Operations | Monitoring | ITSM | DevOps | Cloud

How Thundr Uses AI to Create High Quality 1-on-1 Chats

People desire honest, interesting, and personal communication in today's fast-paced digital world. Most of the time, traditional online chat services fail to provide users with the depth and connections they desire. Thundr is different from other companies in that it utilizes cutting-edge AI to enhance discussions for both parties. The program makes every connection more engaging than a random chat service by placing a strong emphasis on personalization and user safety. Integrating these features on the platform enables this improvement.

What is an AI Agent? Understanding the Future of Intelligent Automation

In today's fast-paced digital world, the term AI agent is becoming increasingly common - but what does it really mean? Whether you're a tech enthusiast, a business owner, or just curious about artificial intelligence, understanding AI agents can help you stay ahead of the curve.

The PagerDuty Vision for AI-First Operations

Something fundamental needs to change in the way we run operations. Organizations are deploying AI to optimize everything from coding and deployment to resource planning and incident management. But they’re discovering that managing AI-powered systems requires a completely different operational mindset. AI models hallucinate. Data pipelines degrade silently. Algorithms develop bias without warning.

You built the MCP server. Now track every client, tool, and request with Sentry.

TL;DR - Starting today, you can instrument most server-side JavaScript SDK based MCP servers with one line of instrumentation code within your MCP SDK implementation. Click to Copy Click to Copy With this in place, you’ll be able to see details like protocol usage, client usage, traffic, tool usage, and performance across your MCP implementation.

Sentry MCP server monitoring

We just launched MCP server monitoring in beta. You can instrument most server-side JavaScript SDK based MCP servers with one line of instrumentation code within your MCP SDK implementation using: wrapMcpServerWithSentry(McpServer) See details like protocol usage, client usage, traffic, tool usage, and performance across your MCP implementation so you you can get visibility into all the sharp edges that your MCP server has — who’s using it, how it’s working (or not), and get alerted when things break.

Cortex MCP set up

Learn how to set up the Cortex MCP in under 5 minutes. The MCP integrates directly into your IDE, giving instant access to Cortex data without leaving your coding environment. It reduces context switching by enabling natural questions about services and teams, and streamlines workflows with real-time data from Cortex, Jira, GitHub, and more.

AI in observability at Grafana Labs: Making observability easy and accessible for everyone

Did you know that observability has been around for more than six decades? It all goes back to a Hungarian-American inventor named Rudolf Kálmán who thought about how external outputs could measure the internal state of a machine. Kálmán wrote about monitoring single-input single-output systems, but our demands are very different today. We need to observe monoliths, microservices, clusters, pods, regions, and many more.