Dynatrace observability is now a Kiro power
The Kiro power for Dynatrace integrates live observability data, root cause analysis, and remediation suggestions directly into the Kiro AI-powered IDE. This integration allows dev…
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From reactive to proactive: How NAIC embedded AI‑powered observability directly into the IDE
By integrating Dynatrace observability data directly into AWS’s Kiro AI-powered IDE, NAIC has eliminated the productivity loss caused by context switching between development and m…
Evaluate LLM and agent quality in Dynatrace AI Observability with dt-evals
`dt-evals` is an open-source CLI tool designed to evaluate the quality and safety of LLMs and agents by analyzing real GenAI traces using a "LLM-as-a-judge" approach. By integratin…
Beyond correlation to autonomous action: Why “good enough” observability fails in the age of agentic AI
The rise of autonomous AI agents requires a shift from traditional, probabilistic observability—which relies on human-centric correlations—to a deterministic, context-driven archit…
Dynatrace Managed release notes version 1.340
Dynatrace Managed version 1.340 introduces redesigned Network and Disk interface pages for enhanced infrastructure observability, along with configurable log retention and storage …
Port and Dynatrace: One-prompt incident triage with the Dynatrace MCP Server
The new Dynatrace MCP Server integration enables Port AI to correlate live production data from Dynatrace with signals from GitHub, Slack, and the Port service catalog. This allows…
What’s new in Dynatrace SaaS version 1.340
The Dynatrace SaaS 1.340 release introduces advanced Cost Intelligence tools designed to help users proactively understand, predict, and optimize their usage costs through actionab…
OneAgent release notes version 1.339
Dynatrace OneAgent version 1.339 introduces significant enhancements to AI observability, specifically adding automatic instrumentation for Python GenAI frameworks such as OpenAI, …
The silent network killer: Preventing Azure SNAT exhaustion with Dynatrace
SNAT exhaustion in Azure is a networking failure that often masquerades as an application bug, causing intermittent service timeouts that are difficult to diagnose. Dynatrace’s Azu…
OpenTelemetry graduates: A milestone for the observability Open Source community
OpenTelemetry has officially graduated from the Cloud Native Computing Foundation (CNCF), establishing itself as a stable, production-ready standard for observability. This milesto…
AI agents are redefining software development—but they’re flying blind without observability
The software development landscape is shifting into a bimodal era where traditional human-led teams coexist with emerging, AI-agent-led operations. Because AI agents lack visibilit…
Dynatrace MCP Server for Atlassian Rovo: Investigate production problems without leaving Jira or JSM
The Dynatrace MCP Server for Atlassian Rovo enables developers and on-call engineers to investigate production issues directly within Jira and JSM using plain language via an AI ag…