What is AWS (Amazon Web Services)?

Amazon Web Services (AWS) is a cloud computing platform provided by Amazon that offers a comprehensive suite of cloud services across dozens of categories, spanning compute, storage, databases, networking, analytics, AI/ML, security, IoT, mobile, and more. These services are delivered from a global infrastructure of 36 regions and 114 Availability Zones, with announced expansions into New Zealand, Saudi Arabia, Taiwan, Chile, and an AWS European Sovereign Cloud. In addition to Regions and AZs, AWS operates 43 Local Zones and 31 Wavelength (5G edge) Zones worldwide. This infrastructure underpins over 200 AWS services and enables customers to deploy scalable, low-latency applications around the globe.

A Brief History of AWS

Amazon Web Services (AWS) has evolved significantly since its inception. In 2002, Amazon took the first step by launching its initial web services, which were based on its internal infrastructure. This laid the foundation for what would become a revolutionary cloud computing platform.

In 2006, AWS was officially launched, offering core services such as Amazon S3 (Simple Storage Service), Amazon SQS (Simple Queue Service), and Amazon EC2 (Elastic Compute Cloud). This launch introduced the pay-as-you-go model, which allowed businesses to pay only for the resources they used—a major innovation in the IT industry.

Between 2009 and 2013, AWS began expanding globally, reaching Europe and launching important services like Amazon CloudFront (a content delivery network), Elastic Block Store (EBS) for block storage, and the AWS Certification program to validate cloud expertise.

In 2018, AWS introduced the Auto Scaling service, enabling applications to automatically adjust capacity to maintain steady, predictable performance at the lowest possible cost.

Why AWS is Important?

AWS has established a global reach with a vast and diverse customer base. It offers more than 200 services that cover virtually every aspect of IT and application development, making it a comprehensive cloud computing platform. Known for its scalable, cost-effective, and secure cloud computing model, AWS meets the needs of businesses of all sizes and industries. Its robust infrastructure and extensive service portfolio have attracted some of the world's top companies, including Netflix, BMW, Airbnb, Coca-Cola, Capital One, and Salesforce, all of which rely on AWS to power their operations and innovate at scale.

How AWS Works?

AWS is built around a modular architecture, offering a wide range of services that users can configure independently according to their specific needs. These services cover a broad spectrum of technology areas, including Compute, Storage, Databases, Application Development, Networking, Artificial Intelligence and Machine Learning (AI/ML), Security, Monitoring, Hybrid Cloud, and much more. This flexibility allows organizations to tailor their cloud infrastructure precisely to their requirements, enabling efficient, scalable, and customized solutions.

Compute Services in AWS

Amazon EC2 (Elastic Compute Cloud):

Provision and manage virtual servers (instances) on demand. EC2 supports a wide range of instance types (x86, ARM/Graviton, GPU, FPGA, high-memory, etc.) for different workloads. Instances can be launched, stopped, and autoscaled as needed. EC2 integrates with features like Auto Scaling, Elastic Load Balancing, and EC2 Virtual Private Cloud. New custom chips (e.g. AWS Trainium3) and instance families continuously expand EC2 capabilities.
AWS Lambda:

Run code serverlessly in response to events, without provisioning or managing servers. Lambda executes functions (supporting languages like Python, Node.js, Java, etc.) triggered by over 200 AWS events (e.g. S3 file uploads, DynamoDB updates, API calls). It automatically scales to handle any request volume and charges only for compute time consumed. Use cases include web backends, stream processing, scheduled jobs, and ML inference.
AWS Fargate:

A serverless compute engine for containers. Fargate lets you run Docker containers without managing EC2 instances or clusters. It works with Amazon ECS and Amazon EKS, launching container tasks on-demand and scaling automatically. Fargate offloads operational tasks (patching, capacity planning, scaling) to AWS, improving security through task-level isolation. Common use cases are microservices, batch processing, and AI/ML workloads in containers.
Container Orchestration:

AWS provides managed container services: Amazon ECS (Elastic Container Service) for Docker management and Amazon EKS (Elastic Kubernetes Service) for Kubernetes. Both support tasks on EC2 or Fargate. They integrate with other AWS services (IAM, VPC, CloudWatch, etc.) for security, networking, and monitoring.
High Performance & Specialized Compute:

AWS offers GPU instances (for graphics, ML training/inference), high-memory instances (SAP HANA, big data), Nitro-based bare metal instances, and emerging chip-based instances (e.g. ARM Graviton, AWS Inferentia for ML inference). AWS also provides dedicated HPC services like AWS Batch (managed batch job scheduling) and AWS ParallelCluster (HPC cluster management).
Edge & On-Premises Compute:

AWS Outposts extends AWS hardware and APIs on-premises. Wavelength Zones and Local Zones bring computers to telecom networks or city centers for ultra-low-latency applications.

AWS's Storage Services

Amazon S3 (Simple Storage Service):

Scalable object storage for any amount of data. S3 provides 11-nines of durability, high availability, and comprehensive security. Objects stored in S3 can be accessed via simple APIs, and S3 automatically scales as needed. S3 offers multiple storage classes (Standard, Intelligent-Tiering, One Zone, Glacier Instant Retrieval, Glacier Flexible Retrieval, Glacier Deep Archive) to optimize cost and access latency. Data management features include versioning, lifecycle policies, replication (cross-region or multi-region), encryption, access logging, and event notifications. Common use cases are data lakes, content distribution, backups, analytics data, and static website hosting. Recent updates: In late 2024, AWS introduced dedicated storage classes for AWS Dedicated Local Zones, allowing S3 “one zone” classes to be used in those zones. Also, a new S3 Metadata feature (GA Jan 2025) automatically catalogs object metadata into queryable tables (Apache Iceberg) for use with Athena/Redshift.
Amazon EBS (Elastic Block Store):

Persistent block storage volumes for EC2 instances. EBS volumes are provisioned and attached to specific AZs, and AWS replicates each volume within an AZ for fault tolerance. EBS offers multiple volume types (SSD gp3/io2 for general or intensive IOPS; HDD st1/sc1 for throughput) to suit database, boot volume, or file system workloads. EBS features include snapshot-based backups (to S3) and encryption at rest with AWS KMS. It provides high IOPS/throughput for databases and enterprise applications.
Amazon EFS (Elastic File System):

Fully managed NFS file storage. EFS provides a shared, elastic file system that can grow to petabytes and serve multiple EC2 instances or containers concurrently. It automatically scales throughput and capacity as files are added. EFS supports standard NFS semantics, POSIX permissions, and can provide high throughput (GB/s) and IOPS. It offers performance modes (General Purpose or Max I/O) and storage classes for cost optimization (Standard vs. Infrequent Access tiers). Typical uses include content management systems, development environments, media workflows, and home directories. EFS is “serverless” in that no provisioning is needed; it's highly durable and available (11 9s durability, up to 4 9s availability).
Amazon FSx:

Managed file systems optimized for specific workloads. Examples include FSx for Windows File Server (SMB volumes for Windows), FSx for Lustre (high-performance Lustre file system for HPC and ML with S3 integration), and FSx for NetApp ONTAP. These fully managed services handle configuration and scaling for workloads needing SMB or Lustre.
Amazon S3 Glacier:

Purpose-built archives for long-term retention. Glacier provides three tiers: Instant Retrieval (millisecond access), Flexible Retrieval (minutes to hours), and Deep Archive (12+ hours) for lowest cost. Data stored via S3 lifecycle policies can be moved automatically to Glacier classes for archiving.
AWS Storage Gateway:

Hybrid storage integration from on-premises to AWS. Supports file, volume, and tape interfaces, transparently storing data in S3 or EBS.
AWS Snow Family:

Physical devices (Snowcone, Snowball, Snowmobile) for petabyte-scale data transfer and edge computing in disconnected environments.

Databases in AWS

Amazon RDS (Relational Database Service):

Managed relational databases. RDS automates provisioning, patching, backup, and scaling for engines like MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server. It handles Multi-AZ failover replication, automated backups, snapshots, and read replicas for high availability and read scaling. Users can tune compute and storage independently and integrate RDS with IAM, CloudWatch, and other AWS services.
Amazon Aurora:

A high-performance, cloud-optimized relational database compatible with MySQL, PostgreSQL, and an Amazon-developed distributed SQL (Aurora DSQL) engine. Aurora delivers up to 5× the throughput of MySQL and 3× PostgreSQL on similar hardware, with a distributed, fault-tolerant storage subsystem. It offers features like serverless scaling (Aurora Serverless v1/v2), global database spanning multiple regions, fast failover, and automated monitoring. Aurora provides up to 99.99% availability with Multi-AZ, and can automatically offload backups to S3. Use cases include enterprise OLTP, SaaS backends, and cloud-native applications.
Amazon DynamoDB:

Fully managed NoSQL database with single-digit millisecond performance. DynamoDB is serverless and scales automatically to handle virtually any request volume. It supports both key-value and document data models and offers built-in high availability and encryption. Features include on-demand or provisioned capacity modes (with auto-scaling), global tables for multi-Region replication, DynamoDB Accelerator (DAX) in-memory caching, and PartiQL (SQL-compatible querying). In 2024 AWS enhanced DynamoDB with performance and integration improvements: new warm up/down throughput settings, configurable max throughput, and tighter integration with analytics (Zero-ETL exports to Redshift and SageMaker). DynamoDB is widely used for gaming, IoT, web/mobile backends, and any low-latency workload.
Amazon ElastiCache:

Managed in-memory cache (Redis and Memcached). ElastiCache deploys, patches, and monitors Redis or Memcached clusters. It provides Redis-compatible clusters (with cluster mode and replication groups) and Memcached caches for sub-millisecond data access. ElastiCache Redis offers high availability with Multi-AZ replication, automatic failover, and snapshots. A newer service, Amazon MemoryDB for Redis, provides a durable Redis-compatible store with Multi-AZ replication and disk durability. Use cases include caching, session stores, leaderboards, and fast transactions.
Amazon DocumentDB:

Managed document database with MongoDB compatibility. DocumentDB handles deployment, scaling, and backups for JSON/document workloads with MongoDB APIs. (Note: Not a native MongoDB engine; uses a separate managed engine.)
Amazon Neptune:

Managed graph database service for highly connected data. Neptune Database is serverless, scales to handle large graphs (billions of relationships), and supports both property graphs (Apache TinkerPop/Gremlin) and RDF/SPARQL models. It offers multi-AZ and multi-Region clusters for high availability (99.99% SLA) and built-in security (encryption, IAM). Neptune Analytics is a companion feature for running graph analytics (via Apache Spark) on Neptune or S3 data. Use cases include knowledge graphs, fraud detection, and social network analysis.
Amazon QLDB (Quantum Ledger Database):

A fully managed ledger database with immutable, cryptographically verifiable transaction log. QLDB maintains a complete history of all changes, suitable for supply chain, finance, and auditing use cases.
Amazon Keyspaces (for Apache Cassandra):

Managed Cassandra-compatible service. Keyspaces allows Cassandra workloads with serverless pricing and virtual nodes for scaling.
Amazon Timestream:

Serverless time-series database optimized for IoT and operational applications, with built-in time-aware data tiering and query functions.
Amazon Redshift:

(Also under Analytics) Fully managed cloud data warehouse. Redshift organizes data in a columnar format across nodes and delivers fast analytical queries across petabyte-scale data. It provides two modes: provisioned clusters (with managed scaling) and Redshift Serverless (auto-managed compute). Redshift integrates with data lakes via Redshift Spectrum and offers features like cross-region replication, concurrency scaling, and materialized views. Typical uses are business intelligence, data mart, and analytics pipelines.

Networking & Content Delivery in AWS

Amazon VPC (Virtual Private Cloud):

Virtual network in AWS for provisioning AWS resources in an isolated environment. VPCs let you define your own IP address ranges, subnets, route tables, and network ACLs. You can launch EC2 instances, RDS databases, and other services within a VPC, controlling access via Security Groups and network policies. VPCs support multi-region peering and hybrid connectivity (VPN, Direct Connect). Use cases include multi-tier applications and secure isolation of cloud resources.
Amazon Route 53:

Scalable DNS and domain name registration service. Route 53 reliably routes end users to internet applications by resolving domain names to IP addresses, using globally distributed DNS servers. It includes advanced routing features like latency-based routing, geo DNS, and health checks to route traffic to healthy endpoints. Route 53 also manages domain registration, and its Resolver DNS Firewall can filter malicious domains.
Elastic Load Balancing (ELB):

Managed load balancers to distribute traffic. AWS provides Application Load Balancer (Layer 7 HTTP/HTTPS routing with host/path-based rules), Network Load Balancer (Layer 4 TCP with static IPs), and Classic Load Balancer (legacy Layer 4/7). ELB improves application availability by distributing incoming requests across targets (EC2, containers, IPs) in multiple AZs. It integrates with AWS Auto Scaling and supports features like SSL termination and access logs.
Amazon CloudFront:

Content Delivery Network (CDN) service for low-latency distribution. CloudFront caches and delivers content (web, streaming, APIs) from over 600 edge locations worldwide. It reduces latency by using AWS's global edge network, with intelligent routing and support for HTTP/2, WebSockets, and gRPC. CloudFront integrates with AWS Shield and AWS WAF for built-in DDoS and web-application protection, and allows running custom code at the edge (Lambda@Edge, CloudFront Functions). Use cases include accelerating websites, APIs, and media streaming globally.
Amazon API Gateway:

Fully managed service to create, publish, monitor, and secure RESTful, HTTP, and WebSocket APIs. API Gateway handles traffic management, authorization, throttling, and versioning, acting as a “front door” for backend services. It supports AWS Lambda, ECS/EKS, and any HTTP backend, scaling to hundreds of thousands of concurrent calls. Developers use API Gateway to quickly build serverless APIs for web/mobile apps or microservices.
AWS Direct Connect:

Dedicated private network connectivity between on-premises data centers and AWS. It bypasses the public internet for consistent bandwidth and lower latency.
AWS Transit Gateway:

Central hub to connect multiple VPCs, VPNs, and Direct Connect gateways. Simplifies network topology by consolidating peering relationships.
AWS Global Accelerator:

Service that improves availability and performance of global applications by routing user traffic through the AWS global network to optimal regional endpoints.
Other services:

AWS PrivateLink (private connectivity to services), VPN (site-to-cloud encrypted links), and Elastic IP addresses, NAT Gateways, VPC Endpoints.

AWS's Security, Identity, & Compliance

AWS Identity and Access Management (IAM):

Core identity service to control access to AWS resources. IAM lets you create users, groups, roles, and policies to finely control who (which identities) can access which services and actions. IAM provides centralized authentication and authorization for AWS accounts, enabling multi-factor authentication (MFA), IAM Roles for service-to-service access, and IAM Identity Center (formerly AWS SSO) for workforce identity. All AWS services integrate with IAM for secure permission management.
AWS Key Management Service (KMS):

Managed service for encryption key management. KMS enables you to create, rotate, and control symmetric and asymmetric keys used to encrypt data in other AWS services (S3, EBS, RDS, Redshift, etc.). Customer Master Keys in KMS are protected by FIPS 140-3 validated hardware security modules. KMS supports automated key rotation, IAM-integrated policies, and multi-Region keys for cross-region replication.
AWS Secrets Manager:

Securely store, retrieve, and rotate database credentials, API keys, and other secrets. Secrets Manager centralizes encryption and access control for secrets, integrates with AWS logging/monitoring, and can automatically rotate credentials without application downtime.
Amazon GuardDuty:

Continuous security threat detection service. GuardDuty analyzes AWS account activity (CloudTrail), VPC flow logs, DNS logs, S3 logs, etc., using machine learning and threat intelligence to detect anomalies and malicious behavior. It provides detailed findings to help identify compromised instances, reconnaissance, or unusual data access. GuardDuty automatically scales across accounts and integrates with AWS Security Hub for centralized response.
AWS WAF (Web Application Firewall):

Layer 7 firewall that protects web applications. WAF lets you define rules to block or allow web requests based on IP addresses, query strings, geolocation, and known malicious signatures. It integrates with CloudFront, ALB, and API Gateway.
AWS Shield:

Managed DDoS protection. Shield Standard is automatically included with AWS services at no extra cost, providing protection against common network and transport layer attacks. Shield Advanced (paid) adds detection and mitigation for sophisticated DDoS attacks, global threat environment dashboards, and cost-protection for scaling during attacks. Shield can be used alone or in conjunction with WAF for application-layer protection.
AWS Inspector:

Automated vulnerability management and compliance assessment. Inspector continuously scans EC2 instances, container images, and Lambda functions for known vulnerabilities and configuration issues. It produces findings that help prioritize remediation based on severity and exploitability. Inspector uses sources like CVEs and security best practices to flag issues.
AWS CloudTrail and AWS Config:

CloudTrail records API calls and events across your account for auditing. AWS Config continuously evaluates resource configurations against best-practice rules (CIS AWS Foundations, custom policies). These services enable compliance reporting and forensic analysis.
AWS Certificate Manager (ACM):

Provision and manage TLS/SSL certificates for use with AWS services (ELB, CloudFront, API Gateway) at no extra charge. ACM automates renewal and deployment of public and private certificates.

Analytics & Big Data with AWS

Amazon Athena:

Serverless interactive query service. Athena lets you run ANSI SQL queries directly against data stored in Amazon S3 (and other sources via connectors) without setting up servers. It automatically parallelizes and scales queries for fast performance on large datasets. Athena is often used to process logs, run ad-hoc analytics on S3 data lakes, or integrate with BI tools. (Athena now supports both SQL and Apache Spark workloads in its next-generation integration with Amazon SageMaker.)
Amazon Redshift:

Managed data warehouse. Redshift is optimized for analytical (OLAP) workloads across petabyte-scale datasets. It uses a massively parallel processing architecture and columnar storage. Redshift Serverless is a no-provisioning option that automatically manages capacity and performance. Redshift Spectrum allows querying data directly in S3 via Redshift, integrating with data lakes. New Redshift features include AQUA (advanced caching) and datasharing between clusters.
Amazon EMR (Elastic MapReduce):

Managed Hadoop, Spark, Presto, and Flink clusters on EC2. EMR simplifies big data processing by provisioning, configuring, and scaling clusters. It supports a wide ecosystem of open-source tools (Hive, HBase, Kafka, etc.) for processing petabytes of data. EMR Serverless lets you run Spark jobs without managing clusters.
Amazon Kinesis:

Real-time data streaming platform. It includes Kinesis Data Streams (high-throughput ingest and buffer of streaming data), Kinesis Data Firehose (stream delivery to data stores like S3, Redshift, Elasticsearch), Kinesis Data Analytics (SQL analytics on streaming data), and Kinesis Video Streams (streaming video ingestion). Kinesis can ingest millions of events per second from sources like logs, IoT devices, or user activity, delivering real-time analytics and dashboards.
AWS Glue:

Serverless data integration/ETL service. Glue helps discover, catalog, and transform data for analytics. It automatically generates ETL code (Python/Scala) to extract, clean, and load data into data warehouses or lakes. Glue Data Catalog stores metadata for datasets across AWS. New AI-assisted features in Glue can generate code and suggest transformations to accelerate data pipeline development. Glue integrates with Athena, Redshift, SageMaker, and now includes generative AI assistance for ETL.
Amazon QuickSight:

Cloud-native business intelligence (BI) and visualization service. QuickSight enables users to create interactive dashboards, reports, and visualizations from various data sources (S3, Redshift, RDS, on-prem databases, and more). It provides embedded analytics APIs for integrating dashboards into applications. QuickSight ML Insights (Amazon Q) allow natural-language querying and ML-driven insights (autoNarratives, anomaly detection) to help interpret data. It automatically scales to tens of thousands of users with a pay-per-session pricing model.
Amazon OpenSearch Service (formerly Amazon Elasticsearch Service) – Managed search and analytics service. OpenSearch Service runs the open-source OpenSearch/Elasticsearch engines at scale, handling cluster provisioning, patching, and scaling. It is used for full-text search, log and metrics analytics, application monitoring, and now as a vector database for AI workloads. The service provides security, high availability, and integrations with AWS monitoring tools. It can ingest logs from CloudWatch or S3 for centralized observability and can accelerate search applications with its distributed architecture.
AWS Data Exchange – Marketplace for third-party data sets (financial, geospatial, marketing, etc.) that customers can subscribe to and import into AWS for analysis.
Amazon Managed Streaming for Apache Kafka (MSK) – Managed Kafka service for streaming data pipelines (if needed).
AWS Lake Formation – Service to set up and govern a secure data lake on S3, centralizing data access controls and metadata.
Others: Amazon Data Pipeline (scheduled data workflows), AWS Step Functions (serverless orchestration of data workflows), Amazon EventBridge (event bus for cross-service event-driven integration).

Artificial Intelligence & Machine Learning in AWS

Amazon SageMaker:

Comprehensive ML platform for building, training, and deploying machine learning models. SageMaker includes Studio (integrated IDE), Autopilot (automated ML model tuning), Ground Truth (data labeling), and many built-in algorithms and frameworks. It supports one-click training on instances or distributed clusters, and real-time or batch inference endpoints. New (re:Invent 2024): AWS announced “next-generation SageMaker” features: SageMaker Unified Studio (single interface for data, notebooks, and ML pipeline), a central SageMaker Model Catalog for managing models and artifacts, SageMaker Lakehouse (integrated analytics and ML), and “zero-ETL” integrations with SaaS data sources. These advances make it easier to govern, share, and operationalize ML across analytics and development teams.
Amazon Bedrock:

Fully managed service for building generative AI applications using foundation models. Bedrock gives developers API access to a range of high-performance large language models (LLMs) and multimodal models from AWS and third-party providers (AI21 Labs, Anthropic, Cohere, Meta, Mistral, Stability AI, AWS Titan, etc.). It handles the infrastructure for model hosting, and provides tools for private fine-tuning, retrieval-augmented generation (RAG), and agent orchestration. As a serverless service, Bedrock scales on demand and ensures data security. It accelerates experimentation by offering model choice and seamless upgrades.
Amazon Titan Models:

A family of foundation models developed by AWS, optimized for various tasks (text, code, embeddings, etc.). Titan models are available via Bedrock and select AWS services.
Amazon Comprehend:

Natural language processing (NLP) service to extract insights (sentiment, key phrases, entities, language) from text.
Amazon Rekognition:

Image and video analysis service. It can identify objects, scenes, and faces; perform face recognition and sentiment analysis; and detect activities or content moderation.
Amazon Textract:

Document text extraction. Automatically detects and extracts printed or handwritten text and data (forms, tables) from scanned documents.
Amazon Transcribe:

Speech-to-text service. Converts audio to text, with support for multiple languages and specialized models (medical, call analytics).
Amazon Translate:

Neural machine translation between dozens of languages.
Amazon Polly:

Text-to-speech service. Generates realistic speech from text, supporting multiple voices and languages.
Amazon Lex:

Build conversational interfaces (chatbots) using speech and text, with deep learning for intent recognition. (Lex powers Alexa-like functionality for custom applications.)
Amazon CodeWhisperer:

AI-powered code completion and generation for developers (guards code quality and speeds coding tasks).
AWS DeepRacer:

(Educational) Reinforcement learning in autonomous racing simulation.
Amazon Kendra:

Intelligent search service (enterprise search with natural language query).
Amazon Neptune ML:

Graph ML for Neptune using embeddings.
Amazon Forecast/Amazon Personalize:

Fully managed services for time-series forecasting and recommendation systems (now under SageMaker as Studios and AutoML).

Internet of Things (IoT)

AWS IoT Core:

Managed cloud service to connect IoT devices securely. It supports MQTT, HTTP, and WebSockets for bi-directional communication between devices and AWS. IoT Core includes a rules engine to route device messages to AWS endpoints (Lambda, DynamoDB, Kinesis, etc.) for processing and storage.
AWS IoT Greengrass:

Software to extend AWS to edge devices, enabling local compute, messaging, and data caching even offline. It allows running AWS Lambda functions or Docker containers on devices, with local shadow states and ML inference. Greengrass can sync data back to AWS IoT Core when reconnected.
AWS IoT Device Management:

Tools for onboarding, organizing, monitoring, and remotely managing device fleets at scale (firmware updates, device shadows).
AWS IoT Analytics:

Managed service for advanced analytics of IoT data. It preprocesses, enriches, and stores IoT device data for analysis with SQL or ML.
AWS IoT SiteWise:

Collects and analyzes data from industrial equipment (PLC, OPC-UA) at scale. It models manufacturing hierarchies and provides metrics to optimize operations.
AWS IoT Events:

Detects and responds to events from IoT sensors (e.g. “machine overheating”) using defined detectors and actions.
AWS IoT SiteWise Edge:

Deploy SiteWise on-premises gateways for local processing of industrial data.
AWS IoT FleetWise:

Ingest, transform, and move vehicle sensor data to the cloud for analytics, with query-based filtering.
AWS IoT TwinMaker:

Service to create digital twins of real-world systems (buildings, factories) for monitoring and ML.

Front-End Web & Mobile Services from AWS

AWS Amplify:

Development platform for building and deploying full-stack web and mobile applications. Amplify provides libraries and UI components for integrating with AWS services (authentication, APIs, data storage, analytics), and supports popular frameworks (React, Angular, Vue, iOS, Android, Flutter). It also offers hosting and continuous deployment: developers can push front-end code to Amplify and instantly publish global websites/apps via CloudFront. Amplify automatically provisions backend resources (GraphQL/REST APIs, DynamoDB/S3 storage, Cognito auth) based on developer-defined schemas.
Amazon Cognito:

User sign-up, sign-in, and access control for mobile/web apps. It handles user pools (for user directory), identity pools (federated identities), and social logins. Cognito integrates with IAM roles to grant AWS resource access to authenticated users.
AWS AppSync:

Managed GraphQL service for real-time data queries. AppSync enables building data-driven mobile/web apps by providing a GraphQL API that connects to DynamoDB, Lambda, or HTTP endpoints. It supports real-time data via GraphQL subscriptions and offline sync.
Amazon Pinpoint:

Marketing and engagement service for mobile apps. Pinpoint sends targeted push notifications, emails, SMS, and voice messages to users, and tracks campaign and user behavior analytics. It helps personalize messaging and measure engagement metrics.
Amazon Simple Notification Service (SNS):

Pub/sub messaging for application-to-application or app-to-person notifications. SNS can send push notifications to mobile devices, emails, or SMS messages, and fan-out messages to multiple subscribers (SQS queues, Lambda, HTTP endpoints).
Amazon Simple Email Service (SES):

Scalable email sending service (transactional and marketing emails), with deliverability tools.
AWS Device Farm:

App testing service that runs mobile app tests on real devices hosted in AWS data centers. Developers can upload apps to test against a wide range of device models and OS versions.
Amazon API Gateway:

(As noted) used for mobile/web backend APIs (REST/WebSocket) with Lambda integration.
Amazon CloudFront:

(As noted) used to accelerate static assets (images, JS, CSS) globally for web/mobile.

AR/VR and Spatial Computing in AWS

Amazon Sumerian:

(Legacy) AWS service (introduced 2018) for building and running AR, VR, and 3D applications in a browser. Sumerian provided a web-based editor for creating 3D scenes and characters (“Hosts”) with integrated AWS services (Polly and Lex for speech/AI). It targeted devices like Oculus Rift, HTC Vive, and WebXR browsers. Note: Amazon Sumerian has not had major updates recently and is now in maintenance mode.
AWS ThinkBox:

Suite of tools (Deadline, etc.) for creative workloads and rendering. (Deadline is a render farm management service.)
Nimble Studio:

(Discontinued as of 2023) Managed service for graphics and media production pipelines in AWS. It provided virtual workstations and shared storage for VFX and animation. AWS now recommends partner solutions for similar needs.

Developer Tools & Management in AWS

AWS CodeCommit, CodeBuild, CodeDeploy, CodePipeline:

A suite of CI/CD tools. CodeCommit is a Git-based source control. CodeBuild is a managed build service (compiling source and running tests). CodeDeploy automates deployments to EC2, Lambda, or on-prem servers. CodePipeline orchestrates continuous delivery pipelines integrating these services and third-party tools. Together they enable full CI/CD workflows for application development.
AWS CodeArtifact:

Managed package repository (like npm, Maven, NuGet) for storing and sharing software packages.
AWS Cloud9:

Cloud-based integrated development environment (IDE) accessible through a browser. Includes code editor, terminal, and debugging for rapid development.
AWS X-Ray:

Distributed tracing service for monitoring and debugging applications. X-Ray collects end-to-end request traces and metrics, helping developers identify performance bottlenecks in microservices or serverless architectures.
AWS CloudFormation:

Infrastructure-as-Code service. Allows defining AWS resources and configurations in text templates (YAML/JSON) for automated provisioning. CloudFormation handles dependency order and updates with rollback support.
AWS CDK (Cloud Development Kit):

High-level framework (TypeScript, Python, etc.) for defining CloudFormation infrastructure using general-purpose programming languages.
AWS Systems Manager:

Operational hub for managing EC2 and on-prem servers at scale. Systems Manager provides Run Command, Patch Manager, Session Manager (shell access), Parameter Store (configuration variables), and Automation for common tasks.
Amazon CloudWatch:

Monitoring, logging, and observability service. It collects metrics (CPU, memory, custom app metrics), logs (application logs, VPC flow logs), and allows setting alarms. CloudWatch also includes Container Insights, Lambda Insights, and CloudWatch Logs for real-time troubleshooting. Dashboards enable custom visualizations.
AWS CloudTrail:

Logging and auditing of all AWS API calls. CloudTrail records actions across services for security analysis and compliance.
AWS Config:

Tracks configuration changes to AWS resources and evaluates them against policies. Useful for compliance auditing and change management.
AWS Systems Manager Parameter Store:

Secure storage for configuration data and secrets, integrated with IAM and KMS.

Migration & Transfer to AWS

AWS Database Migration Service (DMS):

Migrate or replicate on-premises databases to AWS with minimal downtime. Supports homogeneous (e.g. Oracle to Oracle) or heterogeneous (e.g. SQL Server to Aurora) migrations. Continuously replicates data with change data capture (CDC) until cutover.
AWS Application Migration Service (MGN):

(Formerly CloudEndure Migration) Lift-and-shift of servers (VMs and physical) to AWS. Automates replication of the entire machine image for testing and final cutover.
AWS Snowball/Snowmobile:

Physical data transfer devices for offline bulk data migration to AWS. Useful when data sizes are too large for network transfer.
AWS DataSync:

Managed service for online data transfer. Synchronizes files from on-prem NFS/SMB storage to AWS (S3, EFS) or between AWS storage services with high performance.
AWS Transfer Family:

Managed SFTP/FTPS/FTP endpoint on AWS to move files into and out of S3 or EFS.
AWS Storage Gateway:

(As above) for hybrid cloud storage integration.

Business Applications & Emerging

Amazon WorkSpaces:

Managed Desktop-as-a-Service (DaaS) offering cloud-based Windows or Linux desktops. Each user gets a persistent desktop environment accessible from anywhere.
Amazon WorkDocs:

Secure enterprise file collaboration service.
Amazon Chime:

Communications service for online meetings, chat, and business calls. (Chime SDK for embedding in apps.)
Amazon AppStream 2.0:

Managed application streaming service. Stream desktop applications to web browsers (similar to Citrix).
Amazon Connect:

Cloud-based contact center service. Provides multichannel customer service via voice and chat, with integrations to CRM and AI (Lex bots).
Amazon Managed Blockchain:

(As above) for hybrid cloud storage integration.
Amazon QLDB:

(Listed under Databases) immutable ledger database for applications requiring an authoritative data log.
Amazon Quantum Ledger Database:

(Duplicate of QLDB entry above)
Amazon Braket

Managed service for quantum computing. Provides access to quantum simulators and real quantum hardware (from providers like IonQ, Rigetti, etc.) for experimentation with quantum algorithms.
AWS Ground Station

Fully managed satellite ground station service. Allows downlink and uplink of satellite data using AWS infrastructure, integrating satellite data with AWS services.

AWS Availability Zones and Regions (2025)

As of 2025, AWS operates 36 launched AWS Regions around the world, including multiple AWS GovCloud regions. Each Region contains multiple Availability Zones (AZs) (isolated data centers). In total there are 114 launched AZs. AWS has announced five new upcoming Regions (New Zealand, Saudi Arabia, Taiwan, Chile, and an AWS European Sovereign Cloud) and 16 additional AZs. In addition to Regions/AZs, AWS provides specialized zones: 43 Local Zones (metro-area extensions for ultra-low-latency compute) and 31 Wavelength Zones(integrated 5G+Edge sites for telecom applications). The AWS global network also includes 700+ CloudFront Points-of-Presence and 13 Regional Edge Caches for content delivery. This expansive infrastructure ensures that customers can run applications close to end-users with high availability and low latency.

AWS Market Share and Competition

As of Q1 2025, AWS holds 30% of the global cloud market and currently ranks in top position among other cloud services.
Top competitors: Microsoft Azure, Google Cloud Platform (GCP), and IBM Cloud.

Companies Using AWS

Some of the major enterprises leveraging Amazon Web Services (AWS) include industry leaders such as Airbnb, Netflix, BMW Group, Pinterest, Capital One, Salesforce, Coca-Cola, Goldman Sachs, Heineken, Toyota, the NFL, and Philips. These organizations rely on AWS’s scalable, secure, and innovative cloud infrastructure to power their operations, enhance customer experiences, and drive digital transformation.

What is AWS (Amazon Web Services)?

A Brief History of AWS

Why AWS is Important?

How AWS Works?

Compute Services in AWS

Amazon EC2 (Elastic Compute Cloud):

AWS Lambda:

AWS Fargate:

Container Orchestration:

High Performance & Specialized Compute:

Edge & On-Premises Compute:

AWS's Storage Services

Amazon S3 (Simple Storage Service):

Amazon EBS (Elastic Block Store):

Amazon EFS (Elastic File System):

Amazon FSx:

Amazon S3 Glacier:

AWS Storage Gateway:

AWS Snow Family:

Databases in AWS

Amazon RDS (Relational Database Service):

Amazon Aurora:

Amazon DynamoDB:

Amazon ElastiCache:

Amazon DocumentDB:

Amazon Neptune:

Amazon QLDB (Quantum Ledger Database):

Amazon Keyspaces (for Apache Cassandra):

Amazon Timestream:

Amazon Redshift:

Networking & Content Delivery in AWS

Amazon VPC (Virtual Private Cloud):

Amazon Route 53:

Elastic Load Balancing (ELB):

Amazon CloudFront:

Amazon API Gateway:

AWS Direct Connect:

AWS Transit Gateway:

AWS Global Accelerator:

Other services:

AWS's Security, Identity, & Compliance

AWS Identity and Access Management (IAM):

AWS Key Management Service (KMS):

AWS Secrets Manager:

Amazon GuardDuty:

AWS WAF (Web Application Firewall):

AWS Shield:

AWS Inspector:

AWS CloudTrail and AWS Config:

AWS Certificate Manager (ACM):

Analytics & Big Data with AWS

Amazon Athena:

Amazon Redshift:

Amazon EMR (Elastic MapReduce):

Amazon Kinesis:

AWS Glue:

Amazon QuickSight:

Artificial Intelligence & Machine Learning in AWS

Amazon SageMaker:

Amazon Bedrock:

Amazon Titan Models:

Amazon Comprehend:

Amazon Rekognition:

Amazon Textract:

Amazon Transcribe:

Amazon Translate:

Amazon Polly:

Amazon Lex:

Amazon CodeWhisperer:

AWS DeepRacer:

Amazon Kendra:

Amazon Neptune ML:

Amazon Forecast/Amazon Personalize:

Internet of Things (IoT)

AWS IoT Core:

AWS IoT Greengrass:

AWS IoT Device Management:

AWS IoT Analytics:

AWS IoT SiteWise:

AWS IoT Events: