Is It Worth Speeding It Up (Throughput)?

โš ๏ธ This is an experimental tool for thought-provoking educational purposes only. Not financial or architectural advice! No warranty of correctness or consequences. Use at your own risk.

๐Ÿ’ฐ Cost โš–๏ธ Balanced โšก Throughput
System Parameters
Monetary Analysis
Results update automatically as you adjust parameters

Calculation Breakdown

๐Ÿ“Š Analysis & Mathematical Foundation

๐Ÿงฎ Mathematical Foundation
๐Ÿ“ View Mathematical Formulas

The calculations below form the mathematical foundation for the optimization decision above.

Core Calculations

Total Requests Over Time Horizon:

Total Requests = Rate (req/hr) ร— 24 (hr/day) ร— 365 (days/yr) ร— Time Horizon (years)

where r = requests per hour, T = time horizon in years

Time Saved Per Request:

Time Saved = Current Duration ร— (Speed Gain % รท 100)

where d = duration per request (hours), g = speed gain (%)

Total Time Saved:

Total Time Saved = Time Saved Per Request ร— Total Requests

Total Cost (Time-Based):

Total Cost = Implementation Hours + (Maintenance Hours/Year ร— Time Horizon)

where I = implementation hours, M = maintenance hours/year

Financial Analysis

Compute Cost Savings:

Total Cost (Money):

where `R_("dev/hr")` = developer hourly rate

Net Benefit (Money):

Return on Investment:

ROI = (Net Benefit รท Total Cost) ร— 100%

Break-Even Time:

Time (in years) until savings offset costs

๐Ÿ”„ Decision Influence Diagram
๐Ÿ“ˆ View Factor Influence Map

This diagram shows how all input parameters flow through calculations to produce the final decision. Arrows show directional influence: increases (+) or decreases (-). The Optimization Preference slider controls weighting between cost-focused and throughput-focused metrics.

graph TD %% === INPUT PARAMETERS (Blue) === RR[Request Rate] RD[Request Duration] SG[Speed Gain %] TH[Time Horizon] IT[Implementation Time] MT[Maintenance Time] CC[Compute Cost/Hour] DR[Developer Hourly Rate] OP["`โš–๏ธ Optimization Preference Slider`"] %% === THROUGHPUT PATH (Green - benefits from optimization) === RR rre@==>|"increases (+)"| TTS[Total Time Saved] rre@{ animate: true } RD rde@==>|"increases (+)"| TTS rde@{ animate: true } SG sge@==>|"increases (+)"| TTS sge@{ animate: true } TH the@==>|"increases (+)"| TTS the@{ animate: true } TTS tts@==>|"increases (+)"| NB_T["`Net Benefit Time-based`"] tts@{ animate: true } TTS tts2@==>|"increases (+)"| ROI_T["`ROI % Time-based`"] tts2@{ animate: true } TTS ttsbe@-->|"decreases (-)"| BE_T["`Break-even Time-based`"] ttsbe@{ animate: true } %% === COST PATH (Red - costs of optimization) === IT ite@==>|"increases (+)"| TC_T["`Total Cost Time-based`"] ite@{ animate: true } MT mte@==>|"increases (+)"| TC_T mte@{ animate: true } TH the2@==>|"increases (+)"| TC_T the2@{ animate: true } TC_T tcnbt@-->|"decreases (-)"| NB_T tcnbt@{ animate: true } TC_T tcroit@-->|"decreases (-)"| ROI_T tcroit@{ animate: true } TC_T tc_t@==>|"increases (+)"| BE_T tc_t@{ animate: true } %% === MONETARY PATH (Purple - financial impact) === TTS tts3@==>|"increases (+)"| CCS["`Compute Cost Savings`"] tts3@{ animate: true } CC cc@==>|"increases (+)"| CCS cc@{ animate: true } IT ite2@==>|"increases (+)"| TC_M["`Total Cost Money-based`"] ite2@{ animate: true } MT mte2@==>|"increases (+)"| TC_M mte2@{ animate: true } DR dre@==>|"increases (+)"| TC_M dre@{ animate: true } TH the3@==>|"increases (+)"| TC_M the3@{ animate: true } CCS ccs@==>|"increases (+)"| NB_M["`Net Benefit Money-based`"] ccs@{ animate: true } TC_M tcnbm@-->|"decreases (-)"| NB_M tcnbm@{ animate: true } NB_M nbme@==>|"increases (+)"| ROI_M["`ROI % Money-based`"] nbme@{ animate: true } TC_M tcroim@-->|"decreases (-)"| ROI_M tcroim@{ animate: true } NB_M nbmbem@-->|"decreases (-)"| BE_M["`Break-even Money-based`"] nbmbem@{ animate: true } TC_M tc_m@==>|"increases (+)"| BE_M tc_m@{ animate: true } %% === DECISION LOGIC (Yellow - weighted by preference) === NB_T -->|"`weighted by throughput %`"| DC[DecisionConfidence] ROI_T -->|"`weighted by throughput %`"| DC BE_T -->|"`weighted by throughput %`"| DC NB_M -->|"`weighted by cost %`"| DC ROI_M -->|"`weighted by cost %`"| DC BE_M -->|"`weighted by cost %`"| DC SG -->|"`small fixed weight`"| DC OP -->|"`determines metric weights`"| DC DC -->|"`High confidence โ†’ YES Medium confidence โ†’ MAYBE Low confidence โ†’ NO`"| FD[๐Ÿ“Š Recommendation] %% === STYLING === classDef inputParam fill:#e1f5fe,stroke:#01579b,stroke-width:2px,color:#000 classDef throughput fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px,color:#000 classDef cost fill:#ffebee,stroke:#c62828,stroke-width:2px,color:#000 classDef money fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px,color:#000 classDef decision fill:#fff9c4,stroke:#f57f17,stroke-width:3px,color:#000 classDef finalDecision fill:#ffeb3b,stroke:#f57f17,stroke-width:4px,color:#000 classDef leverage fill:#ff9800,stroke:#e65100,stroke-width:3px,color:#000 class RR,RD,SG,TH,IT,MT,CC,DR inputParam class TTS,NB_T,ROI_T,BE_T throughput class TC_T cost class CCS,NB_M,ROI_M,BE_M,TC_M money class DC decision class FD finalDecision class OP leverage

๐Ÿ“Š Diagram Legend

  • Blue nodes: Input parameters you control
  • Green nodes: Time/throughput benefits (weighted more when slider โ†’ Throughput)
  • Red nodes: Time costs of implementing optimization
  • Purple nodes: Financial metrics (weighted more when slider โ†’ Cost)
  • Orange node: Optimization Preference slider - controls metric weighting
  • Yellow node: Decision confidence based on weighted scoring

โš–๏ธ How the Preference Slider Works

  • ๐Ÿ’ฐ Cost-focused (0-33): Prioritizes financial ROI, money-based metrics get 100% weight, time-based get 0%
  • โš–๏ธ Balanced (34-66): Considers both financial and throughput benefits equally, 50/50 weighting
  • โšก Throughput-focused (67-100): Prioritizes speed improvements, time-based metrics get 100% weight, money-based get 0%
  • Decision threshold: Confidence โ‰ฅ60% = YES, 40-60% = MAYBE, <40% = NO

๐ŸŽฏ Key Insights

  • Compounding effect: Higher request rate + longer time horizon = exponential benefit growth
  • Break-even dynamics: Lower costs and higher benefits both reduce break-even time (faster payback)
  • Speed gain impact: Affects both direct time savings AND compute cost savings
  • Trade-off clarity: Use the slider to see how your priorities affect the recommendation
๐Ÿ“Š

Live Results

Adjust parameters on the left to see instant calculations