What each service does, where it fits and how to try it in a real lab.
Durable object storage for files, application assets and data lakes.
When to choose: Store objects independently of compute and retain multiple versions.
Tradeoff: Use EBS for a block device or EFS for a shared file system.
Official AWS documentation
A serverless SQL query service for analyzing data in S3.
When to choose: Explore a data lake with SQL without operating a query cluster.
Tradeoff: Evaluate Redshift for a managed warehouse; RDS for application transactions.
Official AWS documentation
The Data Catalog stores database and table metadata used by query engines.
When to choose: Share table definitions between analytics tools. This lab uses the catalog, not Glue ETL jobs.
Tradeoff: A catalog does not store the underlying rows; the files remain in S3.
Official AWS documentation
Runs event-driven application code without managing servers.
When to choose: Execute short, stateless tasks in response to events.
Tradeoff: Use ECS or EC2 for long-running workers or specialized runtime requirements.
Official AWS documentation
A managed queue that buffers messages between producers and consumers.
When to choose: Absorb traffic spikes and retry background work independently of the producer.
Tradeoff: Use SNS for fan-out, EventBridge for event routing, or Kinesis for a replayable stream.
Official AWS documentation
Policies and roles control which identities can perform actions on AWS resources.
When to choose: Grant a workload only the actions and resources it needs using temporary role credentials.
Tradeoff: Use IAM Identity Center for workforce sign-in; avoid embedding long-lived credentials in code.
Official AWS documentation
Collects logs and metrics to help you understand workload behavior.
When to choose: Inspect application output, failures and operational signals.
Tradeoff: Use CloudTrail to investigate AWS API activity; it serves a different purpose than application logs.
Official AWS documentation