Operations | Monitoring | ITSM | DevOps | Cloud

Three months ago, a CIO told me her organization had “already deployed agents.” Her endpoint team assumed she meant the telemetry clients on every managed laptop. Her service desk thought she meant AI chatbots. Meanwhile, her security architect heard “autonomous decision-making.” They were all right and all talking past each other. This is the agent confusion problem.

The Atlassian Rovo Model Context Protocol MCP Server now supports Bitbucket Cloud. AI clients like Claude, ChatGPT, Cursor, and VS Code can now browse repositories, create commits, open pull requests, and check pipeline results, all through the same secure MCP connection that already works with Jira and Confluence.

For today's modern businesses, the data landscape demands security and flexibility. You need to connect your observability platform to rich, proprietary datasets that often reside in private networks without compromising security or managing complex network infrastructure. You may also face an extra layer of complexity in order to effectively query and visualize that data. Luckily, modern artificial intelligence tools have made these previously complicated processes much simpler.

Hybrid IT environments are the reality for most organizations today. Unfortunately, they’re also one of the biggest reasons outages are now harder to prevent. Between on-prem infrastructure, cloud services, SaaS platforms, distributed networks, and modern applications, IT teams are managing an ecosystem of dependencies that changes constantly.