Operations | Monitoring | ITSM | DevOps | Cloud

PagerDuty Joins AWS QuickSuite: Connect Your Incident Management with 1,000+ Applications

Today, we’re announcing that PagerDuty is now available in AWS QuickSuite through the Model Context Protocol (MCP). This means PagerDuty’s incident management capabilities can now connect with the 1,000+ applications and data sources that QuickSuite integrates with, from AWS services to enterprise SaaS platforms, all accessible through natural language.

A Launch Day in the Life with AI Teammates

Alex, an SRE at Greenagonia, starts the day knowing there’s a big launch coming. Pre-orders suggest a 5-10x increase in normal traffic, which means coffee needs to be extra strong this morning. As Alex scans through overnight alerts, he realizes he’s completely forgotten about a dentist appointment that overlaps with his upcoming on-call shift. Six months ago, this would have meant frantic Slack messages or at least one phone call. Today? Alex’s AI teammate has it covered.

PagerDuty H2 2025 Release: 150+ Customer-Driven Features, AI Agents, and More

My first 6 months here at PagerDuty have been a thrilling ride! PagerDuty continues to set the pace in incident management. With our 16-year track record of helping companies forge a path towards modern operations, we’ve been trusted by over 32,000 companies as the incident management platform of choice. Over these years, we’ve continuously delivered value to our customers at a rapid pace. And our customers have been vocal with us about wanting more.

Introducing Runner Replicas: Scalable, Reliable Automation for Modern Ops

When you’re responsible for the reliability of complex systems, the execution layer of your automation is not something you want to think about—it should just work. Whether you’re deploying code, patching servers, or responding to an incident at 3 a.m., your automation engine should be as resilient and scalable as the infrastructure it’s operating on.

The Next Wave of Automation Makes More Room for Humans

When a system goes down, the impact isn’t just technical. It’s the people in the center of it who adapt, improvise, apply their judgment, and keep the business moving forward. I’ve worked in operations for more than 25 years, and one thing I’ve learned is that in any system, it’s the humans who are the truly resilient part.

PagerDuty Joins Glean's AI Ecosystem: Unlocking More Seamless Incident Management

Today, we announced that PagerDuty is now officially part of the Glean MCP Directory! This partnership brings together two leaders in AI-powered productivity and operations, making it easier than ever for organizations to connect PagerDuty’s incident data directly to any AI tool or agent in their stack through the standardized Model Context Protocol (MCP). PagerDuty is the first (and currently only) incident management partner that is available via Glean’s AI ecosystem.

Agentic AI Becomes Essential: Why Adoption Is Accelerating and What Comes Next

The cautious optimism business leaders held towards AI agents has evolved into more widespread enthusiasm. In our last survey from April 2025, just over half (51%) of companies had deployed AI agents in their organization. Six months later, 75% of companies are deploying more than one agent, according to PagerDuty’s latest research.

Automate or Elevate? 5 Steps to Build an AI-Powered Incident Playbook

Modern development tools, CI/CD infrastructure, and AI have accelerated the pace at which companies release software. This speed supports innovation, but it also increases complexity and the chance of something breaking in ways that aren’t immediately obvious. Teams now deal with more operational data, complex failure patterns, and systems where a small configuration change can ripple across dozens of microservices.

You Don't Need a Five-Year AI Plan. You Need a Five-Week One.

In my travels, I constantly hear about plans that promise to “unlock the full power of AI” down the road. The usual advice is to start small with a few pilots, then gradually scale up from there. It looks good on paper, but in practice, it becomes a months-long slog of one-off experiments that burn a lot of capital, but usually generate little impact on their own.