Operations | Monitoring | ITSM | DevOps | Cloud

Stop Babysitting Your Deployments

Deployments that need multiple reboots shouldn't need a technician hovering over them the whole time. But for most teams, that's exactly what happens — you kick off a job, walk away, and come back to find it stalled halfway through waiting for something nobody handled. Product Manager, Dan Myers, joins this stream to show how these new updates changes enterprise-scale provisioning and deep OS deployments, making your automation smarter than ever before. What you'll learn.

Teamwork Collection - Power the era of human-AI collaboration | Team '26 | Atlassian

As organizations work to bring humans, agents, and automation together, teamwork is getting even more complex. If your AI strategy feels like a collection of one-off experiments layered onto disconnected tools and siloed knowledge, join Atlassian leaders to see how Teamwork Collection brings together Jira, Confluence, Loom, and Rovo into a connected foundation for human-AI collaboration at scale.

Anthropic Shipped An Enterprise Analytics API. We Shipped the Claude Adapter Today.

Anthropic just shipped an Enterprise Analytics API with user-level token and cost data. Today, we're shipping the CloudZero adapter that maps that data to teams, budgets, and cost centers — so Claude spend gets the same accountability as the rest of your stack. Anthropic released the first beta of its Enterprise Analytics API this week. Admins can pull token usage and dollar cost through a programmatic endpoint, broken down by user, model, context window, region, and product surface.

Why agentic AI development needs reliability guardrails

AI has massively accelerated code deployment. In fact, since the introduction of agentic coding, GitHub has seen exponential growth in PRs, commits, and new repos. What they originally predicted would require 10X capacity, they’re now estimating it’s going to require 30X capacity, and the biggest driver is agentic development. Companies across industries are building agentic pipelines to ship features faster than ever before. That acceleration isn’t without risk.

There's an npm-shaped hole in the AI tooling stack

I've had this same conversation with 60+ engineering teams in the last six months. A team adopts AI tooling. One developer figures out how to use it well, builds up a vault of skills, MCP configs, and slash commands that 10x their output. The rest of the team has whatever they can scavenge from a shared Notion doc.

Why IT Teams Choose OnPage Over Opsgenie: 5 Key Benefits

With Atlassian announcing the sunsetting of Opsgenie, IT teams, MSPs, and cybersecurity professionals find themselves at a critical crossroads. Technical leaders are actively searching the market for reliable opsgenie alternatives to keep their infrastructure running smoothly and minimize downtime. While migrating platforms can feel like a frustrating chore, it’s actually the perfect opportunity to upgrade your incident response strategy.

Building Real-Time Telemetry Pipelines for IRIG 106 compliance

Every second of a flight test produces a torrent of telemetry from engines, sensors, and control systems. Aerospace teams have captured this data for decades to verify performance and maintain safety, yet analysis often happens long after the mission ends. Engineers wait for downloads, conversions, and compliance checks before they can interpret results. That delay turns telemetry into a historical record instead of a feedback loop.

When your agents hallucinate at 2 am, it is not a model problem

The first time an AI assistant suggests "restart the service" during a live incident and nobody on the bridge can tell whether that suggestion came from a current runbook, a stale wiki page, or thin air, you stop caring about model benchmarks. You start caring about what the agent actually knew, where that knowledge came from, and whether you can trust the chain of reasoning behind it.