Overview
Both are ways to rent compute capacity from a cloud provider, but they trade cost against reliability in opposite directions. Spot Instances tap into unused capacity at steep discounts but can be reclaimed with almost no notice, while On-Demand Instances cost more per hour in exchange for a guaranteed, uninterrupted slot.
Comparison Diagram
Comparison Table
| Aspect | Spot Instances | On-Demand Instances |
|---|---|---|
| Request & provisioning | Fulfilled only if provider has spare capacity at your bid price | Fulfilled immediately from reserved capacity pools |
| Capacity guarantee | None — provider can reclaim the instance at any time | Guaranteed for as long as you keep paying |
| Pricing model | Variable, set by real-time supply and demand for spare capacity | Fixed hourly rate published by the provider |
| Interruption behavior | Reclaimed with a short warning (e.g. ~2 minutes on AWS) | Never interrupted by the provider; you control shutdown |
| Cost predictability | Fluctuates; can spike or be revoked when demand rises | Stable and predictable, easy to forecast in a budget |
| Ideal workloads | Fault-tolerant, stateless, or checkpointable batch jobs | Stateful, latency-sensitive, or continuously running services |
| Termination control | Provider-initiated; your app must handle abrupt shutdown | User-initiated; you decide exactly when it stops |
Key Differences
- Spot pricing floats with market demand and can be up to 90% cheaper than On-Demand rates
- Spot capacity is reclaimable at any time, typically with only a short warning window
- On-Demand gives a firm capacity guarantee that Spot never promises
- Workloads on Spot need to tolerate sudden termination or design for checkpointing
- On-Demand cost is fixed and predictable, while Spot cost is variable and market-driven
When to Use Each
Spot Instances
- Batch data processing: Jobs like log aggregation or ETL can checkpoint progress and resume cheaply if a Spot instance is reclaimed.
- CI/CD build fleets: Short-lived, parallelizable build and test runners tolerate interruption without affecting production.
- Large-scale simulations: Distributed training or rendering jobs can lose individual nodes without losing the overall run.
- Autoscaled stateless workers: A fleet behind a load balancer can absorb individual node loss with no user-facing impact.
On-Demand Instances
- Production databases: Stateful services that can’t tolerate abrupt shutdown need guaranteed, uninterrupted capacity.
- Customer-facing APIs: Latency-sensitive traffic requires instances that won’t vanish mid-request.
- Unpredictable spiky demand: When you must scale up immediately regardless of spot market availability, On-Demand guarantees the capacity is there.
- Short one-off tasks: For a quick job where setup time to handle interruptions isn’t worth it, On-Demand is simpler to reason about.