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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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In the fast-paced world of cloud computing, serverless technologies have revolutionized how businesses deploy and scale applications. But as more organizations adopt function-as-a-service (FaaS) platforms, a critical question emerges: should your cloud provider charge you for cold starts? This often-overlooked aspect of serverless pricing can significantly impact both your application performance and your bottom line.
What Are Cold Starts and Why Do They Matter?
Cold starts occur when a serverless function is invoked after being idle, requiring the cloud provider to provision new resources, load the runtime, and initialize your code. This initialization process introduces latency—sometimes substantial—before your function begins executing.
For business-critical applications, these delays can:
- Create poor user experiences
- Impact conversion rates
- Violate service level agreements (SLAs)
- Introduce unpredictability in system performance
According to a study by the University of California, Berkeley, cold starts can introduce latency ranging from hundreds of milliseconds to several seconds depending on the runtime, function complexity, and cloud provider.
The Current State of Cold Start Pricing
Today's major cloud function platforms handle cold start costs differently:
AWS Lambda: Doesn't explicitly charge for cold starts, but you pay for the execution time, which includes initialization.
Google Cloud Functions: Charges for the time your function spends during initialization as part of execution time.
Azure Functions: Similar to AWS, charges for execution time including initialization.
IBM Cloud Functions: Charges based on execution time, including cold start initialization.
This seemingly subtle distinction has profound implications for your cloud costs, especially for functions with heavy dependencies or complex initialization requirements.
The Hidden Economics of Cold Starts
When evaluating serverless pricing models, many executives focus solely on per-invocation and compute time costs. This approach misses the sometimes significant economic impact of cold starts.
Consider an enterprise application with:
- 100 different functions
- Each experiencing 10 cold starts per hour
- An average cold start duration of 2 seconds
- A pricing model of $0.0000166 per GB-second
While these numbers might seem inconsequential, they accumulate to approximately $290 per month just for cold starts. For larger organizations with thousands of functions, this quickly escalates into significant spending on what is essentially wait time.
The Performance Pricing Paradox
The fundamental question becomes: should you pay for something that delivers no business value?
Cloud providers might argue that cold starts represent real resource consumption—they're provisioning compute resources, loading runtimes, and preparing your function environment. From their perspective, this is a legitimate operational cost.
However, from a customer viewpoint, you're paying for degraded performance. It's similar to being charged for waiting in line at a restaurant—technically, you're occupying space, but you're not receiving the service you came for.
Strategies for Minimizing Cold Start Costs
Whether your provider charges for cold starts or not, implementing these strategies can help reduce their impact:
- Pre-warming: Keep functions warm by scheduling periodic invocations
- Function optimization: Reduce dependency sizes and optimize initialization code
- Provisioned concurrency: Some platforms offer options to keep functions initialized (for an additional cost)
- Runtime selection: Choose lightweight runtimes that initialize quickly
- Code splitting: Separate frequently and infrequently used functions to minimize cold start impact
According to a 2022 report by Datadog, organizations that implemented cold start optimization strategies reduced their serverless costs by an average of 27%.
What to Ask Your Cloud Provider About Function Pricing
When evaluating cloud function platforms, consider these questions regarding their approach to cold starts:
- Does your pricing model include cold start time in billable execution?
- What tools do you provide for monitoring and optimizing cold start performance?
- Do you offer any mechanisms to mitigate cold starts without additional charges?
- How transparent is your billing in separating cold start costs from actual execution?
- Are there volume-based discounts that might offset cold start costs?
The Future of Cold Start Pricing
As serverless computing matures, we're seeing emerging trends in how providers approach cold start pricing:
- Some newer entrants in the market are experimenting with models that don't charge for initialization time
- Advanced pre-warming technologies are being developed to minimize cold starts altogether
- Hybrid models offering both per-request and reserved capacity options provide flexibility
Conclusion: Making Informed Decisions About Serverless Pricing
When evaluating whether your cloud function platform should charge for cold starts, the answer depends on your specific use case, performance requirements, and budget constraints.
For organizations with predictable, high-volume workloads, platforms that charge for cold starts but offer provisioned concurrency might provide better value. For those with sporadic, low-volume functions, prioritizing platforms with fast cold start times—regardless of pricing model—might be more important.
The key is understanding that cold start pricing isn't just a technical detail—it's a strategic consideration that impacts both application performance and cost efficiency. By carefully analyzing your workload patterns and evaluating provider pricing models, you can make choices that align with your business objectives while keeping serverless costs predictable and reasonable.
As you evaluate your serverless strategy, remember that the true cost of a platform extends beyond the basic function pricing—it encompasses the entire performance envelope, including how cold starts affect your bottom line and your user experience.