Detecting and Refactoring Operational Smells within the Domain Name System

TL;DR

This paper introduces a method to identify and refactor operational bad smells in DNS configurations using dependency graphs, aiming to improve system robustness and security before deployment.

Contribution

It presents a high-level, abstract approach with a taxonomy and reusable vocabulary for detecting DNS operational smells, enabling proactive diagnostics.

Findings

Dependency graphs effectively identify operational smells.

The method supports proactive detection of configuration issues.

A diagnostic tool prototype is developed for DNS robustness and security.

Abstract

The Domain Name System (DNS) is one of the most important components of the Internet infrastructure. DNS relies on a delegation-based architecture, where resolution of names to their IP addresses requires resolving the names of the servers responsible for those names. The recursive structures of the inter dependencies that exist between name servers associated with each zone are called dependency graphs. System administrators' operational decisions have far reaching effects on the DNSs qualities. They need to be soundly made to create a balance between the availability, security and resilience of the system. We utilize dependency graphs to identify, detect and catalogue operational bad smells. Our method deals with smells on a high-level of abstraction using a consistent taxonomy and reusable vocabulary, defined by a DNS Operational Model. The method will be used to build a diagnostic advisory tool that will detect configuration changes that might decrease the robustness or security posture of domain names before they become into production.