THE INTERSECTION OF SECURITY AND RELIABILITY IN PLATFORM ENGINEERING

Abstract

As platform engineering evolves to manage increasingly complex cloud-native infrastructures and distributed systems, the intersection of security and reliability has become critical. This paper investigates the symbiotic relationship between security practices and platform reliability, demonstrating that security incidents like Distributed Denial of Service (DDoS) attacks, data breaches, and ransomware can drastically affect reliability metrics such as uptime, Mean Time to Recovery (MTTR), and Mean Time Between Failures (MTBF). Through an analysis of industry-standard tools and frameworks like Intrusion Detection Systems (IDS), automated vulnerability management, and secure configuration management, we show how security mechanisms enhance platform stability and operational continuity. Additionally, we examine the role of machine learning (ML) and artificial intelligence (AI) in fortifying these systems, highlighting how AI-driven IDS improves detection accuracy and reduces service interruptions. The paper also discusses the impact of security events on Service Level Agreements (SLAs), particularly in industries with stringent reliability targets. This work presents a unified approach for platform engineers to balance security and reliability, ensuring robust, resilient platforms that meet both operational and cybersecurity requirements.