The hidden costs of serverless

Key cost drivers in serverless architectures

Cold start mitigation

To avoid cold starts, serverless functions can be kept “warm” through different solutions, but this comes with increased cost. Various strategies can be implemented based on the cloud provider such as:

• using provisioned concurrency
• defining a minimum number of instances
• choosing premium plans

Evaluating the necessity of low latency against the ongoing expense is important for cost-effective architecture decisions.

Long execution times and memory overhead

Serverless pricing is influenced by both execution duration and memory allocation which means processes requiring high memory and running for extended periods can lead to inflated costs. Optimizing execution time and profiling memory usage is essential to determine if a task is suitable for a serverless model or not.

High invocation frequency

Every invocation of a serverless function incurs a charge. Poorly designed event-driven platforms can lead to substantial costs. For instance, if a function is triggered 10 million times daily, even a minimal cost per invocation can accumulate to significant monthly expenses. It’s crucial to track the frequency of invocation of serverless functions to get clear picture about cost consumption to have the chance dealing with the related issues.

Networking costs

Data transfer between services is not free and can significantly impact costs. Applications that frequently interact with other services may result high data transfer charges. Mapping data flows and understanding inter-service communication is crucial for cost management.

When traditional compute solutions outperform

Steady-state workloads

For processes with predictable resource needs running continuously, traditional compute solutions often provide a more economical option. The fixed costs associated with these solutions can be more favorable than the variable costs of serverless solutions.

Compute-heavy tasks

Long-running, compute-intensive tasks are typically cheaper on traditional compute solutions. The pricing model of serverless can become prohibitive for prolonged computations, making traditional options more appealing.

High throughput APIs

When designing APIs, a critical trade-off arises between cost-effectiveness and availability. In such scenarios, traditional compute solutions may offer a more economical approach, ensuring that high availability and performance are achieved without sacrificing budgetary constraints.

Conclusion

The serverless approach offers significant operational benefits, but modeling costs consumption is essential during system design to avoid unexpected costs and create the optimal software architecture without falling into financial pitfalls.