Cheat Sheet #day26 - AWS Compute Services

Cheat Sheet #day26 - AWS Compute Services

AWS Compute Services Cheat Sheet

AWS offers a variety of compute services that cater to different workload requirements, scalability needs, and pricing models. This cheat sheet provides an overview of key AWS compute services, their use cases, and important features.

Amazon EC2 (Elastic Compute Cloud)

  • Description: Virtual servers in the cloud for running applications.

  • Use Cases:

    • Hosting websites and web applications

    • Running backend servers for mobile and enterprise applications

    • Big data processing and analytics

    • Testing and development environments

  • Key Features:

    • Scalable compute capacity

    • Choice of instance types (e.g., general purpose, memory optimized, GPU instances)

    • Customizable security settings (Security Groups, IAM roles)

    • Integration with other AWS services (EBS, S3, RDS)

Amazon EC2 Auto Scaling

  • Description: Automatically adjusts capacity to maintain steady and predictable performance.

  • Use Cases:

    • Handling variable workloads

    • Scaling in and out based on demand

    • Ensuring fault tolerance and high availability

  • Key Features:

    • Automatic scaling policies based on metrics (CPU utilization, network traffic)

    • Integration with Elastic Load Balancing (ELB)

    • Lifecycle hooks for customizing scaling behavior

AWS Lambda

  • Description: Serverless computing service, runs code in response to events.

  • Use Cases:

    • Real-time file processing

    • Backend services for mobile and web applications

    • IoT device data processing

    • Scheduled tasks and automation

  • Key Features:

    • Pay-per-use pricing model (billed for compute time)

    • Support for multiple programming languages (Node.js, Python, Java, etc.)

    • Integrated with other AWS services (S3, DynamoDB, SQS)

    • Built-in monitoring and logging through AWS CloudWatch

AWS Elastic Beanstalk

  • Description: Platform as a Service (PaaS) for deploying and managing applications.

  • Use Cases:

    • Web application hosting

    • Microservices architecture deployment

    • Container-based applications (Docker)

  • Key Features:

    • Automated environment provisioning

    • Load balancing and auto-scaling

    • Integrated with AWS services (RDS, DynamoDB, S3)

    • Supports multiple programming languages (Java, .NET, PHP, Python, Node.js, Ruby)

Amazon Lightsail

  • Description: Virtual private servers (VPS) that include everything needed to deploy applications.

  • Use Cases:

    • Simple web hosting

    • Development and testing environments

    • Small-scale applications

  • Key Features:

    • Fixed monthly pricing (includes compute, storage, and data transfer)

    • Easy management through AWS Management Console

    • Integrated with AWS services (RDS, S3)

AWS Batch

  • Description: Fully managed batch processing at any scale.

  • Use Cases:

    • Big data processing

    • Data warehousing

    • ETL (Extract, Transform, Load) jobs

  • Key Features:

    • Efficiently run hundreds to thousands of batch computing jobs

    • Dynamically scale based on computing needs

    • Integrated with AWS services (S3, DynamoDB, etc.)

Amazon EKS (Elastic Kubernetes Service)

  • Description: Managed Kubernetes service for container orchestration.

  • Use Cases:

    • Containerized application deployment

    • Microservices architecture

    • Hybrid cloud deployments

  • Key Features:

    • Kubernetes control plane management

    • Integration with AWS services (EBS, IAM, VPC)

    • Automatic scaling and updates

Amazon ECS (Elastic Container Service)

  • Description: Fully managed container orchestration service for Docker containers.

  • Use Cases:

    • Containerized application deployment

    • Microservices architecture

    • Highly scalable and fault-tolerant applications

  • Key Features:

    • Integration with AWS services (ELB, IAM, CloudWatch)

    • Seamless scaling and load balancing

    • Supports Docker container management

Amazon EC2 Spot Instances

  • Description: Purchase spare EC2 compute capacity at reduced rates.

  • Use Cases:

    • Batch processing

    • Fault-tolerant applications

    • Test and development workloads

  • Key Features:

    • Significant cost savings compared to On-Demand instances

    • Flexible pricing model (bid for instance capacity)

    • Integration with Auto Scaling for fault tolerance

Amazon EC2 Dedicated Hosts

  • Description: Physical EC2 server dedicated for your use.

  • Use Cases:

    • Compliance requirements

    • Licensing implications

    • Workloads needing a specific hardware configuration

  • Key Features:

    • Full control over instance placement

    • Visibility into underlying infrastructure

    • Ability to use existing server-bound software licenses

Amazon EC2 Image Builder

  • Description: Automated image creation for EC2 instances.

  • Use Cases:

    • Standardize OS configurations

    • Create golden images for deployment

    • Continuous integration and delivery pipelines

  • Key Features:

    • Simplifies image management

    • Supports custom configurations and scripts

    • Integration with AWS services (S3, EC2, CloudFormation)

Amazon EC2 Instance Types

  • Description: Various configurations of virtual machines to meet different workload needs.

  • Use Cases:

    • Compute-optimized instances for CPU-intensive applications

    • Memory-optimized instances for large-scale databases

    • GPU instances for machine learning and graphic-intensive workloads

  • Key Features:

    • Diverse selection of instance types (e.g., T3, M5, C5, P3)

    • Options for storage, memory, and network performance

    • Choice of purchasing options (On-Demand, Reserved, Spot)

This cheat sheet provides a quick reference to AWS compute services, highlighting their use cases, key features, and integration capabilities. For detailed information and updates, refer to the AWS documentation.

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