🧠 What is AWS Batch?

AWS Batch is a fully managed service that efficiently runs hundreds or thousands of batch computing jobs on AWS.

āœ… It dynamically provisions the right compute resources (EC2 or Spot) and schedules jobs based on their requirements and priority.


šŸ“¦ Use Cases

Use Case Example
Data Processing ETL, log analysis, data normalization
Image & Video Rendering Render farm jobs for animation or video pipelines
Machine Learning Large-scale training and inference jobs
Genomic Processing DNA sequencing workflows
Simulations Monte Carlo simulations, scientific calculations

āš™ļø Key Components of AWS Batch

Component Description
Job A unit of work (like a script or container task)
Job Definition Specifies how to run the job (e.g., Docker image, vCPUs, memory)
Job Queue Where jobs are submitted; maps to compute environments
Compute Environment Manages compute resources (EC2, Spot, Fargate) to run jobs
Scheduler Determines when and where jobs run based on priority and resources

šŸš€ How AWS Batch Works

1. Submit job → 
2. Job goes into queue → 
3. AWS Batch scheduler evaluates → 
4. Dynamically provisions compute → 
5. Runs job using Docker container → 
6. Job completes → compute deallocates

šŸ”§ Job Definition Example (JSON)

{
Ā  "jobDefinitionName": "data-processing-job",
Ā  "type": "container",
Ā  "containerProperties": {
Ā  Ā  "image": "my-docker-image:latest",
Ā  Ā  "vcpus": 2,
Ā  Ā  "memory": 2048,
Ā  Ā  "command": ["python", "process.py"]
Ā  }
}

🧰 Execution Example using AWS CLI

aws batch submit-job \
Ā  --job-name sample-job \
Ā  --job-queue my-queue \
Ā  --job-definition data-processing-job

ā˜ļø Compute Environment Types

Type Description
Managed AWS handles instance provisioning and scaling
Unmanaged You provide and manage the EC2 instances
Fargate Serverless — no EC2 needed (for smaller jobs)

šŸ“ˆ Benefits of AWS Batch

Benefit Description
Fully Managed No need to manage batch schedulers or servers
Scales Automatically Based on workload
Cost-Efficient Supports EC2 Spot Instances
Containerized Jobs Supports Docker images
Prioritized Queues Assign different priorities

šŸ›‘ Limitations

  • Cold start latency if no compute is running
  • Job dependency graph is limited in complexity
  • Requires VPC/subnet setup for compute environments

āœ… Summary

Feature AWS Batch
Scheduler Built-in job scheduling
Resource Provisioning Dynamic (EC2, Spot, Fargate)
Pricing Pay only for underlying compute (no extra fees)
Job Packaging Docker container image
Integration CloudWatch, IAM, S3, ECR, ECS, Lambda, etc.
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