Mastering Cloud Run costs: The 75% rule for choosing a billing model

Cloud Run Billing and Cost Estimation

Key Concepts:

• Cloud Run: A fully managed compute platform that enables you to run stateless containers invocable via HTTP requests.
• Request-based Billing: Paying only for the CPU and memory consumed during request processing.
• Instance-based Billing: Paying for the entire lifetime of a Cloud Run instance, regardless of request activity.
• Free Tier: A monthly allowance of compute time offered by Google Cloud for both billing models.
• Scaling to Zero: Cloud Run’s ability to automatically scale down to zero instances when no requests are being processed.
• OpenTelemetry: An open-source observability framework used for monitoring and tracing applications.

Cloud Run Billing Models: A Detailed Comparison

Mitchell, an Engineering Manager at Google Cloud Run, explains that understanding Cloud Run’s billing models is crucial for cost optimization. There are two primary models: request-based and instance-based.

The default billing model is request-based. Users are charged only for the CPU and memory allocated while a request is being processed. Crucially, there is no charge during the time between requests, as Cloud Run throttles down CPU usage. This, combined with its ability to scale to zero, makes it particularly cost-effective for systems with low or intermittent traffic. A free tier of approximately 50 hours per month (with the default instance size) further reduces costs for low-traffic applications. An example is given: a service receiving one request per day, taking 5 seconds to process, would likely fall within the free tier even with 24/7 availability.

However, instance-based billing offers an alternative. With this model, users pay for the entire lifespan of the Cloud Run instance, even when idle. Mitchell outlines two scenarios where this model might be preferable:

1. Post-Request Processing: When code requires completing tasks after responding to a user (e.g., PDF rendering).
2. Background Processes: When background agents, like OpenTelemetry for monitoring, need to run continuously.

Importantly, instance-based billing offers a lower rate for CPU and memory. Mitchell provides a rule of thumb: switch to instance-based billing if your service is processing requests at least 75% of the time, and idle for 25% or less. The Cloud Console will also indicate if switching would result in cost savings for a running service. This model also has a free tier, offering approximately 66 hours per month for the default instance type.

Real-World Application & Data Points

A case study involving a German bank is cited, where switching to Cloud Run (leveraging its scaling and pay-per-use model) resulted in a 90% reduction in system costs. This highlights the potential for significant savings, particularly when compared to traditional virtual machine deployments requiring always-on instances for redundancy.

Estimating Cloud Run Costs: The Google Cloud Pricing Calculator

To estimate the cost of a new system utilizing Cloud Run, Mitchell recommends using the Google Cloud Pricing Calculator. The calculator allows users to specify:

• Region: (e.g., US Central 1)
• Billing Model: (Request-based or Instance-based)
• Usage Estimates: (e.g., 10 million requests per month, traffic patterns with peaks and troughs)

Using example values (10 million requests/month, default request-based billing), the calculator estimated a cost of approximately $19 per month. Switching to instance-based billing in this example resulted in a slightly higher cost, demonstrating that the optimal model depends on specific traffic patterns and resource utilization.

Step-by-Step Cost Optimization Process

1. Understand Billing Models: Familiarize yourself with the nuances of request-based and instance-based billing.
2. Utilize the Pricing Calculator: Accurately estimate costs based on anticipated usage.
3. Monitor Running Services: Leverage the Cloud Console to identify potential savings by switching billing models.

Key Argument & Perspective

The central argument presented is that Cloud Run offers significant cost optimization potential, but realizing these savings requires a clear understanding of its billing models and careful estimation of resource usage. The perspective is that Cloud Run is not simply a cheaper alternative, but a fundamentally different compute paradigm that rewards efficient resource utilization and scalability.

Notable Quote

“If your service is processing requests at least 75% of the time and idle 25% of the time or less, instance-based billing will save you money.” – Mitchell, Engineering Manager, Cloud Run.

Synthesis/Conclusion

Cloud Run’s flexible billing models and scaling capabilities provide a powerful platform for cost-effective application deployment. By understanding the trade-offs between request-based and instance-based billing, utilizing the Google Cloud Pricing Calculator, and continuously monitoring running services, developers can maximize their cloud investment and achieve significant cost savings. The key takeaway is that proactive cost management is essential to fully leverage the benefits of Cloud Run.