Stop Overpaying for Cloud: A Guide to Maximizing Savings with Flexible Compute Commitments
Controlling cloud infrastructure costs is a top priority for any organization operating at scale. While on-demand pricing offers incredible flexibility, it can lead to unpredictable bills. For years, the primary tool for managing this has been Committed Use Discounts (CUDs), which provide significant savings in exchange for a one or three-year commitment. However, traditional CUDs often came with a major drawback: rigidity.
Committing to a specific machine family or series meant that if your technical needs evolved, your discount could be left on the table, unused. This inflexibility created financial risk and administrative overhead. Fortunately, a more intelligent, spend-based approach has emerged, and it’s now more powerful than ever.
The Problem with Inflexible Commitments
Traditional resource-based commitments lock you into a specific amount of vCPUs and memory within a single machine series (like N2 or C2) in a particular region. While effective for highly stable and predictable workloads, this model breaks down when you need to:
- Modernize your instances: Upgrading from an older machine series to a newer, more powerful one could invalidate your existing discount.
- Adapt to changing needs: A project might shift from a general-purpose machine to a compute-optimized one, leaving your original commitment underutilized.
- Balance different VM types: You might be using a mix of machine series, making it complex to purchase and manage multiple, separate CUDs.
Any unused portion of your commitment is wasted money. This forces a difficult choice between architectural agility and cost savings—a choice no engineering team should have to make.
A Smarter Way to Save: The Power of Spend-Based CUDs
Instead of committing to a set number of resources, flexible, spend-based CUDs allow you to commit to a specific hourly dollar amount of compute spend in a chosen region. This is a fundamental shift that decouples your discount from the underlying hardware specifics.
With this model, your committed discount automatically applies to your aggregated usage of vCPUs and memory across a wide range of machine series. You could run an N2 instance in the morning and a C3 instance in the afternoon, and your single, flexible CUD would apply its discount to both. This ensures you are constantly maximizing your savings, regardless of the specific VMs you deploy.
The core benefit is simple: as long as your total hourly spend on eligible compute resources meets your commitment level, you receive the full discount. This approach drastically reduces the risk of commitment waste and simplifies cost management.
Expanded Coverage Delivers Unprecedented Savings
The real game-changer is the newly expanded scope of what these flexible, spend-based CUDs cover. The pool of eligible resources has grown, making it easier than ever to achieve 100% utilization of your commitment.
Flexible CUDs now provide discounted coverage for an extensive list of Compute Engine resources, including:
- General-purpose machine families: E2, N2, N2D, N1, and Tau T2D.
- Compute-optimized families: C3 and C2.
- Memory-optimized families: M1, M2, and M3.
- Accelerator-optimized families: A2.
- Spot VMs (previously known as preemptible VMs): This is a massive advantage, as the unpredictable nature of Spot VM usage is now covered by your baseline commitment.
- Sole-tenant nodes: For workloads requiring dedicated physical hardware for security or compliance.
This broad coverage means you can confidently purchase a single, spend-based CUD for a region, knowing it will apply to nearly all of your VM usage, from long-running applications to ephemeral Spot VMs.
Actionable Steps to Optimize Your Cloud Bill Today
Ready to take control of your compute spending? Follow these steps to leverage the power of flexible CUDs.
- Analyze Your Baseline Spend: Use your cloud provider’s cost management dashboard to identify your minimum, consistent hourly compute spend over the last month. Look for the “low water mark” of your usage—this is the safest amount to commit to.
- Model Your Commitment: Use the official pricing calculator to model a spend-based CUD based on your baseline usage. The tool will show you the exact monthly savings you can expect for a one or three-year term. Even a small commitment covering your consistent 24/7 workloads can yield substantial savings.
- Prioritize Flexibility: If your teams frequently experiment with new machine types or your workloads fluctuate, a spend-based CUD is almost always the superior choice over a traditional, resource-based one. The slight difference in discount percentage is easily offset by the assurance of near-100% utilization.
- Monitor and Adjust: After purchasing your CUD, keep an eye on your utilization reports. If you find your usage consistently exceeds your commitment, consider purchasing an additional CUD to capture even more savings.
By shifting from rigid, resource-specific commitments to a flexible, spend-based strategy, you can build a more agile and cost-effective cloud environment. This modern approach ensures your cost optimization efforts keep pace with your innovation, allowing you to save money without sacrificing the freedom to choose the best resources for the job.
Source: https://cloud.google.com/blog/products/compute/expanded-coverage-for-compute-flex-cuds/
