Useful resources: AI Observability & AIOps

GosiaMurawska — Thu, 28 May 2026 08:58:29 GMT

We've put together a list of resources that actually help you get started with AI: courses, tutorials, real-world case studies, and a few things worth bookmarking before they get buried under the next wave of content.;)

📌 Start here: Community fundamentals

What is AI and LLM Observability? — The foundational "what and why" before you touch any tooling — a clear explainer on what AI/LLM observability actually means and why it belongs in your stack.

Agentic AI & Model Context Protocol Explained — A grounded breakdown of the agentic AI shift and what MCP means in practice.

Getting Started with AI Observability — Install the OpenLLMetry SDK, add two lines of code, and your GenAI app is sending telemetry to Dynatrace — the shortest path from zero to LLM observability.

Building GenAI Apps with Open Source — A practical map of the open source AI stack - from frontend (NextJS, Streamlit) to LLMs (Llama, Mistral) - covering what tools fit where when building and observing GenAI applications.

🎓 Course

AIOps & SRE for Beginners — A beginner-friendly course that walks you from zero to understanding anomaly detection, automated workflows, and SRE practices that reduce MTTD, MTTI, MTTA, and MTTR — with platform walkthroughs, not just theory.

🛠️ Dynatrace GitHub

Dynatrace for AI — One command installs a full collection of Skills covering DQL essentials, full-stack observability, dashboards, notebooks, and DQL migration — so your AI agent stops guessing and starts knowing.

Introducing dtctl: Your Dynatrace Platform, One Command Away — A kubectl-inspired CLI that lets you manage workflows, dashboards, SLOs, and 20+ resource types from your terminal. Pairs naturally with dynatrace-for-ai: that repo brings the domain knowledge, dtctl brings the hands on the keyboard.

📖 Documentation & Tutorials

Self-Service AI Observability Tutorial — Hands-on tutorial instrumenting a LangChain + Pinecone + Ollama stack on Kubernetes with OpenTelemetry in basically one line — tracks token usage, latency, and prompt quality, with dashboard and SLO examples included.

AI Remediation with GitHub Copilot — Dynatrace runtime context tells GitHub Copilot which Dependabot alerts are actually exploitable — confirmed ones get an auto-generated fix PR, unconfirmed ones are dismissed with a reason, developers just review and merge.

📰 Blog

Dynatrace AI Agents Begin Working for You on Day One — No setup, no prompt engineering: Dynatrace ready-made agents for developers, SREs, and IT ops are available now, triggered via Workflows or the MCP Server, and this post shows exactly which ones to reach for and why.

AIOps Strategy: Real-World Outcomes — One of the largest US banks cut transaction failures, eliminated 7 monitoring tools, and reduced costs by 45% by putting Dynatrace at the center of their AIOps strategy — real numbers, real outcomes.

🎙️ Podcast

10 Fundamentals to Get Vibe Coding Right — Jeff Blankenburg built a 950k+ baseball card site through pure vibe coding and shares practical lessons on structuring your AI workflow.

Hey, got a resource or a topic that should be on this list? Drop it in the comments - let’s build this together.

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Useful resources: AI Observability & AIOps