# AWS Services AWS groups its services into domains/categories. The official overview lists services by category like compute, storage, database, networking, security, analytics, ML/AI, developer tools, migration, IoT, media, AR/VR, etc. [AWS Documentation](https://docs.aws.amazon.com/whitepapers/latest/aws-overview/amazon-web-services-cloud-platform.html?utm_source=chatgpt.com) As you go deeper, you’ll see many overlapping choices — that’s by design: to give you more flexibility depending on scale, latency, cost, etc. --- ## Compute & Serverless This is one of the most dynamic categories. ### Traditional / Older ones: * **EC2 (Elastic Compute Cloud)** — virtual machines. One of the earliest AWS services. * **Auto Scaling** (for EC2) — to scale instances up/down. * **Elastic Beanstalk** — PaaS-ish: you deploy your app, AWS handles provisioning. * **VMware Cloud on AWS**, **Outposts** — for hybrid / on-prem tie-ins. * **AWS Batch** — for batch computing workloads. * **Lightsail** — simpler, packaged compute + storage for small apps. All of these have been around for a while. ### Newer / more modern ones / evolving: * **AWS Lambda** — serverless functions, doesn’t need provisioning. (Introduced ~2014) [Wikipedia](https://en.wikipedia.org/wiki/AWS_Lambda?utm_source=chatgpt.com) * **Fargate** — serverless compute for containers (you don’t manage servers) * **EKS / ECS + “Anywhere” variants** — run containers on AWS, on-prem, or in hybrid setups. * **App Runner** — focused on making containerized apps super easy to deploy. (Newer) [Wikipedia](https://en.wikipedia.org/wiki/AWS_App_Runner?utm_source=chatgpt.com) * **Image Builder** — automated building and hardening of server images. * **Wavelength, Local Zones** — bringing compute close to the edge / mobile / 5G edge. * **Graviton / ARM instance families** — improvements in computing architectures. **Evolution insight**: The trend is moving from “you manage servers” → “we manage everything” → edge / hybrid blur. Use the minimal complexity tool that does the job. --- ## Storage & File / Object / Block Storage Storage is foundational. ### Old / core: * **S3 (Simple Storage Service)** — object storage. One of the first AWS services (launched ~2006). [Wikipedia](https://en.wikipedia.org/wiki/Amazon_S3?utm_source=chatgpt.com) * **EBS (Elastic Block Storage)** — block-level volumes for EC2. * **Glacier** — colder-tier archival. * **EFS (Elastic File System)** — network file-system for Linux workloads. [Wikipedia](https://en.wikipedia.org/wiki/Amazon_Elastic_File_System?utm_source=chatgpt.com) ### Newer / more variants: * **S3 Storage Classes** — e.g. One-Zone, Intelligent-Tiering, Glacier Deep Archive. AWS keeps introducing new storage classes for cost/latency tradeoffs. * **FSx for Windows / Lustre / OpenZFS** — managed file systems for specialized workloads. * **Storage Gateway** — hybrid (on-prem + cloud) storage bridging. **Evolution insight**: Storage originally was simpler (S3 + EBS), but new additions are all about cost, tiering, performance tradeoffs, filesystem semantics, and hybrid. --- ## Database & Data Stores This is where AWS has exploded with options. ### Old / foundational: * **RDS (Relational Database Service)** — MySQL, PostgreSQL, SQL Server, Oracle, etc. * **Aurora** — AWS’s high-performance relational engine (MySQL-compatible, PostgreSQL-compatible). * **DynamoDB** — fully managed NoSQL / key-value / document store. * **ElastiCache** — in-memory caching (Redis, Memcached). [Wikipedia](https://en.wikipedia.org/wiki/Amazon_ElastiCache?utm_source=chatgpt.com) * **Redshift** — data warehousing. * **Neptune** — graph database. * **DocumentDB** — JSON / document store (MongoDB-compatible) [Wikipedia](https://en.wikipedia.org/wiki/Amazon_DocumentDB?utm_source=chatgpt.com) ### Newer / evolving: * **Aurora Serverless v2** — autoscaling relational. * **Keyspaces** (for Apache Cassandra) * **QLDB** — a ledger database with immutability / cryptographic verification. * **Timestream** — time-series database. * **MemoryDB for Redis** — a Redis-compatible, durable, managed in-memory DB. * **Glue Data Catalog / Lake Formation** — more metadata & data-lake oriented. **Evolution insight**: Unlike compute or storage, the database space shows “domain specialization” — relational, time-series, ledger, graph, etc. When AWS introduces a new need (say, IoT time-series), they often spin up a tailored DB service instead of forcing one DB to serve all. --- ## Networking & Content Delivery The spine of how services communicate, connect, and are globally available. ### Key ones (old & still central): * **VPC (Virtual Private Cloud)** — your isolated network in AWS. * **Route 53** — DNS service. * **Elastic Load Balancer (ELB)** — distribute traffic. * **CloudFront** — CDN (content distribution). * **Direct Connect** — dedicated network link to AWS. ### Newer / enhancements: * **Transit Gateway**, **Global Accelerator** * **AWS PrivateLink** — access services privately across accounts/VPCs. * **Network Firewall / WAF / Shield** — security-focused network services. * **API Gateway**, **AWS App Mesh** / **Service Mesh** — for microservices connectivity. * **AWS Global Accelerator**, **Edge/Local Zones** — low latency global networking. --- ## Security, Identity, & Compliance This domain is critical; AWS invests heavily here. * **IAM (Identity & Access Management)** — foundational. * **Cognito** — user identity / auth for apps. * **KMS (Key Management Service)** — encryption keys & management. * **Secrets Manager** / **Parameter Store** — storing credentials, secrets. * **CloudTrail** — audit logs of API calls. * **GuardDuty** — threat detection. * **Macie** — data security & classification. * **Inspector** — vulnerability assessments. * **Security Hub** — central security dashboard / posture. Over time AWS adds more fine-grained, proactive, AI / ML driven security services (GuardDuty, Inspector, etc.). --- ## Analytics, Big Data, & Streaming Since AWS is as much a data company as compute, this area is dense. * **EMR (Elastic MapReduce)** — Hadoop / Spark cluster management. * **Kinesis** — real-time streaming (Data Streams, Firehose, Analytics). * **Glue** — ETL / data integration / catalog. * **Athena** — querying S3 with SQL (serverless). * **Redshift** (already mentioned) — data warehouse. * **QuickSight** — business intelligence. Newer additions: enhancements in streaming, ML inference pipelines, lakehouse architectures, etc. --- ## Machine Learning, AI & ML Services One of the most rapidly growing areas. * **SageMaker** — full ML platform: training, inference, pipelines. * **Transcribe, Translate, Comprehend, Rekognition** — prebuilt AI services (speech, translation, NLP, image). * **Lex, Polly, Forecast, Personalize, Textract** — chatbot, TTS, forecast, personalization, document extraction. * **Bedrock, CodeWhisperer, CodeGuru, DevOps Guru** — newer additions that marry AI and devops. * **Inferentia / Trainium** — AWS’s custom ML hardware. AWS is pushing in Generative AI / agent frameworks now. Keep an eye on “what’s new at AWS.” [Amazon Web Services, Inc.](https://aws.amazon.com/new/?utm_source=chatgpt.com) --- ## Developer Tools, DevOps & Deployment These services help you build, test, release, monitor, manage. * **CloudFormation** — infrastructure as code (IaC). * **CodeCommit / CodeBuild / CodeDeploy / CodePipeline** — full CI/CD chain. * **SAM (Serverless Application Model)**, **CDK (Cloud Development Kit)** — newer approaches to IaC / serverless dev. * **X-Ray** — distributed tracing. * **Systems Manager** — operations, automation, patching, inventory. * **CloudWatch** — metrics, logs, alerts (central monitoring). * **EventBridge / SNS / SQS / Step Functions** — event-driven workflows, messaging, orchestration. Over time AWS tries to unify event buses, let you react to infra events, etc. --- ## Migration, Hybrid, & Integration To bridge on-prem, multi-cloud, legacy systems. * **Server Migration Service (SMS)** * **Database Migration Service (DMS)** * **Application Migration Service (MGN)** * **AWS Outposts**, **Local Zones**, **Wavelength** (for hybrid / edge) * **Glue / AppFlow** — data integration between SaaS / on-prem / cloud * **API Gateway**, **Step Functions**, etc., help integrate systems. --- ## Media, AR/VR, Gaming & Misc Special-purpose domains: * **Elemental Media Services** — video processing, live streaming. * **Game Tech** — GameLift, GameSparks. * **IoT services** — IoT Core, IoT Greengrass, etc. * **AR/VR / XR** — AWS has launched some niche support. * **Quantum / Braket** — quantum computing experimentation. * **Blockchain / Ledger** — QLDB, Managed Blockchain. * **Satellite / Ground Station** — AWS Ground Station for satellite comms. * **Proton** — newer service for managing infrastructure provisioning for microservices. --- ## Deprecation & Legacy / “Old” That Might Be Phasing Out * Some older APIs / older generation instance types are deprecated over time. * AWS often extends old services rather than completely replacing them, but encourages using newer variants (e.g. serverless vs EC2). * Always check the AWS **“What’s New”** announcements. [Amazon Web Services, Inc.](https://aws.amazon.com/new/?utm_source=chatgpt.com) * Some older “wrapper” services may get absorbed or fall out of favor. --- ## How to Write This Blog — Structure & Depth Tips 1. **Timeline / evolution thread** — show how AWS moved from VMs → containers → serverless → edge / hybrid. 2. **Pick a category-per-section** — compute first, storage next, database, etc. 3. **Within each, do “Old / Foundational” vs “New / Evolving / Niche”** 4. **Use use-cases / when to pick which** 5. **Highlight tradeoffs** — cost, latency, complexity, operations burden 6. **Call out deprecation risks** — AWS supports backward compatibility, but things age 7. **Link to “What’s New”**, AWS blogs, release announcements 8. **Possibly maintain a live list or table**, since AWS adds services frequently