The MLA-C01 exam retires on September 28, 2026
You can still take and pass the exam until then — plan your exam date accordingly.
Copyright (c) 2026 MindMesh Academy. All rights reserved. This content is proprietary and may not be reproduced or distributed without permission.
6.2. Quick Reference Decision Trees and Cheat Sheets
🎯 Quick Reference: Endpoint Selection
| Question | If Yes → | If No → |
|---|---|---|
| Need real-time predictions (<100ms)? | Real-time endpoint | Continue ↓ |
| Processing large payloads (>25MB) or long inference (>60s)? | Async endpoint | Continue ↓ |
| Traffic is intermittent (<1 req/min) and cold starts are OK? | Serverless endpoint | Continue ↓ |
| Processing large datasets without real-time need? | Batch Transform | Re-evaluate requirements |
🎯 Quick Reference: Managed vs. Custom Decision
🎯 Quick Reference: Data Prep Service Selection
| Scenario | Service | Why |
|---|---|---|
| Visual data exploration and transformation with minimal code | SageMaker Data Wrangler | Built-in visualizations, no Spark required |
| Large-scale ETL on petabyte data | AWS Glue | Serverless Spark, scales massively |
| Simple data transformations with recipe-based UI | AWS Glue DataBrew | 250+ built-in transformations, no code |
| Custom Spark processing on large datasets | Amazon EMR | Full Spark/Hadoop cluster control |
| Streaming data transformation | Amazon Kinesis + Lambda or Managed Flink | Real-time processing |
| Feature storage and reuse across teams | SageMaker Feature Store | Online (real-time) + offline (batch) stores |
🎯 Quick Reference: Monitoring Service Selection
| What to Monitor | Service | Trigger |
|---|---|---|
| Feature distributions vs. baseline | Model Monitor (Data Quality) | Scheduled job |
| Model accuracy vs. baseline | Model Monitor (Model Quality) | Requires ground truth |
| Fairness metrics for protected groups | Model Monitor (Bias Drift) via Clarify | Scheduled job |
| Endpoint latency, CPU, memory | CloudWatch Metrics + Alarms | Threshold-based |
| Error logs, stack traces | CloudWatch Logs + Logs Insights | Query-based |
| Cross-service request tracing | AWS X-Ray | On-demand |
| API call audit trail | AWS CloudTrail | Continuous |
| PII in training data | Amazon Macie | Scheduled scan |
| Resource configuration compliance | AWS Config | Rule-based |
🎯 Quick Reference: Security Controls
| Protection Layer | Service | What It Controls |
|---|---|---|
| Identity (who) | IAM roles, policies, SageMaker Role Manager | What actions users and services can perform |
| Network (where) | VPC, security groups, network isolation, PrivateLink | What resources can communicate |
| Data (what) | KMS, SSE, Secrets Manager | Whether data is readable if intercepted |
| Audit (when/how) | CloudTrail, Config, Macie | Whether policies are followed |
🎯 Quick Reference: Cost Optimization by Workload
| ML Workload | Pricing Strategy | Additional Savings |
|---|---|---|
| Training jobs (fault-tolerant) | Spot Instances (up to 90% off) | Use managed spot training with checkpointing |
| Production endpoint (24/7 steady) | Savings Plans (30-72% off) | Rightsizing with Inference Recommender |
| Production endpoint (variable) | On-Demand + auto scaling | Scale to zero during off-hours |
| Low-traffic endpoint (<1 req/min) | Serverless endpoint | Pay only per invocation |
| Batch scoring (weekly) | Batch Transform + Spot | No persistent endpoint cost |
| Development/notebooks | On-Demand + lifecycle configs | Auto-stop idle notebooks |
Written byAlvin Varughese
Founder•20 professional certifications