Operations | Monitoring | ITSM | DevOps | Cloud

It’s 2:47 p.m. Your checkout service has been down for 11 minutes. Customers are screenshotting errors and calling in. Your CEO walks into your office and starts asking questions. In this moment, there are two kinds of IT leaders: Whether you walk out with more budget authority (and executive trust) or less depends on your answers, and the infrastructure that supports them. But preparation isn’t just about surviving the incident. It’s actually a revenue opportunity.

While most on-call schedules are built to represent regular rotations, often on a weekly basis, not all of your on-call needs require the same coverage every week. We’ve added Custom Shifts to the Shift-Based Schedules for maximum flexibility. Custom shifts are a feature of our new Shift-Based Schedules. With Custom Shifts, your team can cover ad hoc needs for special events, major deploys, Failure Fridays, gamedays, or whatever comes up that needs some extra coverage.

For most enterprises, ServiceNow has become the backbone of IT operations, the platform where workflows are governed, compliance is maintained, and every incident, change, and request is tracked from start to finish. If you’re running ServiceNow, you’ve made a serious investment in how your IT operates. PagerDuty is built to make that investment work even harder.

We recently updated our Schedules to better reflect how teams are currently managing their on-call responsibilities. Not everyone is working on weekly shifts or providing 24×7 coverage for all of their services, and that should be easy to schedule in our new tooling. To give you some examples, I’ve gone back through some of the questions we’ve gotten on the PagerDuty Commons over the past couple of years for questions about custom schedules that we weren’t really thinking about.

A year ago, AI coding tools worked alongside developers—suggesting the next line, completing a function, accelerating work that a human was already doing. Today, they’re writing entire modules and services independently, producing code that no human has reviewed line by line, built from components that no single person has fully mapped. And adoption is only accelerating: According to our recent AI Resilience Survey, 84% of organizations are now using AI to write, review, or suggest code.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey toward autonomous operations. Read on to learn about the PagerDuty agent app in GitHub (Early Access) and how it builds toward this vision. How many tabs do you have open right now? And how many more do you open the moment an incident hits? Context switching during incident response is one of the most persistent sources of toil in engineering.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how AI Orchestrations builds towards this vision. “We should automate this.” Sound familiar? For many operations teams, that sentence never becomes action. Building event orchestration rules demands deep platform expertise, time no one has, and the ability to spot which patterns in your data actually matter.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s Rundeck/RBA 6.0 recently announced in GA builds towards this vision.

Organizations are no longer asking whether to adopt AI; that question is settled. The focus now is on reaching a point where AI is doing meaningful operational work—or as the industry calls it, being “AI-first.” But being “AI-first” isn’t binary. You don’t go from zero AI to meaningful autonomy by flipping a switch. In reality, getting there means moving through distinct stages.