Guardians of Trust: Navigating Data Security in AIOps through Vendor Partnerships
This work tackles data protection issues for organizations using AIOps vendors, but it is incremental as it focuses on reviewing existing practices without introducing new methods.
The paper addresses data security concerns in AIOps by analyzing vendor-provided security features and best practices to protect sensitive information like PII and confidential data.
Artificial Intelligence for IT Operations (AIOps) is a rapidly growing field that applies artificial intelligence and machine learning to automate and optimize IT operations. AIOps vendors provide services that ingest end-to-end logs, traces, and metrics to offer a full stack observability of IT systems. However, these data sources may contain sensitive information such as internal IP addresses, hostnames, HTTP headers, SQLs, method/argument return values, URLs, personal identifiable information (PII), or confidential business data. Therefore, data security is a crucial concern when working with AIOps vendors. In this article, we will discuss the security features offered by different vendors and how we can adopt best practices to ensure data protection and privacy.