Operations | Monitoring | ITSM | DevOps | Cloud

Graylog MCP Integration: Real-Time LLM Access to Your Data

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.

Introducing the Splunk Technology Add on for Ollama Illuminating Shadow AI Deployments

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.

Beyond Models: JFrog AI Catalog Evolves to Detect Shadow AI and Govern MCPs

When we first introduced the JFrog AI Catalog, it was our mission to provide the industry with a single system of record for governing the complex landscape of internal, open-source, and external commercial AI models. This foundational step was critical for enterprises to move from uncontrolled innovation to delivering AI with trust and confidence. However, the AI landscape is ever-evolving. The challenge for today’s enterprise is already evolving beyond simply managing a library of known models.

Securing Vibe Coding: JFrog Introduces AI-Generated Code Validation

A fundamental shift in software development is already here. Gartner predicts that by 2028, 75% of enterprise software engineers will use AI code assistants – a massive leap from less than 10% in early 2023. While this AI-driven speed creates a competitive advantage, it also opens a dangerous new front in the battle for software supply chain security.

ignio AI Agent for IT Event Management | AI Agent for alert noise reduction

Discover how ignio’s AI-powered agents are transforming IT event and alert management by combining Agentic AI, AI/ML algorithms and automation. In this video, we introduce ignio AI Agent for IT Event Management — a purpose-built, autonomous agent designed to reduce alert noise, group related alerts and predict future events. Whether you’re managing a large-scale enterprise infrastructure, cloud-native environment, or hybrid IT setup, this AI agent empowers your SRE and IT operations (ITOps) teams with real-time observability, automated alert correlation and suppresion, and predictive intelligence What You’ll Learn in This Video.

Top 8 AI Editing Software That Can Change a Person's Voice in 2025

Having worked extensively in audio production and voice-based media, I evaluate every voice changer with a professional, meticulous testing process. I focus on realism, interface usability, and editing precision. Over the years, I've tested most major desktop voice editors, examining how accurately they reproduce natural tones and avoid robotic or distorted outputs. Only a few programs truly balance advanced functionality with user-friendly controls.

Our Engineering in the Age of AI: 2026 Benchmark Report finds AI is making engineering faster, but not necessarily better

Everyone's talking about how AI is transforming software development. Teams are shipping more code, deploying more frequently, and getting features to market faster than they could a year ago. The productivity gains are real. But we kept hearing a different story from engineering leaders. Yes, velocity is up. But incidents are climbing, resolution times are getting longer, and code review processes are struggling to keep up.

Conquer Complexity, Accelerate Resolution with the AI Troubleshooting Agent in Splunk Observability Cloud

The digital landscape has transformed dramatically, and with it, the demands on our systems have grown exponentially. Traditional monitoring tools struggle to provide sufficient insight into complex, distributed, cloud-native environments. Observability is the answer, moving beyond merely knowing "what" is happening to understanding "why" it's happening, and its impact on user experience and business outcomes.