Cost Framework: Serverless vs. Continuously Running Docker Apps

This framework provides a structured approach to evaluate the costs of serverless applications (e.g., Google Cloud Run) compared to continuously running Docker applications. The analysis incorporates key cost factors for each model.

1. Serverless Cost Breakdown

Serverless platforms charge based on usage, including compute time, memory allocation, and request count.

Cost Formula:

Total?Cost=(Request?Count×Execution?Time?per?Request)×Cost?per?GB-second+Additional?Costs\text{Total Cost} = (\text{Request Count} \times \text{Execution Time per Request}) \times \text{Cost per GB-second} + \text{Additional Costs}Total?Cost=(Request?Count×Execution?Time?per?Request)×Cost?per?GB-second+Additional?Costs

• Request Count: Number of requests handled by the serverless app.
• Execution Time per Request: Average time (in seconds) for each request.
• Cost per GB-second: Price per second of computation for 1 GB of memory (e.g., $0.0000166667 for Google Cloud Run).
• Memory Allocation: Memory allocated for each instance (e.g., 128 MB = 0.125 GB).
• Additional Costs: Costs for networking (data egress) or custom features.

Example:

For 1 million requests per month, each taking 30 ms with 128 MB memory:

Total?Compute?Time=1,000,000×0.03?seconds=30,000?seconds?(8.33?hours).\text{Total Compute Time} = 1,000,000 \times 0.03 \, \text{seconds} = 30,000 \, \text{seconds (8.33 hours)}.Total?Compute?Time=1,000,000×0.03seconds=30,000seconds?(8.33?hours).Cost=0.125?GB×30,000?seconds×0.0000166667?USD≈USD?0.64/month.\text{Cost} = 0.125 \, \text{GB} \times 30,000 \, \text{seconds} \times 0.0000166667 \, \text{USD} \approx \text{USD 0.64/month}.Cost=0.125GB×30,000seconds×0.0000166667USD≈USD?0.64/month.

2. Docker Cost Breakdown

Continuously running Docker containers incur fixed costs based on the infrastructure they run on, such as virtual machines or cloud instances.

Cost Formula:

Total?Cost=(Instance?Cost?per?Hour×Uptime?Hours)+Additional?Costs\text{Total Cost} = (\text{Instance Cost per Hour} \times \text{Uptime Hours}) + \text{Additional Costs}Total?Cost=(Instance?Cost?per?Hour×Uptime?Hours)+Additional?Costs

• Instance Cost per Hour: Pricing for the virtual machine or cloud instance hosting the Docker container.
• Uptime Hours: Total hours the instance runs per month.
• Additional Costs: Expenses for storage, backups, or networking.

Example:

For a small VM with 2 vCPUs and 4 GB RAM at $0.040/hour, running 24/7:

Total?Uptime=24×30?hours=720?hours.\text{Total Uptime} = 24 \times 30 \, \text{hours} = 720 \, \text{hours}.Total?Uptime=24×30hours=720hours.Cost=720?hours×0.040?USD/hour=USD?28.80/month.\text{Cost} = 720 \, \text{hours} \times 0.040 \, \text{USD/hour} = \text{USD 28.80/month}.Cost=720hours×0.040USD/hour=USD?28.80/month.

3. Comparison Summary

4. Framework Implementation Steps

1. Define Workload:
2. Calculate Serverless Costs:
3. Calculate Docker Costs:
4. Consider Overheads:
5. Evaluate Trade-offs:

This cost framework ensures an informed decision tailored to workload characteristics and financial constraints. Let me know if you need help applying this to a specific use case!