Building pipelines has become easy. Knowing if they work correctly is now easy, too

Any agent anywhere: How to use Grafana Cloud with Claude, Cursor, and any other AI agent

Learn how any agent—whether it's Grafana Assistant, a coding agent in your IDE, or a tool you’ve built yourself—can interact with Grafana Cloud and use your observability data to find root causes faster.

How we investigated prompt cache misses with Datadog

An investigation of prompt cache misses in internal AI applications by using Datadog Cloud Cost Management and Agent Observability.

What Is OpenTelemetry? A Guide to the OTel Framework

What is OpenTelemetry? See how the OTel framework standardizes traces, metrics, and logs so you can switch backends freely.

Apache Airflow 3.4.0: Task Loops, Dags in Any Language, and AI Agents

Apache Airflow 3.4.0 introduces bounded Task Loops for iterative workflows, Dag authoring beyond Python (TypeScript, Go, Java, and YAML) on the new AIP-85 Dag Importer, and a maturing Common AI provider for running LLM and agent tasks with built-in human approval.

Don't Write Markdown Files for Your Coding Agent. Write Scripts.

If you want agents to do what you want, you need to learn how to box them into deterministic actions.... Tagged with ai, programming, devops, productivity.

Announcing the OpenTelemetry JavaScript SDK 3.0

OpenTelemetry JavaScript has released SDK 3.0 (stable v3.0.0 packages and experimental v0.300.0 packages) and API 1.10.0. Migration guide For a detailed description of breaking changes, see the OpenTelemetry JS SDK 3.x migration guide. What is JS SDK 3.x? JS SDK 3.x encompasses new releases of the @opentelemetry/* JavaScript packages published from the opentelemetry-js repository, except the API and semantic-conventions packages. The package versions for this new major will be >=3.0.0 for the stable and >=0.300.0 for the unstable packages. Details on the full list of packages can be found in the migration guide.

How to Build an Agentic Development Tech Stack

Bối cảnh xây dựng agentic development tech stack đang trở nên quan trọng khi các hệ thống AI tự chủ ngày càng phổ biến. Nguyên nhân kỹ thuật đến từ nhu cầu tích hợp nhiều thành phần như models, orchestration, memory, tools, observability, evaluations, guardrails và testing. Hệ quả là việc thiếu kế hoạch tổng thể dẫn đến hệ thống phức tạp, khó bảo trì và không đảm bảo chất lượng. Điều đáng học là cần có thiết kế hệ thống có cấu trúc, rõ ràng cho từng thành phần để tạo ra nền tảng agent mạnh mẽ và đáng tin cậy.

Bài này giúp bạn thiết kế hệ thống công cụ phát triển agent hiệu quả với các thành phần then chốt như model, orchestration và bảo mật.

What’s new with Grafana variables: less clutter, easier reuse across dashboards, and more

As your dashboards grow, managing Grafana variables can mean more clutter and duplicate work. Learn how section-level and cross-dashboard variables help make controls easier to organize and maintain.