Understand the Savings Options Across Providers

• AWS offers Savings Plans for flexibility and Reserved Instances (RIs) for predictable workloads, with up to 72% savings.
• Azure's Savings Plans for Compute allow flexibility, while RIs cater to fixed, long-term workloads.
• GCP uses Committed Use Discounts (CUDs) with resource- or spend-based commitments, offering up to 60% savings.

Match Workloads with the Right Plan

• Dynamic Workloads: Savings Plans (AWS, Azure) and Spend-Based CUDs (GCP) offer flexibility.
• Stable Workloads: RIs (AWS, Azure) or Resource-Based CUDs (GCP) provide maximum savings for predictable usage.
• Analyze Usage to Optimize Commitments

Use native tools like AWS Cost Explorer, Azure Advisor, and GCP Billing Reports to analyze past usage and identify consistent patterns.
Leverage recommendations from these tools to determine optimal commitment levels.

Key Considerations When Choosing Plans

• Workload Predictability: Dynamic workloads benefit from flexible plans; stable workloads thrive on fixed commitments.
• Commitment Length: Longer terms (3 years) yield higher discounts but less flexibility.
• Payment Options: Evaluate upfront vs. monthly payments based on cash flow.

Savings Potential by Cloud Provider

• AWS: Up to 72% savings with Compute Savings Plans and RIs.
• Azure: Up to 65-72% savings with Compute Plans and RIs.
• GCP: Up to 60% savings with Committed Use Discounts.

Streamline with Automation

Manual calculations can be time-consuming. Platforms like Cloudgov.ai simplify cloud cost optimization by automating savings insights with AI/ML-driven recommendations, freeing up engineering resources for innovation. Know more about it here.

💡 Conclusion: Savings Plans, RIs, and CUDs are indispensable for cost optimization. By aligning your choice with workload needs, you can achieve significant cloud cost savings and improve ROI. Explore Cloudgov.ai to automate and maximize your cloud investments across AWS, Azure, and GCP!