AWS: On-Demand vs Reserved vs Spot Cost savings

Quick Comparison

On-Demand Instances

On-demand instances allow you to pay as you go with no upfront costs, offering flexibility for unpredictable workloads. They are ideal for development, testing, and short-term projects but come at a higher price compared to other options.

• Pricing: Pay-as-you-go; no upfront cost.
• Flexibility: No long-term commitment; ideal for unpredictable workloads.
• Use Cases: Development, testing, and short-term projects.
• Pros: Easy to scale up or down; no upfront payment.
• Cons: Highest cost compared to other instance types.

Reserved Instances

Reserved Instances require a 1- or 3-year commitment, providing significant cost savings of up to 75% and reserved capacity for predictable, steady-state workloads. This option is best suited for long-term projects with consistent usage patterns.

• Pricing: Up to 75% discount compared to On-Demand; requires upfront payment.
• Flexibility: 1 or 3-year commitment; reserved capacity.
• Use Cases: Predictable, steady-state workloads.
• Pros: Significant cost savings; capacity reservation.
• Cons: Less flexibility; requires long-term commitment.

Spot Instances

Spot Instances offer the lowest cost, with up to 90% savings compared to On-Demand, by taking advantage of unused EC2 capacity. They are perfect for fault-tolerant, flexible workloads like batch processing and data analysis, though they come with the risk of interruptions by AWS.

• Pricing: Up to 90% discount compared to On-Demand; variable pricing.
• Flexibility: Instances can be terminated by AWS with short notice.
• Use Cases: Batch processing, data analysis, and flexible applications.
• Pros: Lowest cost; great for fault-tolerant and flexible workloads.
• Cons: Risk of interruption; not suitable for critical applications.

Workload Management for Best Cost Optimisation

Different types of workloads can be split into On-Demand, Reserved, and Spot to ensure you are optimizing for your compute costs at every step.

On-Demand Instances

• Development and testing environments
• Short-term projects
• Unpredictable workloads
• Applications with variable or temporary usage

Reserved Instances

• Long-term applications
• Predictable, steady-state workloads
• Large enterprises with consistent usage patterns
• Critical applications requiring reserved capacity

Spot Instances

• Batch processing
• Data analysis
• High-performance computing
• Fault-tolerant and flexible applications
• Big data workloads
• CI/CD pipelines

This is the first stage to start saving costs, next steps are to dynamically migrate workloads on compute and time patterns to save additional costs at a monthly level. We will share more about that soon!

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