Skip to main content

PagerDuty Announces Latest Release of Operations Cloud Platform

PagerDuty will add new agentic AI functionality across the PagerDuty Operations Cloud platform beginning with its Spring 25 release, which will help enterprises solve high-impact, mission-critical issues. 

The company also announced new packaging of its Incident Management products to deliver premium features, capabilities and value to PagerDuty customers.

With PagerDuty AI agents, powered by the PagerDuty Operations Cloud’s generative AI offering, PagerDuty Advance, organizations will be able to use agentic AI to reduce operating costs by automating repetitive tasks, mitigating risk by resolving incidents faster and increasing revenue by ensuring seamless customer experiences.

The company is building PagerDuty AI agents, starting with agents for site reliability engineering, operational insights and scheduling optimization. Beginning with the Spring 25 release, advanced AI agents will work with responders and autonomously resolve issues, empowering organizations to efficiently redeploy their resources towards higher-value work.

PagerDuty’s AI agents will include:  

  • Agentic Site Reliability Engineer: Will identify and classify operational issues, surfacing important context such as related or past issues and guiding responders with recommendations to accelerate resolution, thus mitigating business risk caused by operational disruption and enhancing the customer experience.
  • Agentic Operations Analyst: Will analyze data across an organization’s ecosystem of tools to identify patterns needed for strategic operational decisions, continuously improving operational and business efficiency.
  • Agentic Scheduler: Will preempt scheduling and availability conflicts by dynamically adjusting on-call shifts to ensure seamless responder coverage, driving faster resolution that can result in lower operational costs and positive customer impact.
  • AI use case library: To help PagerDuty customers realize the full potential of generative AI and agentic innovation, PagerDuty is launching a curated repository of field-tested AI prompts with relevant integrations. The use case library empowers customers to customize and combine generative AI prompts to address a wide range of mission-critical use cases and business challenges – ensuring fast time to value, guided by generative AI best practices.

“Operations leaders have high expectations for the business value of AI and automation,” said Jeffrey Hausman, chief product development officer at PagerDuty. “With the AI-powered PagerDuty Operations Cloud, teams can make smarter decisions, resolve critical issues faster and focus on top-level business priorities. We are excited to bring PagerDuty AI agents to market that will enable operations teams to gain time and efficiency, enabling them to focus on increasing revenues and improving customer satisfaction, while reducing operating costs.”

PagerDuty continues to invest in these relationships to ensure its customers can realize the benefits of the PagerDuty Operations Cloud:  

  • Slack AI Assistant - PagerDuty Advance’s generative AI capabilities can now be directly accessed within Slack’s AI partner ecosystem. The PagerDuty Slack assistant enables responders to work seamlessly with greater context and move decisively to resolve issues faster, efficiently mitigating risk and enhancing customer experience. PagerDuty is the only industry-leading IT operations platform selected as a launch partner in Slack’s AI Assistant inaugural program.
  • Zoom - Zoom and PagerDuty are collaborating to increase efficiency across IT and Engineering teams by applying generative AI to automatically summarize rich incident notes and post-incident reviews, speeding up organizational collaboration to resolve issues and learn faster to preempt future disruptions. The new Zoom real-time API integration will be available for early access in Q2.
  • Amazon Q - PagerDuty was the first incident management platform to integrate with Amazon Q Business, and PagerDuty will continue to expand that relationship with integration to the Amazon Q Data Accessor capability. Businesses use over 100 SaaS applications on average, often creating data silos that hinder AI’s potential to drive true operational resilience. Bringing PagerDuty Advance together with Amazon Q will unlock those silos and make that data actionable. For example, using data accessible by Amazon Q, PagerDuty Advance could analyze a medical device company's customer trial data, flag an anomaly, identify the root cause, and recommend the replacement of a faulty component before mass production. This AI-driven, integrated approach to operational transparency and resiliency could prevent costly recalls, lawsuits, and regulatory fines while preserving customer trust and ensuring safety and compliance. The Amazon Q and PagerDuty data integration will be available for early access in Q2.

PagerDuty is redefining its Business and Professional plans for Incident Management by including critical AI and automation capabilities across all paid tiers to deliver full end-to-end incident management for all customers. This new approach embeds select premium features within the Business and Professional plans for Incident Management, with a unified chat experience where teams can leverage the PagerDuty platform within a single interface. These updates deliver greater value at no additional cost, ensuring that all types of businesses grow seamlessly with PagerDuty while streamlining their operations across a scalable enterprise-grade platform.

The first PagerDuty AI agent will be available for early access in North America starting in the fiscal year Q2 of 2025.

The PagerDuty AI use case library is now generally available in all regions.

Unified chat experience and Incident Types are now generally available for PagerDuty Incident Management and Customer Service Operations customers.

The Slack AI Assistant with integrated PagerDuty Advance is now generally available in North America.

The Zoom real-time API PagerDuty integration will be available for early access in North America in Q2 of 2025.

The PagerDuty Advance and Amazon Q Data Accessor integration will be available for early access in North America in Q2 of 2025.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

PagerDuty Announces Latest Release of Operations Cloud Platform

PagerDuty will add new agentic AI functionality across the PagerDuty Operations Cloud platform beginning with its Spring 25 release, which will help enterprises solve high-impact, mission-critical issues. 

The company also announced new packaging of its Incident Management products to deliver premium features, capabilities and value to PagerDuty customers.

With PagerDuty AI agents, powered by the PagerDuty Operations Cloud’s generative AI offering, PagerDuty Advance, organizations will be able to use agentic AI to reduce operating costs by automating repetitive tasks, mitigating risk by resolving incidents faster and increasing revenue by ensuring seamless customer experiences.

The company is building PagerDuty AI agents, starting with agents for site reliability engineering, operational insights and scheduling optimization. Beginning with the Spring 25 release, advanced AI agents will work with responders and autonomously resolve issues, empowering organizations to efficiently redeploy their resources towards higher-value work.

PagerDuty’s AI agents will include:  

  • Agentic Site Reliability Engineer: Will identify and classify operational issues, surfacing important context such as related or past issues and guiding responders with recommendations to accelerate resolution, thus mitigating business risk caused by operational disruption and enhancing the customer experience.
  • Agentic Operations Analyst: Will analyze data across an organization’s ecosystem of tools to identify patterns needed for strategic operational decisions, continuously improving operational and business efficiency.
  • Agentic Scheduler: Will preempt scheduling and availability conflicts by dynamically adjusting on-call shifts to ensure seamless responder coverage, driving faster resolution that can result in lower operational costs and positive customer impact.
  • AI use case library: To help PagerDuty customers realize the full potential of generative AI and agentic innovation, PagerDuty is launching a curated repository of field-tested AI prompts with relevant integrations. The use case library empowers customers to customize and combine generative AI prompts to address a wide range of mission-critical use cases and business challenges – ensuring fast time to value, guided by generative AI best practices.

“Operations leaders have high expectations for the business value of AI and automation,” said Jeffrey Hausman, chief product development officer at PagerDuty. “With the AI-powered PagerDuty Operations Cloud, teams can make smarter decisions, resolve critical issues faster and focus on top-level business priorities. We are excited to bring PagerDuty AI agents to market that will enable operations teams to gain time and efficiency, enabling them to focus on increasing revenues and improving customer satisfaction, while reducing operating costs.”

PagerDuty continues to invest in these relationships to ensure its customers can realize the benefits of the PagerDuty Operations Cloud:  

  • Slack AI Assistant - PagerDuty Advance’s generative AI capabilities can now be directly accessed within Slack’s AI partner ecosystem. The PagerDuty Slack assistant enables responders to work seamlessly with greater context and move decisively to resolve issues faster, efficiently mitigating risk and enhancing customer experience. PagerDuty is the only industry-leading IT operations platform selected as a launch partner in Slack’s AI Assistant inaugural program.
  • Zoom - Zoom and PagerDuty are collaborating to increase efficiency across IT and Engineering teams by applying generative AI to automatically summarize rich incident notes and post-incident reviews, speeding up organizational collaboration to resolve issues and learn faster to preempt future disruptions. The new Zoom real-time API integration will be available for early access in Q2.
  • Amazon Q - PagerDuty was the first incident management platform to integrate with Amazon Q Business, and PagerDuty will continue to expand that relationship with integration to the Amazon Q Data Accessor capability. Businesses use over 100 SaaS applications on average, often creating data silos that hinder AI’s potential to drive true operational resilience. Bringing PagerDuty Advance together with Amazon Q will unlock those silos and make that data actionable. For example, using data accessible by Amazon Q, PagerDuty Advance could analyze a medical device company's customer trial data, flag an anomaly, identify the root cause, and recommend the replacement of a faulty component before mass production. This AI-driven, integrated approach to operational transparency and resiliency could prevent costly recalls, lawsuits, and regulatory fines while preserving customer trust and ensuring safety and compliance. The Amazon Q and PagerDuty data integration will be available for early access in Q2.

PagerDuty is redefining its Business and Professional plans for Incident Management by including critical AI and automation capabilities across all paid tiers to deliver full end-to-end incident management for all customers. This new approach embeds select premium features within the Business and Professional plans for Incident Management, with a unified chat experience where teams can leverage the PagerDuty platform within a single interface. These updates deliver greater value at no additional cost, ensuring that all types of businesses grow seamlessly with PagerDuty while streamlining their operations across a scalable enterprise-grade platform.

The first PagerDuty AI agent will be available for early access in North America starting in the fiscal year Q2 of 2025.

The PagerDuty AI use case library is now generally available in all regions.

Unified chat experience and Incident Types are now generally available for PagerDuty Incident Management and Customer Service Operations customers.

The Slack AI Assistant with integrated PagerDuty Advance is now generally available in North America.

The Zoom real-time API PagerDuty integration will be available for early access in North America in Q2 of 2025.

The PagerDuty Advance and Amazon Q Data Accessor integration will be available for early access in North America in Q2 of 2025.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.