Which practice should be avoided to maintain system integrity in decentralized architecture?

Which practice should be avoided to maintain system integrity in decentralized architecture?

• A. Duplication
• B. Documentation
• C. Centralization
• D. Compliance checks

Answer: (A)

In a decentralized architecture, avoiding duplication of data is crucial for system integrity. When multiple services or nodes each maintain their own copy of the same data, updates must be synchronized across many places. This creates opportunities for data to drift apart, leading to inconsistent states, conflicting updates, and harder audits or troubleshooting. Minimizing duplication helps establish a single source of truth, simplifies synchronization, and supports clear conflict resolution, which together keep data accurate and the system reliable. Documentation, while valuable for transparency and governance, does not by itself prevent the integrity problems caused by duplicated data. Centralization contradicts decentralization goals, reducing the benefits of a distributed approach. Compliance checks are important for governance and risk management, but they don’t inherently solve the data consistency issues that duplication introduces.

In a decentralized architecture, avoiding duplication of data is crucial for system integrity. When multiple services or nodes each maintain their own copy of the same data, updates must be synchronized across many places. This creates opportunities for data to drift apart, leading to inconsistent states, conflicting updates, and harder audits or troubleshooting. Minimizing duplication helps establish a single source of truth, simplifies synchronization, and supports clear conflict resolution, which together keep data accurate and the system reliable.

Documentation, while valuable for transparency and governance, does not by itself prevent the integrity problems caused by duplicated data. Centralization contradicts decentralization goals, reducing the benefits of a distributed approach. Compliance checks are important for governance and risk management, but they don’t inherently solve the data consistency issues that duplication introduces.