The Kubernetes Dashboard served its purpose well in the early days of Kubernetes adoption. It provided a simple, browser-based interface for viewing cluster resources without needing to master kubectl commands. But as Kubernetes...
Datadog recently announced that its LLM Observability platform now provides automatic instrumentation for applications built with Google's Agent Development Kit (ADK), offering deeper visibility into the behavior, performance, cost, and safety of AI-driven agentic systems. The integration, highlighted on the Google Cloud Blog, aims to make it easier for developers and SRE teams to monitor and troubleshoot complex multi-step AI agent workflows without extensive manual setup or custom instrumentation.
Good morning, programs! Today I'm sharing yet another example of Chrome's on-device AI features, this time to demonstrate a "Bluesky Sentiment Dashboard". In other words, a tool that lets you enter terms and then get a report on the average sentiment for posts using that word. I actually did this before (and yes, I forgot until about a minute ago) last year using Transformers.js: Building a Bluesky AI Sentiment Analysis Dashboard.
Support for distributed systems. Check how well the tool handles microservices, serverless, and Kubernetes. Can you follow a request across services, queues, and third-party APIs? Does it understand pods, nodes, clusters, and autoscaling events, or does it treat everything like a static host? Correlation across metrics, logs, and traces. In an incident, you shouldn't be copying IDs between tools. Look for the ability to pivot directly from a slow trace to relevant logs,
