DEV Community

Cover image for Comprehensive Guide to AWS Services and Their Applications
Harshit Singh
Harshit Singh

Posted on

Comprehensive Guide to AWS Services and Their Applications

AWS offers a mind-boggling array of services, each with its own niche and capabilities. Here’s a crash course on the what, why, when, and where of AWS services, broken into bite-sized bullet points.


1. Amazon EC2: Virtual Servers for Computing

  • What: Virtual machines in the cloud.

  • Why: Host backend applications, run batch jobs, or host services needing high control.

  • When: You need customizable servers or want to run heavy workloads like Java Spring Boot applications.

  • Used With: Any backend framework (Java, Python, Node.js).


2. Amazon S3: Scalable Object Storage

  • What: Storage for any type of file or object.

  • Why: To store static assets like images, videos, documents, and React frontend builds.

  • When: You need highly available storage or to host static websites.

  • Used With: Frontend frameworks like React, Angular, and Vue.


3. Amazon RDS: Managed Relational Databases

  • What: Fully managed SQL databases (PostgreSQL, MySQL, OracleDB, etc.).

  • Why: Simplifies database administration tasks like backups and patching.

  • When: Your project requires structured data storage and ACID compliance.

  • Used With: Backend frameworks (Java, Spring Boot) for traditional web apps.


4. Amazon DynamoDB: NoSQL Database Service

  • What: Fast and flexible NoSQL database.

  • Why: For projects with unstructured or semi-structured data and low-latency requirements.

  • When: You’re dealing with real-time applications like user profiles or session storage.

  • Used With: Mobile apps, IoT, or Node.js.


5. Amazon VPC: Virtual Private Cloud

  • What: A private, isolated network for your AWS resources.

  • Why: To ensure secure communication and restrict unauthorized access.

  • When: Security is a priority, especially in microservices architecture.

  • Used With: All backend services, databases, and load balancers.


6. Amazon IAM: Identity and Access Management

  • What: Controls access to AWS resources.

  • Why: To grant users and applications specific permissions.

  • When: Always! Security and access control are critical.

  • Used With: All AWS services.


7. Amazon Route 53: DNS and Traffic Management

  • What: DNS and domain routing service.

  • Why: For managing domain names and directing traffic.

  • When: Your app has a custom domain like myapp.com.

  • Used With: S3, CloudFront, and backend services.


8. Amazon CloudFront: Content Delivery Network

  • What: Distributes content globally with low latency.

  • Why: To serve static assets (React builds, videos) faster with HTTPS.

  • When: You have global users accessing your app.

  • Used With: S3, EC2, or any hosting service.


9. Amazon CloudWatch: Monitoring and Logging

  • What: Centralized monitoring for AWS services.

  • Why: Track performance, set alarms, and debug issues.

  • When: Your project scales, and observability becomes crucial.

  • Used With: EC2, Lambda, RDS, and other AWS resources.


10. AWS Lambda: Serverless Compute Service

  • What: Runs code without managing servers.

  • Why: Ideal for event-driven applications.

  • When: Need to run short-lived tasks like processing S3 uploads.

  • Used With: DynamoDB, S3, API Gateway.


11. Amazon EBS: Block Storage Volumes

  • What: Persistent storage for EC2 instances.

  • Why: To store data that needs to persist beyond server restarts.

  • When: Your backend needs local, high-performance storage.

  • Used With: EC2 instances.


AWS TOP 10 Services


12. Amazon Redshift: Data Warehousing Service

  • What: Scalable data warehouse.

  • Why: For running analytics on big data.

  • When: Your app generates a lot of structured data requiring complex queries.

  • Used With: Data analytics tools and ETL processes.


13. Amazon ElastiCache: In-Memory Data Store

  • What: Managed Redis or Memcached.

  • Why: For caching to improve application performance.

  • When: Your app has repetitive queries or session storage needs.

  • Used With: Backend frameworks, especially in microservices.


14. Amazon ECS: Container Orchestration Service

  • What: Manages Docker containers.

  • Why: To deploy and scale containerized applications.

  • When: You’re using containers for microservices.

  • Used With: Docker, Kubernetes.


15. Amazon EMR: Big Data Processing

  • What: Managed Hadoop and Spark clusters.

  • Why: For big data analytics and processing.

  • When: Your app handles large-scale data processing.

  • Used With: Data pipelines and analytics workflows.


16. Amazon Kinesis: Real-Time Data Streaming

  • What: Processes real-time data streams.

  • Why: To handle use cases like event logs or IoT data.

  • When: Real-time processing is a must.

  • Used With: Analytics dashboards and machine learning apps.


17. AWS CloudFormation: Infrastructure as Code

  • What: Automates resource provisioning.

  • Why: To manage resources declaratively.

  • When: Infrastructure management is becoming complex.

  • Used With: All AWS services.


18. AWS IAM Identity Center: Centralized Access Control

  • What: Single sign-on for multiple AWS accounts.

  • Why: Simplifies multi-account access.

  • When: You manage multiple AWS environments.

  • Used With: Enterprise setups.


19. Amazon API Gateway: API Management Service

  • What: Manages REST and WebSocket APIs.

  • Why: Simplifies building and deploying APIs.

  • When: Your app needs an API layer.

  • Used With: Lambda, EC2, DynamoDB.


20. Amazon Cognito: User Identity Management

  • What: Handles user signup, login, and authentication.

  • Why: To offload identity management.

  • When: Your app has user accounts.

  • Used With: Frontend and backend frameworks.


21. AWS Step Functions: Workflow Orchestration

  • What: Automates workflows.

  • Why: For managing distributed tasks.

  • When: You need coordination between multiple services.

  • Used With: Lambda, API Gateway.


22. Amazon Athena: Serverless Query Service

  • What: Queries S3 data using SQL.

  • Why: To extract insights from stored data.

  • When: Your app has raw data in S3.

  • Used With: Data lakes and BI tools.


23. Amazon QuickSight: Business Intelligence Tool

  • What: Creates dashboards and visualizations.

  • Why: To analyze and present data.

  • When: Your project needs reporting.

  • Used With: Redshift, Athena.


24. AWS Glue: Data Integration Service

  • What: ETL (Extract, Transform, Load) service.

  • Why: To process and transform data.

  • When: Your app requires data pipelines.

  • Used With: Redshift, S3, Athena.


25. Amazon AppStream 2.0: Desktop and App Streaming

  • What: Streams applications to end-users.

  • Why: For delivering desktop applications securely.

  • When: Your project needs remote app access.

  • Used With: Enterprise applications.


Top comments (0)