Dynatrace's Davis AI engine enhances site reliability engineers' (SREs) capabilities by streamlining exploratory and proactive analyses, ultimately saving time and reducing complexity in managing cloud-native environments. By automatically analyzing thousands of signals, Davis identifies anomalies and provides explanations, allowing SREs to understand and address the root causes of unexpected changes without the need for custom dashboards. This capability is particularly beneficial in complex scenarios such as Kubernetes environments, where introducing technologies like service meshes can lead to issues like "zombie" pods, which consume resources unnecessarily. Davis enables efficient diagnosis and remediation of such issues by providing detailed insights and suggesting best practices, such as using Kubernetes' activeDeadlineSeconds spec, concurrencyPolicy, and namespace quotas, to prevent resource exhaustion. The new exploratory analysis feature, part of Dynatrace SaaS version 1.254, is set to be released in November and will extend its utility beyond Kubernetes to other domain-specific analysis pages, promising to enhance the operational efficiency and innovation potential for SRE and DevOps teams.