Operations | Monitoring | ITSM | DevOps | Cloud

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.