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Learning Objectives & Key Takeaways
0 / 4 Completed- Understand AWS core architecture and runtime execution model
- Audit real-world latency, throughput benchmarks, and memory footprint
- Implement zero-downtime deployment patterns with resilience guards
- Verify code snippets and architect blueprints against production SLOs
Architecture Ready
100%
What you will learn
- EKS gave a six-person team a Kubernetes control plane they did not have the headcount to operate safely.
- Only the Service Quotas CLI commands, the EC2 L-1216C47A example, and Bedrock Knowledge Bases plus S3 are pulled from AWS's own docs here.
- Compute choice usually comes down to how long a task runs and how spiky its traffic is, not which service sounds most modern.
- DynamoDB rewards teams who know their access pattern upfront and punishes teams who pick it before they do.
- Script a quota check before a launch instead of discovering a default limit during an incident.
The Friday Night EKS Outage That Was Really a Service Choice
A six-person fintech startup had just moved its lending product off a simple platform onto Amazon EKS because a new hire had strong Kubernetes opinions and the rest of the team went along with it.
The actual workload was three services with predictable, moderate traffic and a nightly batch job, nothing that needed Kubernetes-specific tooling or multi-cloud portability.
In the rest of this story
- What's Actually From AWS's Docs Here, and What's Field Experience
- Compute: EC2, Lambda, ECS, and EKS — When Each One Earns Its Keep
- Data: S3, RDS and Aurora, and DynamoDB — Matching the Store to the Access Pattern
- Edge, Identity, and AI: CloudFront, IAM, and Bedrock
- Check Your Quotas Before You Commit to a Service
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