Operations | Monitoring | ITSM | DevOps | Cloud

As we enter 2025, we reflect on a year committed to innovation and customer success at PagerDuty. In 2024, we introduced capabilities that empowered operations teams to mitigate risks, protect customer trust, and improve business outcomes. From managing global outages to addressing complex digital operations, the PagerDuty Operations Cloud enabled organizations to respond faster, work smarter, and build operational resilience.

The stress, sudden disruptions, and high stakes of resolving issues while on call is one of the most challenging aspects of an engineer’s job. Many organizations, from startups to large enterprises, still struggle with their on-call experience, which leads to longer resolution times and lower employee retention rates. Constant context switching, managing multiple tools, and racing against time to resolve issues can cause frustration, burnout, and inefficiency.

Artificial intelligence (AI) is reshaping industries, and software development is no exception. By integrating AI technologies like machine learning, generative AI, and natural language processing, development teams can optimize workflows, enhance code quality, and reduce time-to-market. In this article, we’ll examine AI in software development, including its benefits, challenges, and most recent developments. Let’s get started.

It's no secret that building a data-driven culture in a company is hard, but what is it exactly that makes this such a tricky endeavor? Contrary to popular belief, technology isn't the main hurdle. A recent survey reveals that only a quarter of respondents cite technological limitations as the primary obstacle to becoming data-driven.

In 2024, we focused on operating at a very high speed. Every week was a lot of tiny releases, meeting with users, fulfilling user requests and focusing on simplicity. Still an incredibly small team (< 10) but tons of releases. 2025 is going to be great but before that let's glance on the year gone. Read the 2023 recap.

What is Alerting? Alerting is a central component of modern safety and operating concepts. It is used to act quickly and effectively in hazardous situations. From operational alerting in operations management to alerting the population, there are various scenarios that cover specific requirements and areas of application. In this article, we provide an overview of the various alerting methods and their significance.

Do you feel you’re always playing catch-up with incidents? If so, you’re not alone. As IT environments become more complex, alerts keep piling up, and finding the root cause feels like searching for a needle in a haystack. And ITOps and incident responders are left scratching their heads and wondering: what went wrong? It can be frustrating when you don’t have end-to-end visibility into your systems. This is where observability comes in.

Being an on-call engineer is often overwhelming, requiring you to pivot between tickets, dashboards, runbooks, and different data sources as you try to separate legitimate incidents from unnecessary noise. Not only does the process of investigating irrelevant alerts take time away from remediating important issues, but it also compounds alert fatigue.