Dynatrace has introduced the QuickStart app and dtwiz setup wizard to provide a streamlined, zero-config onboarding experience for new users and free trial participants. These tool…
This article explores how Dynatrace Smartscape on Grail uses a traversable, typed graph to model Kubernetes environments, providing SREs with a unified data model for observability…
The launch of IBM z17 introduces advanced AI and automation capabilities to mission-critical enterprise workloads, but this increased complexity creates new observability challenge…
Dynatrace has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Observability Platforms, marking its 16th time receiving this recognition. The company’s unified platform…
Dynatrace Security Enrichment provides a unified platform to integrate various commercial, open-source, and proprietary threat intelligence sources through standardized HTTP-based …
Dynatrace is pursuing FedRAMP Class D (High) certification to expand upon its existing FedRAMP Moderate authorization, aiming to support federal agencies managing highly sensitive,…
This article outlines recent Dynatrace updates, highlighting a new unified topology view in Smartscape and enhanced AI observability through tools like `dt-evals` for LLM evaluatio…
To navigate the overwhelming hype surrounding new AI coding tools, developers should focus on identifying creators who demonstrate real value through public work and shared impleme…
Dynatrace provides full-stack observability for complex agentic AI systems by monitoring everything from GPU infrastructure and model performance to token consumption. Through its …
Dynatrace has enhanced its Kubernetes Security Posture Management (KSPM) by embedding vulnerabilities, threats, and misconfigurations directly into its existing Kubernetes app to e…
Dynatrace has expanded its HIPAA-compliant observability services to include Google Cloud Platform (GCP), allowing healthcare organizations to standardize security and monitoring a…
This article explores how LLM evaluations provide a systematic framework for measuring the quality, accuracy, and safety of probabilistic AI models as they move from experimentatio…