Top 50+ AWS Services Explained: What They Do and How They Power the Cloud
Written by Massa Medi
In 2006, Amazon Web Services (aka AWS) made its revolutionary debut with only three humble services: a way to store files (some early buckets), a method to spin up virtual computers (EC2 compute instances), and a messaging queue. Fast forward to the present, and the AWS “supermarket” now boasts a dizzying 200+ services covering just about every need for developers from hosting web apps, storing data, scaling workloads, to, believe it or not, communicating with satellites and running quantum computers. If navigating this cloud mega mart feels overwhelming, you’re not alone! Many AWS services appear to overlap in purpose, often leaving developers wondering which “brand” to pick, just like standing in front of 30 different jars of peanut butter at your local grocery store.
In this feature, we’ll take you on a guided walk “down the aisles” of AWS’s sprawling service catalog, demystifying and explaining over 50 key products along the way. Whether you’re a robotics engineer, a weekend web app tinkerer, or a data scientist, there’s something here for you.
Innovative and Niche AWS Services Above Most Pay Grades
Let’s kick things off with some specialty services that, unless you have robots in your garage or satellites in orbit, might fly under your radar:
- RoboMaker: Simulate and test fleets of robots at scale. Useful if you’re building or managing robotic systems think Amazon delivery bots or industrial drones.
- IoT Core: Manage and monitor fleets of connected devices from updating their firmware to collecting sensor data once those bots are out in the world.
- Ground Station: Got a satellite zipping around Earth? AWS’s global network of antennas can connect with it directly, letting you transfer huge volumes of space data to the cloud.
- Braket: Experiment with quantum computing an entirely new paradigm of computation accessed directly from the familiar AWS platform. Come, taste the future!
Compute Aisle: Elastic and Ephemeral Power in the Cloud
Of course, most developers come to AWS to solve practical day to day problems. So, let’s roll our carts to the compute aisle, where flexibility, scalability, and pay by the second pricing reign supreme.
- EC2 (Elastic Compute Cloud): The OG AWS staple. Create virtual machines in the cloud, pick your favorite operating system and hardware specs, and rent server “apartments” that charge by the second. Ideal for hosting websites, running APIs, and more.
- As your app grows, managing a single server becomes unsustainable. Elastic Load Balancing (ELB) steps in to distribute traffic automatically across multiple servers, ensuring smooth, uninterrupted service.
- CloudWatch: Keeps a close eye on your servers, collecting logs and metrics, then feeding this data to other AWS tools.
- Auto Scaling: Define policies (e.g., “add two more servers when CPU hits 80%”) to scale your infrastructure up or down automatically, so your app keeps pace with traffic changes.
- Elastic Beanstalk: Introduced a higher level of abstraction in 2011. Deploy your code (think Ruby on Rails or Node.js) and let AWS manage the underlying EC2 instances, scaling, and updates. A quintessential Platform as a Service (PaaS) solution.
- LightSail: For those who just want to click and deploy (think WordPress sites or small app demos), LightSail offers a rock simple, point and click approach, taking care of the complex configurations.
- One major leap came with AWS Lambda (“serverless” computing) in 2014. No need to run or manage any servers just upload your code, specify events that trigger it (like an API request or file upload), and AWS takes care of auto scaling and traffic, charging you only for the precise time your code runs.
- Serverless Application Repository: Don’t want to write functions yourself? Deploy pre built Lambda functions for common use cases with a single click.
- Outposts: For huge enterprises that aren’t ready to dump their on premises hardware, Outposts lets you bring AWS services to your own servers, running AWS APIs locally.
- Snow Devices: Mini data centers you can ship anywhere say, a research outpost in Antarctica to process and store data even without a steady internet connection.
The Rise of Containers Standardizing Modern App Deployment
Many modern apps are built and deployed using Docker containers, ensuring portability across clouds and environments. AWS has you covered with:
- Elastic Container Registry (ECR): Store Docker images for easy distribution and deployment.
- Elastic Container Service (ECS): Launch and manage containers, controlling when and where they run. Connect them to load balancers and scale as needed.
- EKS (Elastic Kubernetes Service): For teams wanting full Kubernetes control without the headaches of manual cluster management.
- Fargate: Serverless deployment for containers focus on your app, not the infrastructure.
- App Runner: Launched in 2021, this new service lets you point at a container image and auto magically handles all the scaling and orchestration.
Storage Solutions: File Cabinets in the Cloud
Your applications need a place to stash their data, and AWS offers several flavors of cloud storage:
- S3 (Simple Storage Service): The original AWS workhorse, allowing unlimited storage for files (think images, videos, and backups) with legendary durability. The backbone of Amazon.com itself.
- Glacier: Archive infrequently accessed data at ultra low cost. Accessing it takes longer, but saves you a ton of money.
- Elastic Block Store (EBS): Super fast storage volumes attached to EC2 instances. Best for high performance needs but requires manual setup.
- Elastic File System (EFS): Managed, scalable file storage shared by multiple servers. Premium features at a premium price.
Databases: Structured Data for Every Appetite
Storing files is great, but what about structured data? Enter the database aisle, a place with almost too many choices:
- SimpleDB: AWS’s first foray into NoSQL databases. As the name suggests… perhaps a little too basic for most real world applications.
- DynamoDB: Easily scalable, fast, and ideal for high volume, non relational workloads. Think of it as Amazon’s answer to the modern NoSQL challenge.
- DocumentDB: API compatible with MongoDB, yet not open source Mongo for licensing reasons. Useful if you want to deploy a Mongo like database without hosting headaches.
- Elasticsearch: Build lightning fast text search capabilities for your apps. Amazon’s version gets around licensing issues but delivers the same powerful search experience.
- RDS (Relational Database Service): Fully managed SQL databases, with support for MySQL, PostgreSQL, Oracle, and more.
- Aurora: Amazon’s proprietary flavor of SQL, offering MySQL or Postgres compatibility, optimized for cloud scale, cost, and performance. Try the serverless mode for pay as you go flexibility.
- Neptune: Graph database for highly connected datasets, great for social networks or recommendation engines.
- ElastiCache: Managed Redis serving blazing fast, in memory caching perfect for scaling APIs or real time data needs.
- Timestream: Time series database purpose built for tracking and querying data over time, such as stock market trends.
- Quantum Ledger Database: Keeps tamper evident, cryptographically signed transaction logs, ideal for regulatory or blockchain like needs.
Analytics and Machine Learning: Making Sense (and Predictions) from Data
Your data is only as valuable as the insights you gain from it. AWS delivers a toolkit for every stage of analysis and ML:
- Redshift: Data warehousing for large businesses. Store structured data from multiple sources for unified analysis and reporting.
- Lake Formation: Build vast “data lakes” for storing all your raw, unstructured data, making it queryable alongside structured warehouse data.
- Kinesis: Real time streaming data capture, letting you analyze business or app activity the moment it happens.
- Elastic MapReduce (EMR): Harness Apache Spark and other frameworks for distributed, high speed processing of massive datasets.
- MSK (Managed Streaming for Kafka): For those who love Apache Kafka’s open source streaming. Fully managed, ready to process vast data flows.
- Glue: Serverless ETL (extract, transform, load). Quickly wrangle data from S3, Redshift, or Aurora, and build data pipelines visually with Glue Studio.
Machine Learning on AWS
- Data Exchange: Buy and subscribe to high quality datasets from third parties, a mega boon if you lack proprietary data.
- SageMaker: End to end machine learning platform. Build, train, and deploy ML models using familiar frameworks (TensorFlow, PyTorch, etc.) with managed notebooks and scalable compute.
- Rekognition: Ready made computer vision API. Automatically classify images, detect objects skip building CV models from scratch!
- Lex: Build chatbots and conversational UIs powered by Alexa grade AI.
- DeepRacer: Learn ML by programming and racing an actual cloud connected car a fun way to build skills and experiment.
Developer Essentials: Security, Notifications, and Infrastructure as Code
- IAM (Identity and Access Management): Control exactly who has access to your AWS resources, and what capabilities they have.
- Cognito: Add login, registration, and user management to your apps supporting username/password, social logins, and more.
- SNS (Simple Notification Service): Send push notifications to users’ devices.
- SES (Simple Email Service): Send bulk or transactional emails from your app straight from the cloud.
- CloudFormation: Build and manage infrastructure as code, using YAML or JSON templates. Spin up complex environments with one click no more clicking everywhere in the console.
- Amplify: Connect frontend apps (web, iOS, Android) to AWS with easy SDKs and managed services, streamlining DevOps for modern apps.
Don’t Forget: Keeping Cloud Costs Under Control
As you start provisioning all these amazing resources, remember: AWS’s power comes at a price, which (figuratively) fuels Jeff Bezos’s interstellar ambitions. Be sure to monitor your bill with Cost Explorer and Budgets, so you don’t get sticker shock or accidentally sponsor the next big rocket launch.
Conclusion: Exploring AWS, One Service at a Time
There you have it an epic journey down the aisles of AWS, uncovering the major ingredients for building modern apps, analyzing data, and scaling out futuristic solutions. This guide just scratched the surface of AWS’s ever growing offerings, and the best way to master them is to experiment, deploy, and explore.
If you enjoyed this deep dive, help support further quality cloud content by liking, sharing, or becoming a pro member at Fireship.io for access to more advanced tutorials. Thanks for joining us on this run through the AWS “supermarket” see you in the next installment!
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