Understanding Google Cloud Platform Pricing
As a GDG Community Leader, I’ve often been asked about the intricacies of Google Cloud Platform (GCP) pricing. Navigating through the various pricing models can be a bit overwhelming, but with a clear understanding, you can optimize costs effectively. Let’s dive into the different pricing points with some examples to make things clearer.
Pricing Overview
GCP pricing is based on the resources you consume, which include compute, storage, and networking. Costs can vary depending on the type of services you use, the region where your resources are located, and how you use them.
Free Trial and Free Tier
Free Trial:
New GCP users receive $300 in free credits to use over 90 days. This allows you to experiment with most GCP services without incurring any costs.
Free Tier:
Certain GCP services offer free usage limits every month. For example:
Compute Engine: 1 f1-micro VM instance per month in specific regions.
Cloud Storage: 5 GB of regional storage.
BigQuery: 1 TB of queries per month.
On Demand
This is the pay-as-you-go model, where you only pay for the resources you use without any long-term commitments.
Example:
If you run an n1-standard-1 VM in the us-central1 region for 10 hours at an hourly rate of $0.0475, the cost would be:
10 hours * $0.0475/hour = $0.475
Committed Use Discounts
By committing to use certain resources for 1 or 3 years, you can save significantly compared to on-demand pricing. This requires an upfront commitment.
Example:
If the on-demand cost for an n1-standard-1 VM is $0.0475 per hour, a 1-year committed use discount might reduce it to $0.033 per hour.
Annual cost: 8760 hours * $0.033/hour = $288.08 (compared to $415.50 on-demand).
Sustained Use Discounts – I love it!
These discounts are automatically applied when you use certain resources consistently for a significant portion of the month. The more you use, the higher the discount.
Example:
If you run a VM for more than 25% of the month, GCP will automatically apply a discount to your usage for the entire month. The discount increases as your usage approaches 100%.
Flat Rate Pricing
For services like BigQuery, you can opt for flat-rate pricing, which offers predictable pricing by charging a fixed monthly fee regardless of actual usage.
Example:
BigQuery’s flat-rate pricing option allows you to pay a fixed fee (e.g., $10,000 per month) for a dedicated slot of processing capacity, making it ideal for organizations with high and predictable query loads.
Sole Tenant Node Pricing
This model is ideal for organizations that require dedicated physical servers due to regulatory, compliance, or performance needs. You pay for the exclusive use of a physical server, which can run multiple virtual machines.
Example:
Suppose a sole tenant node costs $1,000 per month. You can run multiple VMs on this node, and the total cost remains $1,000, providing dedicated hardware and isolation for your workloads.
Banking Example with Sole Tenant Nodes
Let’s say you’re a bank that needs to run sensitive financial applications requiring strict compliance and data isolation. By using sole tenant nodes, you ensure that your data and applications run on dedicated hardware without sharing resources with other customers. This isolation helps meet regulatory requirements and enhances security.
Example:
If your bank runs several critical applications on a sole tenant node costing $2,000 per month, you can ensure these applications are isolated, reducing the risk of data breaches. Additionally, you can run multiple virtual machines on this dedicated node, optimizing the use of the physical hardware while maintaining compliance.
For more detailed calculations and to stay updated on any pricing changes, I highly recommend using the GCP pricing calculator. It’s a valuable tool to estimate costs based on your specific usage and requirements, and prices can change frequently, so it’s good to check it regularly.
As you explore GCP, understanding these pricing models can help you make informed decisions, optimize costs, and leverage the full potential of Google Cloud’s services.
Happy Clouding,
Kemal Cholovich
