling** storage up to **64 TB**.
+  - Supports **Multi-AZ** and up to **15 read replicas**.
+  - Great for **enterprise-grade** applications requiring high availability and performance.
+  - Aurora costs more than RDS (20% more) – but is more efficient
+
+## Amazon ElastiCache Overview
+
+- **ElastiCache**: In-memory data caching service.
+  - **Redis**: Advanced key-value store with replication and persistence.
+  - **Memcached**: Simple, memory-only caching service.
+  - Reduces database load and speeds up applications by **caching frequent queries**.
+  - Caches are in-memory databases with high performance, low latency
+  - AWS takes care of OS maintenance / patching, optimizations, setup, configuration, monitoring, failure recovery and backup
+
+## DynamoDB
+
+- Fully managed, serverless NoSQL database.
+- Supports key-value and document data models.
+- Automatically scales based on demand.
+- Provides high availability and durability with replication across 3 AZ
+- Millions of requests per seconds, trillions of row, 100s of TB of storage
+- Fast and consistent in performance
+- Single-digit millisecond latency – low latency retrieval
+- Integrated with IAM for security, authorization and administration
+- Low cost and auto scaling capabilities
+- Standard & Infrequent Access (IA) Table Class
+
+### DynamoDB Accelerator (DAX)
+
+- In-memory caching for DynamoDB.
+- **10x faster** read performance.  ingle-digit millisecond latency to microseconds latency – when accessing your DynamoDB tables
+- Secure, highly scalable & highly available
+- Ideal for use cases where **low-latency reads** are critical.
+
+### DynamoDB Global Tables
+
+- Multi-region replication for **global** applications.
+- **Low-latency** reads and writes across multiple regions.
+- Ensures data availability globally with **multi-master replication**.
+
+## Redshift Overview
+
+- Managed data warehousing service.
+- Optimized for **online analytical processing (OLAP)** and big data analytics.
+- Uses **columnar storage** for fast query performance.
+- 10x better performance than other data warehouses, scale to PBs of data
+- Columnar storage of data (instead of row based)
+- Supports integration with **BI tools** (QuickSight, Tableau).
+- Massively Parallel Query Execution (MPP), highly available.
+- Has a SQL interface for performing the queries.
+- Pay-per-query or **reserved instances** for cost savings.
+- Designed for **massive datasets**.
+
+## Amazon EMR (Elastic MapReduce)
+
+- Managed big data processing service.
+- Uses **Hadoop**, **Apache Spark**, and **Hive** for processing large data sets.
+- Ideal for **data transformation**, **machine learning**, and **ETL** (Extract, Transform, Load).
+- Integration with **S3**, **DynamoDB**, and **Redshift**.
+- The clusters can be made of hundreds of EC2 instances
+- EMR takes care of all the provisioning and configuration
+- Auto-scaling and integrated with Spot instances
+- Use cases: data processing, machine learning, web indexing, big data
+
+## Amazon Athena
+
+- Serverless query service
+- Use **SQL** to query structured and unstructured data stored in **S3**.
+- No infrastructure to manage, pay-per-query.
+- Supports various formats like **CSV**, **JSON**, **Parquet**, and **ORC**.
+- Pricing: $5.00 per TB of data scanned
+- Use compressed or columnar data for cost-savings (less scan)
+- Use cases: Business intelligence / analytics / reporting, analyze & query VPC Flow Logs, ELB Logs, CloudTrail trails, etc...
+- Analyze data in S3 using serverless SQL, use Athena
+
+## Amazon QuickSight
+
+- Business Intelligence (BI) tool for data visualization.
+- Serverless machine learning-powered business intelligence service to create interactive dashboards
+- Fast, automatically scalable, embeddable, with per-session pricing
+- Supports data from S3, Redshift, RDS, and other AWS data sources.
+- **Pay-per-session** pricing model for cost efficiency.
+- Use cases:
+  - Business analytics
+  - Building visualizations
+  - Perform ad-hoc analysis
+  - Get business insights using data
+
+## DocumentDB (with MongoDB Compatibility)
+
+- Managed document database, **MongoDB-compatible**.
+- DocumentDB is the same for MongoDB (which is a NoSQL database)
+- Highly scalable and durable with **Multi-AZ**.
+- Built for **JSON** document storage.
+- Aurora storage automatically grows in increments of 10GB, up to 64 TB.
+- Automatically scales to workloads with millions of requests per seconds
+- Use cases: Content management, cataloging, and mobile backends.
+
+## Amazon Neptune
+
+- Fully managed graph database
+- A popular graph dataset would be a social network
+  - Users have friends
+  - Posts have comments
+  - Comments have likes from users
+  - Users share and like posts…
+- Highly available across 3 AZ, with up to 15 read replicas
+- Build and run applications working with highly connected datasets – optimized for these complex and hard queries
+- Can store up to billions of relations and query the graph with milliseconds latency
+- Highly available with replications across multiple AZs
+- Great for knowledge graphs (Wikipedia), fraud detection, recommendation engines, social networking
+
+## Amazon QLDB
+
+- QLDB stands for ”Quantum Ledger Database”
+- A ledger is a book **recording financial transactions**
+- Fully Managed, Serverless, High available, Replication across 3 AZ
+- Used to **review history of all the changes made to your application data** over time
+- **Immutable** system: no entry can be removed or modified, cryptographically verifiable
+- 2-3x better performance than common ledger blockchain frameworks, manipulate data using SQL
+- Difference with Amazon Managed Blockchain: no decentralization component, in accordance with financial regulation rules
+
+## Amazon Managed Blockchain
+
+- Blockchain makes it possible to build applications where multiple parties can execute transactions without the need for a trusted, central authority.
+- Amazon Managed Blockchain is a managed service to:
+  - Join public blockchain networks
+  - Or create your own scalable private network
+- Compatible with the frameworks Hyperledger Fabric & Ethereum
+
+## AWS Glue
+
+- Managed extract, transform, and load (ETL) service
+- Useful to prepare and transform data for analytics
+- Fully serverless service
+- Glue Data Catalog: catalog of datasets
+  - can be used by Athena, Redshift, EMR
+
+## DMS - Database Migration Service
+
+- Quickly and securely migrate databases to AWS, resilient, self healing
+- The source database remains available during the migration
+- Supports:
+  - Homogeneous migrations: ex Oracle to Oracle
+  - Heterogeneous migrations: ex Microsoft SQL Server to Aurora
+
+## Databases & Analytics Summary
+
+- Relational Databases - OLTP: RDS & Aurora (SQL)
+- Differences between Multi-AZ, Read Replicas, Multi-Region
+- In-memory Database: ElastiCache
+- Key/Value Database: DynamoDB (serverless) & DAX (cache for DynamoDB)
+- Warehouse - OLAP: Redshift (SQL)
+- Hadoop Cluster: EMR
+- Athena: query data on Amazon S3 (serverless & SQL)
+- QuickSight: dashboards on your data (serverless)
+- DocumentDB: “Aurora for MongoDB” (JSON – NoSQL database)
+- Amazon QLDB: Financial Transactions Ledger (immutable journal, cryptographically verifiable)
+- Amazon Managed Blockchain: managed Hyperledger Fabric & Ethereum blockchains
+- Glue: Managed ETL (Extract Transform Load) and Data Catalog service
+- Database Migration: DMS
+- Neptune: graph database

sections/elb_asg.md

@@ -57,11 +57,11 @@
 
 ## Scalability vs Elasticity (vs Agility)
 
-| **Term**           | **Definition**                                                                                   |
+| **Term**        | **Definition**                                                                                                    |
-|--------------------|--------------------------------------------------------------------------------------------------|
+| --------------- | ----------------------------------------------------------------------------------------------------------------- |
-| **Scalability**     | Ability to increase or decrease the capacity to handle varying levels of traffic or load.        |
+| **Scalability** | Ability to increase or decrease the capacity to handle varying levels of traffic or load.                         |
-| **Elasticity**      | Automatically adjusts resources up or down based on the load in real-time, preventing under or over-provisioning. |
+| **Elasticity**  | Automatically adjusts resources up or down based on the load in real-time, preventing under or over-provisioning. |
-| **Agility**         | The ability to deploy and manage resources quickly and efficiently in response to changing demands. |
+| **Agility**     | The ability to deploy and manage resources quickly and efficiently in response to changing demands.               |
 
 ## What is Load Balancing?
 

sections/iam.md

@@ -38,6 +38,7 @@
 - **Users**: Represent individual identities that interact with AWS services. Users have unique credentials (username, password, access keys).
 - **Groups**: Logical grouping of users to simplify permission management.
   - Permissions assigned to a group are automatically inherited by its users.
+- Flexibility in User Management in IAM, users do not have to belong to a group, and a user can belong to multiple groups. This allows user to manage access permissions in a granular and efficient manner. For example, a user could belong to both the “QAs" group and the “Developers” group, inheriting permissions from both.
 
 | **IAM Users**                                              | **IAM Groups**                                           |
 |------------------------------------------------------------|----------------------------------------------------------|
@@ -55,6 +56,8 @@
 
 ### IAM Policies Inheritance
 
+![IAM Policies Inheritance](../images/IAM_Policies_inheritance.png)
+
 - Policies are evaluated together for a user, including:
   - **Directly attached policies**.
   - **Group policies**.

sections/other_compute.md

@@ -0,0 +1,192 @@
+# Other Compute
+
+## What is Docker?
+
+- Docker is a software development platform to deploy apps
+- Apps are packaged in containers that can be run on any OS
+- Apps run the same, regardless of where they’re run
+  - Any machine
+  - No compatibility issues
+  - Predictable behavior
+  - Less work
+  - Easier to maintain and deploy
+  - Works with any language, any OS, any technology
+- Scale containers up and down very quickly (seconds)
+
+### Where are Docker images stored?
+
+- **Docker Hub**: Centralized public repository for storing Docker images.
+- Public: Docker Hub <https://hub.docker.com/>
+- Private: **Amazon ECR (Elastic Container Registry)**: AWS service for storing, managing, and deploying container images.
+
+### Docker versus Virtual Machines
+
+- Docker is ”sort of” a virtualization technology, but not exactly
+- Resources are shared with the host => many containers on one server
+
+| **Docker Containers**                  | **Virtual Machines (VMs)**                |
+| -------------------------------------- | ----------------------------------------- |
+| Lightweight, shares the host OS kernel | Heavier, includes full OS                 |
+| Starts in seconds                      | Slower startup (minutes)                  |
+| Portable, fast scaling                 | Not as portable, more resource-intensive  |
+| Best for microservices & modern apps   | Best for running multiple OS environments |
+
+## ECS (Elastic Container Service)
+
+- Fully managed container orchestration service.
+- Supports Docker containers.
+- Launch Docker containers on AWS
+- AWS takes care of starting / stopping containers
+- **Two launch modes**: **EC2** (self-managed instances) and **Fargate** (serverless).
+- Provides integration with IAM, VPC, ELB, and ECR.
+
+## Fargate
+
+- Serverless compute engine for containers, works with ECS and EKS.
+- No need to manage EC2 instances.
+- Pay for resources used (vCPU and memory).
+- AWS just runs containers for you based on the CPU / RAM you need
+
+## ECR (Elastic Container Registry)
+
+- Fully managed Docker container registry.
+- Stores, manages, and secures Docker images.
+- Integrated with **ECS**, **EKS**, and **Fargate** for easy deployment.
+- This is where you store your Docker images so they can be run by ECS or Fargate
+
+## What’s Serverless?
+
+- No need to provision, scale, or manage servers.
+- Resources are automatically provisioned and scaled by AWS.
+- Serverless is a new paradigm in which the developers don’t have to manage servers anymore…
+- They just deploy code
+- They just deploy… functions !
+- Initially... Serverless == FaaS (Function as a Service)
+- Serverless was pioneered by AWS Lambda but now also includes anything that’s managed: “databases, messaging, storage, etc.”
+- Serverless does not mean there are no servers…
+- it means you just don’t manage / provision / see them
+- Ideal for event-driven and stateless applications.
+
+## Why AWS Lambda?
+
+- Serverless compute service to run code without managing infrastructure.
+- Executes code in response to events (e.g., API calls, file uploads).
+- Scales automatically and you only pay for usage.
+
+| EC2                                                | Lambda                                    |
+| -------------------------------------------------- | ----------------------------------------- |
+| Virtual Servers in the Cloud                       | Virtual functions – no servers to manage! |
+| Limited by RAM and CPU                             | Limited by time - short executions        |
+| Continuously running                               | Run on-demand                             |
+| Scaling means intervention to add / remove servers | Scaling is automated!                     |
+
+### Benefits of AWS Lambda
+
+- **No server management**: AWS handles the infrastructure.
+- **Automatic scaling**: Scales based on event triggers.
+- **Flexible scaling**: Runs from a few requests per day to thousands per second.
+- **Event-driven architecture**: Ideal for apps that need to respond to events.
+- Easy Pricing:
+  - Pay per request and compute time
+  - Free tier of 1,000,000 AWS Lambda requests and 400,000 GBs of compute time
+- Integrated with the whole AWS suite of services
+- Event-Driven: functions get invoked by AWS when needed
+- Integrated with many programming languages
+- Easy monitoring through AWS CloudWatch
+- Easy to get more resources per functions (up to 10GB of RAM!)
+- Increasing RAM will also improve CPU and network!
+
+### AWS Lambda Language Support
+
+- Node.js
+- Python
+- Ruby
+- Java
+- Go
+- .NET Core
+- custom runtime (via container images) (community supported, example Rust)
+- Lambda Container Image
+  - The container image must implement the Lambda Runtime API
+  - ECS / Fargate is preferred for running arbitrary Docker images
+
+### AWS Lambda Pricing: Example
+
+- Based on number of requests and execution time.
+- You can find overall pricing information here: <https://aws.amazon.com/lambda/pricing/>
+- First **1 million requests/month** are free.
+- After that, **$0.20 per million requests**.
+- **Execution duration**: $0.00001667 for every GB-second used (first 400,000 GB-seconds free per month).
+- - Pay per duration: (in increment of 1 ms)
+  - 400,000 GB-seconds of compute time per month for FREE
+  - == 400,000 seconds if function is 1GB RAM
+  - == 3,200,000 seconds if function is 128 MB RAM
+  - After that $1.00 for 600,000 GB-seconds
+- It is usually **very cheap** to run AWS Lambda so it’s **very popular**
+
+## Amazon API Gateway
+
+- Managed service for creating, publishing, and monitoring REST, HTTP, and WebSocket APIs.
+- Integrates with AWS Lambda for fully serverless APIs.
+- Serverless and scalable
+- Support for security, user authentication, API throttling, API keys, monitoring.
+- **Throttling**, **caching**, and **authorization** features built-in.
+
+## AWS Batch
+
+- Fully managed service for running batch processing workloads.
+- Dynamically provisions compute resources based on job requirements.
+- Suitable for large-scale data processing, such as machine learning and rendering tasks.
+- Efficiently run 100,000s of computing batch jobs on AWS
+- A “batch” job is a job with a start and an end (opposed to continuous)
+- Batch will dynamically launch EC2 instances or Spot Instances
+- AWS Batch provisions the right amount of compute / memory
+- You submit or schedule batch jobs and AWS Batch does the rest!
+- Batch jobs are defined as Docker images and run on ECS
+- Helpful for cost optimizations and focusing less on the infrastructure
+
+## Batch vs Lambda
+
+| **AWS Batch**                               | **AWS Lambda**                             |
+| ------------------------------------------- | ------------------------------------------ |
+| Designed for **batch processing**           | Designed for **event-driven** architecture |
+| Handles large-scale compute jobs            | Executes short-lived functions             |
+| Custom EC2 instances or Fargate tasks       | Fully serverless, no server management     |
+| Jobs may take minutes to hours              | Max execution time of 15 minutes           |
+| Rely on EBS / instance store for disk space | Limited temporary disk space               |
+
+## Amazon Lightsail
+
+- Virtual servers, storage, databases, and networking
+- Low & predictable pricing
+- Simpler alternative to using EC2, RDS, ELB, EBS, Route 53…
+- Great for people with little cloud experience!
+- Can setup notifications and monitoring of your Lightsail resources
+- Use cases:
+  - Simple web applications (has templates for LAMP, Nginx, MEAN, Node.js…)
+  - Websites (templates for WordPress, Magento, Plesk, Joomla)
+  - Dev / Test environment
+- Has high availability but no auto-scaling, limited AWS integrations
+
+## Lambda Summary
+
+- Lambda is Serverless, Function as a Service, seamless scaling, reactive
+- Lambda Billing:
+  - By the time run x by the RAM provisioned
+  - By the number of invocations
+- Language Support: many programming languages except (arbitrary) Docker
+- Invocation time: up to 15 minutes
+- Use cases:
+  - Create Thumbnails for images uploaded onto S3
+  - Run a Serverless cron job
+- API Gateway: expose Lambda functions as HTTP API
+
+## Other Compute Summary
+
+- Docker: container technology to run applications
+- ECS: run Docker containers on EC2 instances
+- Fargate:
+- Run Docker containers without provisioning the infrastructure
+- Serverless offering (no EC2 instances)
+- ECR: Private Docker Images Repository
+- Batch: run batch jobs on AWS across managed EC2 instances
+- Lightsail: predictable & low pricing for simple application & DB stacks

sections/s3.md

@@ -421,4 +421,3 @@
 - Snow Family: import data onto S3 through a physical device, edge computing
 - OpsHub: desktop application to manage Snow Family devices
 - Storage Gateway: hybrid solution to extend on-premises storage to S3
-