Compute Cost Optimization Strategy — AWS Solutions Architect (SAA-C03)
Fault tolerance and predictability define the purchase model
The scenario describes a batch analytics workload that runs six hours nightly and is fault-tolerant. The candidate selects On-Demand instances because the workload runs every day and feels like a baseline. The exam expects Spot Instances — the workload is interruptible, time-flexible within a window, and does not require continuous availability. Reserved Instances optimize cost for always-on predictable workloads. Savings Plans offer cross-family flexibility but still require committed usage. The deciding variable is always: can this workload tolerate interruption without failing the stated requirement?
What This Pattern Tests
The exam presents workload characteristics and tests pricing model selection. Spot Instances offer 60-90% savings for interruptible workloads — batch processing, CI/CD runners, data analytics. Compute Savings Plans offer 20-40% savings with flexibility across instance families, regions, and OS. EC2 Instance Savings Plans offer slightly deeper savings but lock to a specific instance family and region. Graviton3 instances provide ~25% better price-performance than comparable x86 instances. The trap is recommending Spot for a user-facing web tier (interruptions cause errors) or ignoring Graviton when the scenario mentions "optimize compute cost" for Linux workloads.
Decision Axis
Workload characteristics (interruptibility, predictability, architecture) determine pricing model. Spot for fault-tolerant, Savings Plans for steady, Graviton for ARM-compatible.
Associated Traps
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Decision Rules
Whether the workload's explicit interruptibility and non-continuous run profile (≈17% of daily hours) makes EC2 Spot Instances the dominant cost choice over commitment-based options such as Reserved Instances or Savings Plans that impose per-hour baseline charges on idle hours.
Domain Coverage
Difficulty Breakdown