AWS: On-Demand vs Reserved vs Spot Cost savings

AWS: On-Demand vs Reserved vs Spot Cost savings

How to manage your workloads for best cost optimisation

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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