Operations | Monitoring | ITSM | DevOps | Cloud

Your AI agents can now monitor, triage, and respond to cloud outages autonomously. The way enterprises manage cloud infrastructure incidents is changing. AI agents are no longer just chatbots answering questions — they’re becoming first responders in your incident management pipeline. Today, we’re launching the StatusGator MCP Server, giving AI agents direct, structured access to the full power of StatusGator’s cloud status monitoring platform.

The AI-powered documentation search on the Alloy Software docs site has been updated, and it’s noticeably better.

Organizations across industries are accelerating their investments in AI for operations, yet the path to meaningful impact is proving far more complex than early expectations suggested. Analysts at Gartner, Forrester, Deloitte, and McKinsey continue to highlight the same structural barrier. AI cannot produce accurate predictions or safe automation when the operational data feeding it is fragmented, incomplete, or inconsistent.

Since releasing our hosted MCP server last year, we've been thrilled to see customers not just adopt it but build Honeycomb deeply into their agentic development and observability workflows. Users have embraced it, leveraging Honeycomb to stay in conversation with their code and understand how it runs in production.

While AI have usage has been growing steadily for the last several years, the LLM models noticeably improved around the end of 2025. Specifically, they become more viable for software development. We are seeing the results. The feature and product delivery has picked up. One way to visualize this is by looking at the number of pull requests for your organization / software development teams. This chart shows the number of Github pull requests created by a team. Can you spot when AI usage increased?