
PagerDuty announced the launch of the PagerDuty Fall '25 Release, an end-to-end AI agent suite.
With more than 150 platform enhancements and deep integrations across the modern tech stack, PagerDuty’s Fall ‘25 release redefines how companies achieve operational resilience and scale in an era of increasing complexity and risk.
“This is a turning point for digital operations,” said Jeffrey Hausman, chief product development officer at PagerDuty. “PagerDuty’s AI agents are not just automating tasks—they’re transforming how organizations innovate and compete in a world where every second counts. Our customers are already seeing dramatic reductions in downtime and a step-change in engineering productivity.”
PagerDuty’s new AI agent suite empowers teams to move beyond manual, reactive incident response. The PagerDuty SRE Agent learns from related incidents, automatically surfaces context, recommends and executes diagnostics and remediations. Additionally, the SRE agent generates self-updating runbooks, which reduce cognitive load and prevent recurring issues. Early customer adopters have reported up to double digit percentage, faster resolution times and significant reductions in on-call fatigue.
- PagerDuty Scribe Agent: Instantly transcribes Zoom calls and chat conversations, generating structured summaries and status updates in Slack or Microsoft Teams, so teams never miss a critical detail during or after an incident.
- PagerDuty Shift Agent: Detects and resolves on-call scheduling conflicts automatically, freeing managers and responders to focus on high-impact work.
- PagerDuty Insights Agent: Delivers context-aware answers and proactive recommendations based on PagerDuty analytics, helping teams anticipate and prevent issues before they escalate.
PagerDuty is expanding its AI ecosystem with the general availability of its remote Model Context Protocol (MCP) server, building on the open standard introduced by Anthropic. This enables seamless, bidirectional connections between PagerDuty and third-party AI agents—removing friction and accelerating time to value. In just two months, over 250 customers have adopted PagerDuty’s MCP server to power their AI-driven operations.
With enhanced integrations for Spotify for Backstage, and strengthening its chat-native experience with Slack and Microsoft Teams, PagerDuty is embedding AI-powered insights and automation directly into developer workflows. Teams will be able to view service health, trigger automated runbooks, and resolve incidents in an improved way—all without context switching. New chat-native experiences and flexible scheduling features will further reduce toil and empower teams to run incidents their way.
PagerDuty SRE Agent: Early access now; general availability projected in Q4 2025.
PagerDuty Scribe Agent: Generally available.
PagerDuty Shift Agent: Generally available.
PagerDuty Insights Agent: Early access now; general availability projected in Q4 2025.
MCP Server and Backstage Integration: Generally available.
Flexible Schedules: Early access projected in Q4 2025.
Chat-first experience enhancements for Slack are now generally available, and are projected to be generally available for Microsoft Teams in Q4 of 2025
The Latest
Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...
AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...
Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...
Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...
Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...
In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...
Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...
Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...
This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...
There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...