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Reserved Instances and Savings Plans: Maximising Cloud Commitment Discounts
Cloud Strategy

Reserved Instances and Savings Plans: Maximising Cloud Commitment Discounts

Commitment discounts are the single biggest lever for reducing cloud costs. Getting the strategy right requires understanding the options across AWS, Azure, and GCP.

Published 15 February 2026 9 min read

## The Biggest Quick Win in Cloud Cost Optimisation

If your organisation is running significant cloud workloads on on-demand pricing without any commitment discounts, you're paying 40-72% more than you need to for those workloads. That's the discount range available through 1-year and 3-year commitments, and it represents the single largest cost optimisation lever available for most cloud-spending organisations.

The hesitation to commit is understandable — you're paying for capacity whether you use it or not, and committing to the wrong amount or instance type creates waste. But the fear of commitment waste is often overweighted relative to the cost of on-demand pricing. Even with 20% commitment waste (you're using 80% of what you committed to), the economics of committed pricing typically win over on-demand.

## AWS: Reserved Instances vs. Savings Plans

AWS offers two main paths to commitment discounts. Reserved Instances (RIs) apply to specific instance types in specific regions. They offer the highest discounts (up to 72% for 3-year all-upfront) but require more specific commitments about instance type, size, and region. They're best for stable workloads where you're confident about instance type and region.

Savings Plans are more flexible — you commit to a dollar amount of compute spend per hour, and the discount applies automatically across any instance type, size, operating system, or region (for Compute Savings Plans). The discount is slightly lower than RIs (up to 66%) but the flexibility is often worth the difference, particularly for organisations with dynamically changing workloads.

The practical strategy for most AWS customers is: cover your stable baseline compute with Compute Savings Plans (maximum flexibility), use instance-specific RIs only for workloads where you're very confident about instance type stability, and keep variable and uncertain workloads on on-demand or spot.

## Azure Reserved VM Instances and Savings Plans

Azure Reserved VM Instances (RVMIs) provide discounts of 40-72% on VM compute costs for 1-year or 3-year commitments. Azure also introduced Azure Savings Plans in 2022, which like AWS Compute Savings Plans, apply discounts flexibly across VM series and regions within a geographic scope.

Azure Hybrid Benefit — allowing you to use existing Windows Server and SQL Server licences for Azure VMs — compounds with Reserved Instance pricing. The combination of Hybrid Benefit and RI pricing can reduce Windows Server VM costs by up to 80% compared to on-demand pricing for equivalent unlicensed instances.

Azure's reservations extend beyond just VMs — you can purchase reserved capacity for SQL Database, Cosmos DB, Azure Cache for Redis, Synapse Analytics, and other services. Many organisations focus only on VM reservations and miss the savings available on PaaS services, which often represent a significant portion of their Azure spending.

## GCP Committed Use Discounts

Google Cloud handles commitment pricing somewhat differently with Committed Use Discounts (CUDs) and Sustained Use Discounts (SUDs). SUDs apply automatically — GCP gives you a discount on any resource you run for more than 25% of a month without any commitment needed. CUDs are explicit commitments for 1 or 3 years that stack on top of sustained use discounts.

For GCP, the commitment decision is simpler than AWS because the flexible discount structure means you're already getting automatic discounts on sustained workloads. CUDs make sense for resources you're confident you'll maintain long-term and where the additional CUD discount justifies the commitment.

*For cloud financial optimisation and commitment discount strategy, contact Lara IT Solutions on 0330 043 1930.*