GCP Compute VM Pricing Overview
Google Cloud offers different pricing models for Compute Engine VMs. Here’s a brief summary of the pricing models and which one offers the best balance of discount and flexibility.
1️. On-Demand Pricing (Pay-As-You-Go)
How it works: You pay for the VM per second with no commitment.
Best for: Short-term workloads, unpredictable demand, or development/testing.
Downside: Most expensive option compared to discounts available via commitment plans.
2️. Committed Use Discounts (CUDs) - Commitment-Based Pricing
How it works: Commit to using a specific VM (CPU & RAM) for 1 or 3 years and get up to 57% discount (compared to on-demand).
Flexibility:
Cannot change machine family (e.g., from n1 to e2).
Can change size within the same family.
Cannot change region after commitment.
Best for: Long-running workloads where you know the resource needs.
🔹 Alternative: You can choose Flexible CUDs (newer option) where you commit to a specific amount of vCPUs and RAM but can change machine types and regions within that commitment.
3️. Spot VMs - Cheapest but No Uptime Guarantee
How it works: Get up to 91% discount, but Google can shut down the VM anytime when resources are needed.
Flexibility:
No commitment, no minimum usage.
Can change machine type, family, and region anytime.
Best for: Batch jobs, data processing, AI/ML training, and workloads that can handle interruptions.
Downside: Not for critical applications since VMs can be terminated anytime.
4️. GCP Savings Plan (New Alternative to CUDs) - More Flexible Commitment
How it works: Commit to a spending amount per hour for 1 or 3 years instead of committing to specific VM types.
Flexibility:
You can change machine types, regions, and families.
More flexible than CUDs but discounts may be lower (~20-30% vs. up to 57% in CUDs).
Best for: Organizations that want discounts but need flexibility in machine types and regions.
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