Operations | Monitoring | ITSM | DevOps | Cloud

Most organizations managing major incidents realized that every moment matters. Context-switching between different tools – with multiple web and chat surfaces having to be open to collect information causes friction. The cost of context-switching during an outage is even more painful. These are the problems that PagerDuty’s Slack Transformation just closed.

PagerDuty’s new intelligent Model Context Protocol (MCP) tools, recently announced in Early Access, are a step toward autonomous operations. Here’s how they help customers get there.

According to a 2025 report from Ravio, entry-level hiring (especially in engineering roles) has collapsed by more than 73% due to increasing AI capabilities. That means junior developer jobs are disappearing. At the same time, demand for senior engineers keeps climbing because organizations need more people to manage and optimize their complex AI agents.

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 PD Automation Runner, now in Early Access, builds towards this vision. Your on-call engineer gets paged for a critical alert on a self-hosted Kubernetes cluster. If this were a cloud-hosted service, Workflow Actions and the SRE Agent would already be working the problem: pulling logs, checking health, surfacing a fix.

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 Scoped OAuth for Public Apps, now in Early Access, builds towards this vision. Your security team asks a simple question during a routine review: which third-party apps can reach our PagerDuty data right now, and what exactly can they do with it?

With AI agents and AI-generated code becoming the norm in modern enterprise software, backend systems are evolving faster than ever. And it’s leaving most operations teams with an impossible choice: burn out senior talent on repetitive firefighting, or hand production over to untrained AI agents. With disruptions costing enterprises an average of $300,000 per hour, manual firefighting isn’t an option.

In a 2025 analysis spanning over 100 large language models, Veracode found that nearly half (45%) of AI-generated code causes known security issues and vulnerabilities. Novel risks are being introduced into your operations systems faster than humans can manage or review. At the same time, studies suggest that human review isn’t all that effective, especially beyond 400 lines of code. But AI-generated code isn’t inherently bad. It just doesn’t always work across your whole system.

As the world is racing to plug AI into nearly every part of business, especially software engineering, the stakes to maintain operational integrity have never been higher. AI-generated code and AI-agents ship faster than human SREs can prepare for, which can create costly issues down the line: incidents get harder to predict and more expensive to recover from.

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 Event Enrichment builds towards this vision. Every on-call engineer knows the drill. An alert fires. It tells you something is wrong, but not what it means. Is this asset in maintenance? Which team owns it? Is it customer-facing?

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 recent SRE Agent Enhancements build towards this vision. During an incident, everything is competing for attention at once. Responders lose time swiveling between tools, insights gathered by AI stay siloed instead of feeding into the next decision, and the pressure to move fast means learnings rarely stick.