Estimate request cost (ms CPU) and multiply by concurrency to size CPU/RAM

What it means:

• Every request your service handles consumes CPU and memory.
• To properly size your server, you need to estimate how much CPU time each request takes, then consider how many requests you expect to handle concurrently.

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Step-by-step:

1. Estimate request cost

• Measure or estimate how much CPU time a single request consumes, usually in milliseconds (ms).

• Example:

  • A typical request may take 20 ms of CPU to process.

1. Estimate concurrency

• How many requests will your service need to handle at the same time?

• Example:

  • During peak load, you expect 500 concurrent requests.

1. Compute total CPU requirement

[ \text{Total CPU time needed per second} = \text{Request CPU time (ms)} \times \text{Concurrency} ]

• Example: [ 20,ms \times 500 = 10,000,ms,\text{CPU per second} = 10,CPU cores ]
• Why? Because 1 CPU core ≈ 1000 ms CPU per second.

1. Size RAM

• Estimate how much memory each request uses, then multiply by concurrency to get total memory requirement.

Summary:

CPU/RAM sizing = (per-request resource usage) × (expected concurrent requests)

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Use queue length and worker processing time to compute worker count for background jobs

Context:

• Background jobs (async tasks) are usually processed by worker processes.
• To ensure jobs are handled without delays, you need enough workers to handle incoming queue length.

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Step-by-step:

1. Queue length (Q)

• Number of pending jobs in the queue.
• Example: Q = 1000 jobs

1. Worker processing time (T)

• Average time a worker takes to process a single job.
• Example: T = 2 seconds/job

1. Compute worker count (W)

• You want to process all jobs in desired time, or at least keep up with incoming rate.

Formula: [ W = \frac{\text{Queue length} \times \text{Processing time per job}}{\text{Target processing window}} ]

• Example:

  • Queue = 1000 jobs
  • Processing time = 2 s/job
  • Target = process all jobs in 100 s

[ W = \frac{1000 \times 2}{100} = 20,workers ]

• If jobs arrive continuously, also consider arrival rate: [ W \geq \text{Job arrival rate} \times \text{Processing time per job} ]

1. Adjust for concurrency

• Depending on whether workers can process multiple jobs simultaneously (threads, async), adjust worker count accordingly.

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Summary

Concept	Formula / Rule
CPU sizing	CPU cores ≈ (request CPU ms × concurrency) / 1000
RAM sizing	RAM ≈ (per-request memory × concurrency)
Worker count	Workers ≈ (queue length × processing time) / desired processing window or Workers ≥ arrival rate × processing time

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💡 Analogy:

1. CPU sizing:

• Like figuring out how many chefs you need in a kitchen:

  • Each dish takes 5 min
  • 10 people want dishes simultaneously → need enough chefs to cook all without delay

1. Queue + worker sizing:

• Like a line at a bakery:

  • 100 customers waiting
  • Each cashier takes 2 minutes per customer
  • To serve everyone in 20 minutes → need enough cashiers (workers)

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