Explore how to balance Point-in-Time Recovery, Global Tables, and backup strategies to meet aggressive disaster recovery objectives for DynamoDB workloads without over-engineering.
Discover why choosing the right load balancer type is critical for detecting application-layer failures and improving availability without custom scripting.
A professional-level analysis of migrating bursty, hour-long file processing from on-premises to AWS, comparing Lambda limitations, EC2 Auto Scaling, MQ vs. SQS, and EFS vs. S3 storage—culminating in a FinOps-driven decision matrix.
A high-level analysis of DynamoDB billing models (Provisioned vs. On-Demand) and how Reserved Capacity combined with Auto Scaling delivers optimal TCO for write-heavy workloads with predictable weekly peaks.
A simulated SAA-C03 scenario exploring how to architect high availability for a mission-critical web application using Aurora PostgreSQL and Auto Scaling groups, focusing on the balance between availability guarantees and operational simplicity.
A global gaming startup runs multiple VPC-native GKE clusters on a shared subnet and faces IP exhaustion. This drill analyzes the best approach to scale node pools without network disruptions.
A manufacturing company needs high-availability hybrid connectivity to AWS with stable latency, minimal cost, and tolerance for slower backup. Learn why Direct Connect + VPN backup is the optimal solution over dual Direct Connect or dual VPN approaches.
This drill explores how to reduce cloud spending for a high-security image processing service by optimizing VPC networking—specifically choosing between NAT Gateways and S3 Gateway Endpoints for 1TB daily S3 data transfer.
A retail analytics company faces duplicate database records despite unique SQS messages. This drill examines why visibility timeout extension is the correct solution and how it prevents race conditions in distributed message processing.
A fintech startup must handle 500K requests per second with cost constraints. This drill explores managed compute vs. VM autoscaling and BigQuery vs. Bigtable for real-time exact-match storage.