Individual skill
apify-cost-tuning
Optimize Apify platform costs through memory tuning, compute unit management, and proxy budgeting. Use when analyzing Apify billing, reducing Actor run costs, or implementing usage monitoring and budget alerts. Trigger with "apify cost", "apify billing", "reduce apify costs", "apify pricing", "apify expensive", "apify budget", "compute units".
skills/.curated/apify-cost-tuning/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Last checked
- Nov 12, 2026
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- Repository last updated
- Nov 12, 2026
- License
- MIT
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
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- anthropic Repository topic
- claude-code-plugins Repository topic
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- saas Declared skill tag
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- automation Declared skill tag
- apify Declared skill tag
- engineering Derived category
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SKILL.mdcore · 5,684 bytesreferences/examples.mddoc · 1,984 bytesreferences/implementation.mddoc · 7,414 bytesreferences/pricing-model.mddoc · 1,468 bytes
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# Apify Cost Tuning
## Overview
Apify charges on three axes: compute units (CU), proxy traffic (GB), and storage.
One CU = 1 GB of memory running for 1 hour, so cost scales with both memory
allocation and run duration. This skill walks the investigate → tune → guard loop
that finds where spend is going, cuts it at the biggest lever (memory), and installs
guardrails so it stays down.
Full pricing tables (plan CU prices, proxy rates, storage rules) live in
[pricing-model.md](references/pricing-model.md).
## Prerequisites
