The OpenTelemetry Collector acts as a translation and routing layer that decouples application instrumentation from specific observability backends. Instead of a single version, it…
The Dynatrace MCP Server bridges the gap between AI coding assistants and live production environments by providing AI agents with direct access to real-time observability data via…
This article provides a step-by-step guide for configuring the OpenTelemetry Astronomy Shop demo application to use Dynatrace as an observability backend. It explains how to deploy…
Standard Kubernetes monitoring often fails to report the "effective" resource value reserved by the scheduler, which can be significantly higher than per-container requests if heav…
This article provides a detailed breakdown of the anatomy of an OpenTelemetry span, explaining its core building blocks such as context, name, kind, and attributes. It illustrates …
Operational technology (OT) is critical for managing the physical infrastructure essential to society, such as power, water, and manufacturing, where system failures can have sever…
This article explains how OpenTelemetry uses traces and spans to provide end-to-end visibility into the journey of requests within complex distributed systems like microservices an…
To transform unreliable AI-generated code into production-ready software, organizations must move beyond simple prompting toward a multi-layered approach involving structured plann…
Koney is an open-source Kubernetes operator that automates cyber deception by deploying "honeytokens," or decoy files, across a cluster to catch attackers during unauthorized acces…
CISA’s new Binding Operational Directive (BOD) 26-04 mandates that U.S. federal agencies transition from using static severity scores to a risk-based vulnerability prioritization m…
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…
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…