Operations | Monitoring | ITSM | DevOps | Cloud

Something fundamental needs to change in the way we run operations. Organizations are deploying AI to optimize everything from coding and deployment to resource planning and incident management. But they’re discovering that managing AI-powered systems requires a completely different operational mindset. AI models hallucinate. Data pipelines degrade silently. Algorithms develop bias without warning.

Too many incidents waste valuable engineering time on the basics: collecting logs, pulling system data, and tracking down the right person to fix the issue. Meanwhile, customers experience delays, SLAs are breached, and critical work gets pushed aside. The real kicker? Those L3 and L4 severity incidents that could actually prevent future fires get labeled as “nice to have” and collect dust in your backlog. Automated diagnostics and triage eliminates these bottlenecks.

Summer is in full swing, and we’ve been busy cooking up some exciting updates to make your operations life easier (and less stressful). This quarter has been all about bringing AI agents into the mix to handle the heavy lifting—whether that’s fixing those pesky recurring issues automatically or surfacing the exact context you need when something totally new breaks. We’re excited about the impact this will have on your day-to-day operations.

State and local governments face an increasingly complex challenge: delivering reliable digital services to the public while operating under tighter budget constraints and reduced federal funding. As taxpayers demand more efficient operations, government leadership must ensure every technology purchase can show clear return on investment (ROI) value.

There’s no shortage of hype around AI in operations, but recognition from a trusted source like GigaOm cuts through the noise. We are excited to share that PagerDuty earned a top spot as a Leader and Outperformer in the 2025 report. It’s recognition that reflects the progress we’ve made in delivering an AI-powered platform that actually helps teams move faster, reduce costs, and operate with confidence in complex environments.

Organizations migrating from Opsgenie and other legacy incident management platforms are discovering that basic connectivity monitoring isn’t enough for modern operations. While Opsgenie Heartbeats and similar traditional heartbeat features offer simple binary status checks of system availability, PagerDuty’s AIOps-powered approach transforms system health monitoring from reactive alerting into intelligent, automated operational intelligence.

Every organization wants to innovate, but the reality is that operational friction can grind even the most ambitious plans to a halt. A delayed response here, an inactionable alert there, and suddenly your engineers are spending more time firefighting than building. Context is scattered across tools, and the “big picture” is lost in a sea of alerts and thumbnail-sized dashboards that provide no context or direction.

The recent outage on June 12 proved yet again that service disruptions are inevitable, it’s not a matter of if, but when? And the next question is: how ready are you when that disruption strikes? What sets successful leaders apart is how quickly they are able to recover. Digital businesses are more complex than ever. Teams are managing sprawling cloud environments, microservices architectures, and a dizzying array of third-party integrations.

AI doesn’t replace teams. It frees them. AI can be viewed as a digital twin, shouldering the manual load, eliminating low-value work and giving people their time back. In network operations, where every second counts and pressure never lets up, AI becomes the way to rise above the pressing workload. The overwhelming workload isn’t due to teams being incapable, but more because they’re buried in busywork.

In the past year alone, we’ve seen just how much a single outage can disrupt and how much stronger teams become when they learn from it. From the July 16, 2024 incident to the widespread June 2025 outage, it’s clear that incidents are inevitable. The question is: how do you transform each disruption into an opportunity to improve your processes for the next one?