Operations | Monitoring | ITSM | DevOps | Cloud

Accelerating AI Agent Development on Google Cloud with JFrog MCP Registry

Developers building agentic AI on Google Cloud have powerful infrastructure at their fingertips: Gemini 3 for reasoning, Google’s Agent Development Kit (ADK) for orchestration, and a rapidly expanding ecosystem of Model Context Protocol (MCP) servers that connect agents to data and tools. So why are so many teams still waiting weeks to ship their first agent to production?

Under the Hood: Engineering JFrog Premium Availability

In the modern software factory, 99.9% uptime is no longer the gold standard. A standard 99.9% SLA translates to approximately 43 minutes of unexpected downtime per month. While industry data shows that a single minute of downtime costs an average of $9,000, for large global enterprises, that figure can easily be 5x higher. At tens of thousands of dollars per minute, those 43 minutes quickly compound into a catastrophic financial and operational risk.

(AusBiz) JFrog teams up with Nvidia to manage AI agents

AI agents are making real-time decisions inside enterprises right now; pulling code, accessing tools, executing tasks. But most businesses have zero visibility into what those agents are actually using. In this interview on @ausbizTV, Sunny Rao, SVP APAC at JFrog, explains why the governance gap is one of the biggest risks facing enterprises today; and how JFrog and NVIDIA are building the trust layer to fix it.

SAS Enhances Security and Compliance with the JFrog Platform

This video features Brett Smith, a distinguished software developer at SAS Institute, discussing how the company secures its software production pipelines for its flagship AI and machine learning platform, SAS Viya 4. SAS initially utilized JFrog Artifactory for managing Java-based Maven and Ivy artifacts. To address the increasing need for robust security and compliance with global regulations, the company expanded its partnership with JFrog by integrating additional security tools to protect their delivery pipelines.

Ending the Chaos of CLI Version Drift: Introducing the JFrog CLI Control Manager

In a large-scale DevOps environment, small discrepancies lead to massive headaches. You’ve likely experienced it: a script runs perfectly on a developer’s laptop but fails in the production pipeline. You spend hours hunting for the cause, only to discover a mismatch in CLI versions. At JFrog, we know the JFrog CLI is vital to your automation, but managing it manually across thousands of users and pipelines is a hurdle that slows you down.