Operations | Monitoring | ITSM | DevOps | Cloud

This 5-minute critique pulls back the curtain on where AI is succeeding and where the biggest challenges remain. Experts expose the gap between market hype and reality: the failure to deploy fully autonomous production agents and the missing human-machine interface for non-developers. It’s a challenge to the entire industry.

Graylog V7.0 supports integration with the Model Context Protocol (MCP), which allows large language models (LLMs) to access and interact with Graylog data and workflows in real time. Graylog exposes an MCP-compatible endpoint for LLM clients, such as Claude and LM Studio. MCP integration allows Graylog users to interact with their data through LLMs. With MCP, an LLM can connect directly to Graylog as a remote tool interface, performing queries, retrieving system information, and assisting with common administrative or investigative tasks. This capability may make it possible to.

Without strong visibility and governance, local LLMs risk replicating the fragmented, unsupervised sprawl once seen in shadow IT, complicating security postures and making it difficult for organizations to ensure proper oversight and compliance as these powerful AI tools become embedded in daily workflows. To address this challenge, The Splunk Threat Research Team has released the Splunk Technology Add-on for Ollama that provides comprehensive monitoring and observability capabilities specifically designed for local LLM deployments.