Services Comparison
Quick reference for choosing the right AWS service.
Endpoint Types
| Type |
Latency |
Payload |
Timeout |
Cost Model |
Use Case |
| Real-time |
Milliseconds |
6 MB |
60s |
Per hour |
Interactive apps |
| Serverless |
Seconds (cold start) |
6 MB |
60s |
Per request |
Variable traffic |
| Async |
Minutes |
1 GB |
15 min |
Per hour |
Large payloads |
| Batch Transform |
Hours |
- |
- |
Per job |
Offline batch |
Data Processing Services
| Service |
Mode |
Use Case |
Scalability |
| Glue ETL |
Batch |
Large-scale ETL |
Auto-scaling |
| Glue DataBrew |
Batch |
Visual prep |
Managed |
| EMR |
Batch |
Custom Spark |
Manual/Auto |
| Kinesis Data Streams |
Streaming |
Custom consumers |
Shards |
| Kinesis Firehose |
Streaming |
Direct to S3/etc |
Automatic |
| SageMaker Processing |
Batch |
ML data prep |
Instance-based |
Storage for ML
| Service |
Data Type |
Access Pattern |
Use Case |
| S3 |
Any |
Object access |
Data lake, models |
| Feature Store Online |
Features |
Low-latency |
Real-time inference |
| Feature Store Offline |
Features |
Batch queries |
Training |
| Redshift |
Structured |
SQL queries |
Analytics |
| DynamoDB |
Key-value |
Low-latency |
Application data |
MLOps Orchestration
| Service |
Focus |
Best For |
| SageMaker Pipelines |
ML-specific |
End-to-end ML workflows |
| Step Functions |
General |
Multi-service orchestration |
| MWAA (Airflow) |
General |
Complex DAGs, existing Airflow |
| EventBridge |
Events |
Event-driven triggers |
Hyperparameter Tuning Strategies
| Strategy |
Best For |
Speed |
Quality |
| Bayesian |
Most cases |
Fast |
High |
| Random |
Exploration |
Medium |
Medium |
| Grid |
Small space |
Slow |
Complete |
| Hyperband |
Deep learning |
Fast |
High |
Monitoring Services
| Service |
Purpose |
Data Type |
| Model Monitor |
Drift detection |
ML metrics |
| CloudWatch Metrics |
Infrastructure |
Time series |
| CloudWatch Logs |
Application logs |
Text |
| CloudTrail |
API audit |
Events |
| X-Ray |
Distributed tracing |
Traces |
Security Services
| Service |
Purpose |
| IAM |
Identity and access |
| KMS |
Encryption keys |
| Secrets Manager |
Credentials |
| Macie |
Sensitive data discovery |
| VPC |
Network isolation |
| Security Groups |
Instance firewall |
AI Services vs Custom ML
| Use Case |
AI Service |
Custom (SageMaker) |
| Text sentiment |
Comprehend |
Custom NLP |
| Object detection |
Rekognition |
Custom CV |
| Speech-to-text |
Transcribe |
Custom ASR |
| Translation |
Translate |
Custom NMT |
| Recommendations |
Personalize |
Custom RecSys |
| Forecasting |
Forecast |
Custom models |
Bedrock vs SageMaker
| Aspect |
Bedrock |
SageMaker |
| Model type |
Foundation models |
Any ML model |
| Training |
Fine-tuning only |
Full training |
| Infrastructure |
Serverless |
Managed instances |
| Customization |
Limited |
Full control |
| Use case |
GenAI apps |
Custom ML |