Whether you’re a “startup.ai” or an “enterprise.com”, operating cloud infrastructure on Google Cloud Platform (GCP) offers compelling advantages, especially in data analytics, machine learning, and Kubernetes-native operations.
However, compared to first-mover AWS and enterprise-first Azure, GCP presents unique challenges. While some are a mere result of GCP being younger, others stem from a different logic applied to some GCP services (like IAM and networking) and savings mechanisms, like commitments.
Since 2019, Spot Eco has been helping thousands of enterprises to maximize their commitment savings and keep their portfolio flexible for change. Through the years, GCP customers have been a brave minority. But today, as the platform matures into the ultimate cloud-native choice, we foresee a surge in GCP adoption. On this ground, we are happy to announce Eco’s new GCP dashboard, and a widened list of supported GCP services.
Google Cloud commitments: One heck of a hard nut
A particularly unique challenge for GCP users lies in managing Committed Use Discounts (CUDs) and Sustained Use Discounts (SUDs). While these GCP-specific discount plans can lead to significant savings, they also introduce complexities that are not present in AWS or Azure commitments, including:
- Rigid resource binding
GCP CUDs are tightly bound to specific instance families, regions, and resource types (e.g., vCPU and memory for N2 instances in a specific region). If your workload shifts or your team adopts new machine types (e.g., from N1 to N2), the CUDs become partially or fully unusable. AWS, by contrast, offers Compute Savings Plans that automatically apply across instance families, operating systems, and even regions, offering much more flexibility. - No convertible or exchangeable commitments
Unlike AWS Convertible Reserved Instances or Azure Reserved Instance Exchanges, GCP offers no official way to modify or cancel commitments mid-term. This lack of flexibility can result in sunk costs, especially for organizations in dynamic environments that frequently change workloads or machine types. - Forecasting and optimization tooling
GCP’s forecasting tools, including its Recommender API, are still behind AWS’s Cost Explorer or Azure’s Cost Management solutions. For organizations with bursty or seasonal workloads, this makes it harder to confidently commit to long-term discounts without risking waste. - SUDs vs CUDs interactions
GCP automatically applies Sustained Use DiscountsSUDs when VM instances run for a significant portion of the month. While helpful for cost control, these discounts can complicate the decision to purchase CUDs, since the savings from CUDs must be evaluated in the context of discounts you would already receive via SUDs. - No resell or marketplace options
Both AWS and Azure do not currently support reselling unused Reserved Instances, but Azure does offer limited refund and exchange policies. GCP offers no such mechanism. Once a CUD is purchased, there is no option to cancel, transfer, or resell it, even if it becomes misaligned with your usage patterns.
Spot Eco for GCP: More savings, less overcommitment
Why do GCP users choose Eco?
Eco overcomes the inherent CUD challenges of GCP users, offering significant advantages over self-management. These advantages help increase actual CUD savings—and give you back the engineering time once invested in managing them:
- Deep knowledge of Google’s FinOps logic and commitment models across compute, data, and application services, ensures the highest possible discounts, with enough wiggle room for your shifting needs.
- Unique, per-user portfolio blend of resource, spend, and flex CUDs keeps ROI high, even when usage patterns change.
- Tiered CUD purchasing and extensions provide flexibility over time in committed spend and resources, while locking the same great discounts for you.
- Regular monitoring of actual CUD utilization allows Eco to add and extend CUDs for increased workload coverage or shift CUDs
What’s new in ECO for GCP?
On the new Eco dashboard, Eco and GCP users can view and analyze the performance of their CUD and SUD portfolio. Key metrics already presented are monetary savings and remaining commitment value by time, region, and GCP service.
Where can I save with Eco for GCP?
Eco helps you with GCP rate optimization, far beyond compute. Some key services managed by Eco include:
- Compute Engine CUDs
- GKE CUDs
- Cloud Run CUDs
- AlloyDB CUDs
- App Engine configurations
Join Eco
Onboarding your Google account is a simple, self-service process, as seen in this video:
Once onboarded, Eco analyzes your current resource usage and composes your unique, distributed blend of CUDs. Once implemented, Eco tracks actual utilization to add, extend, or shift CUDs around your different organizations.
Don’t want to go it alone? Watch the Eco demo or claim your free commitment consultancy here.
