Honeycomb has added a Canvas framework for managing and orchestrating multiple artificial intelligence (AI) agents as they observe and query massive amounts of telemetry data. Morgante Pell, technical lead manager for engineering at Honeycomb, said Canvas is the latest extension to a series of Honeycomb Intelligence initiatives that, for example, provide access to an AI […]
Sketch Coding and the Rise of MCP in DevOps
At swampUP 2025, JFrog’s Yonatan Arbel reflects on his journey inside the company and how developer DNA continues to shape JFrog’s culture. Arbel, who has spent nearly a decade with JFrog, began as a software engineer before moving into leadership and eventually into a developer relations role. But as he emphasized, “once a developer, always […]
JFrog CEO: AI Agents Require Practices Beyond Security, Traceability
NAPA, Calif. — A new persona in software development, artificial intelligence (AI) agents rather than human developers, has made it imperative that foundational platforms incorporate agentic practices alongside security, traceability, and visibility to succeed in the AI era. “Every foundational platform requires a single system of record,” Ben Haim told the crowd. “If you don’t […]
Why APIs Alone Won’t Cut It in the AI Era
Kumar Chivukula, co-founder and CEO of Codeglide.ai (a subsidiary of Upsera), explains why the rise of the Model Context Protocol (MCP) is reshaping how enterprises connect APIs to large language models. For years, APIs have served as the backbone of data access, but they were never designed with AI in mind. They lack memory, context, […]
MCP Emerges as a Catalyst for Modern DevOps Processes
Loreli Cadapan, VP of product at CloudBees, discusses how the Model Context Protocol (MCP) developed by Anthropic will provide the foundation for reinventing DevOps workflows. Cadapan explains that MCP acts as a bridge between large language models and enterprise DevOps environments, functioning as a kind of control plane. It can connect with different CI/CD tools […]
Sentry Adds Tool for Monitoring MCP Servers to APM Platform
Sentry today added an ability to monitor Model Context Protocol (MCP) servers to its application performance monitoring (APM) platform.
AI-Driven Observability: Fast, Context-Rich MCP Servers
Christine Yen—developer-turned-CEO—explains why Honeycomb built an MCP server and why every observability vendor may follow. MCP, short for Model Context Protocol, acts like a concierge for AI agents: It makes a product’s API, telemetry schema and helper tools easily discoverable so large-language models can ask precise questions instead of guessing. Yen sees it as table […]
Context on Tap: How MCP Servers Bridge AI Agents and DevOps Pipelines
Large language models can draft code or move artifacts, but without situational awareness they still trip over the basics. Cloudsmith CEO Glenn Weinstein tells Mike Vizard why a new piece of plumbing—the Model Context Protocol (MCP) server—is quickly becoming table stakes. Think of MCP as a receptionist for AI agents: it answers questions like “Which […]
Coralogix MCP Server Offers Observability View Into AI Agents
Full-stack observability platform company Coralogix has detailed the launch of its new Model Context Protocol Server technology. The product is designed to allow third-party AI agents to connect directly to Coralogix’s observability data services to provide a deeper view into the new fabric of agentic AI connections. Breaking down the observability viewfinder on offer here, […]
AWS Extends MCP Support in Amazon Q Developer to Multiple IDEs
Amazon Web Services (AWS) has added support for the Model Context Protocol (MCP) with the Visual Studio Code and JetBrains plugins that are provided for Amazon Q Developer, a set of artificial intelligence (AI) agents that automate a range of software development tasks.