Mitigating the Cost Amplification of Platform Defaults in Lean Cloud Data Deployments Through Configuration Hygiene

Cloud data platforms offer flexibility, but their default configurations are implicitly optimized for enterprise-scale environments, leading to hidden, disproportionate costs for small-scale deployments. This paper introduces the concept of a silent tax, where platform defaults, such as minimum billing durations and over-provisioned column types, disproportionately inflate costs for small business organisations with modest compute budgets, exemplified by a 10 IPU per month scenario. These defaults act as regressive cost drivers, penalizing users unable to amortize inefficiencies. We employ an analytical cost modelling approach using Snowflake and Informatica Intelligent Cloud Services (IICS) as reference platforms. Our findings indicate that fixed-cost components embedded in these defaults can consume approximately 65% of a minimal budget. Key mechanisms include 60-second warehouse billing minimums, schema-driven memory over-allocation, and CI/CD pipeline reconfiguration costs. The study demonstrates that cost waste in minimal deployments is predominantly structural. An optimization pathway focusing on configuration hygiene—including explicit data types, aggressive warehouse tuning, and schema-as-code—can reclaim over 80% of this overhead, aligning with FinOps guidance for small estates. This research addresses a gap in cloud cost governance, empowering small teams to leverage cost intelligence for sustainability, and suggests transparent disclosure of default cost impacts by providers.

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Publication Details

Journal
Transactions on Informatics and Data Science
Published
2025-11-14
DOI
https://doi.org/10.24090/tids.v2i2.14737
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
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article

Mitigating the Cost Amplification of Platform Defaults in Lean Cloud Data Deployments Through Configuration Hygiene

Manuel Díáz
Transactions on Informatics and Data Science
Software System Performance and Reliability
article

Mitigating the Cost Amplification of Platform Defaults in Lean Cloud Data Deployments Through Configuration Hygiene

Manuel Díáz
article en

Abstract

Cloud data platforms offer flexibility, but their default configurations are implicitly optimized for enterprise-scale environments, leading to hidden, disproportionate costs for small-scale deployments. This paper introduces the concept of a silent tax, where platform defaults, such as minimum billing durations and over-provisioned column types, disproportionately inflate costs for small business organisations with modest compute budgets, exemplified by a 10 IPU per month scenario. These defaults act as regressive cost drivers, penalizing users unable to amortize inefficiencies. We employ an analytical cost modelling approach using Snowflake and Informatica Intelligent Cloud Services (IICS) as reference platforms. Our findings indicate that fixed-cost components embedded in these defaults can consume approximately 65% of a minimal budget. Key mechanisms include 60-second warehouse billing minimums, schema-driven memory over-allocation, and CI/CD pipeline reconfiguration costs. The study demonstrates that cost waste in minimal deployments is predominantly structural. An optimization pathway focusing on configuration hygiene—including explicit data types, aggressive warehouse tuning, and schema-as-code—can reclaim over 80% of this overhead, aligning with FinOps guidance for small estates. This research addresses a gap in cloud cost governance, empowering small teams to leverage cost intelligence for sustainability, and suggests transparent disclosure of default cost impacts by providers.

Transactions on Informatics and Data ScienceVol. 2(2)
Ateneo de Naga University (PH)
Openalex Percentile: Top 60%
Software System Performance and Reliability
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