New platform adds a recommendation engine, machine learning based service dependencies and change impact to reduce incidents by 67% and lower Developer and IT costs.
PagerDuty, a global leader in digital operations management, launched the most significant update yet to its Digital Ops platform, during its annual user conference Summit20. The new release applies machine learning and automation to break down the complexity of managing digital operations by reducing interruptions and minimizing the time to resolve issues. PagerDuty’s latest platform release empowers teams in both large enterprises and high growth disruptors to prevent incidents that cause customer dissatisfaction and negative business impact, so they can confidently scale services and accelerate initiatives that capitalize on strong consumer demand for digital services.
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“We now live, work, and learn primarily online. Digital is the new operating system, and operations teams are now on the frontline that keeps businesses running as they manage the technologies that deliver the customer experience and revenue,” said Jennifer Tejada, CEO at PagerDuty. “These teams deserve a cloud native, real-time platform designed for unpredictable emergent work that automates in service of people. PagerDuty is the modern platform for action in the digital default world.”
PagerDuty’s platform release includes new capabilities for event management, incident response and AIOps, as well as advanced insights and analytics that enable a proactive approach to digital ops. As Eric Yuan, CEO and founder of Zoom explains, “We have experienced unprecedented growth in the last six months, requiring us to scale our service without compromising the great video experience our customers expect from Zoom. We could not have done this without PagerDuty underpinning us and this new platform release will only make things easier for our digital teams.”
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The new capabilities in Event Intelligence (an event management and AIOps solution within PagerDuty’s platform) are as follows:
- Intelligent recommendations – New machine learning capabilities in PagerDuty’s Event Intelligence offering automatically identify the noisiest services and provide recommendations to reduce noise so teams can focus on the incidents that matter. While Event Intelligence has long been known for noise reduction, what’s new is the prescriptive nature of the recommendations which are powered by PagerDuty’s machine learning and don’t require training to use.
- Change impact mapping – By linking changes in a customers’ software deployment pipeline with incidents in its digital operations, PagerDuty allows teams to quickly find and resolve an incident’s root cause. With an estimated 80% of incidents caused by change1, this is an important advancement. This new capability integrates change events from code repositories via new integrations with GitHub, Puppet, and Evolven.
- Dynamic service dependencies – New capabilities in PagerDuty’s Service Directory, which provides a single view of a customers’ entire digital operations, dynamically identifies dependencies between people, changes, incidents, and services in real time. It then applies machine learning to automatically keep a company’s service directory up to date, preventing redundant work between teams, and surfacing recommendations for automation of incidents without needing to follow manual steps, or learn advanced skills.
- Flexibly automation controls – Applying AI and automation to something as critical as a company’s digital operations requires complete trust. The platform now includes flexible automation controls to safely ensure that a human is in control at all times by pausing incident notifications, to give systems a chance to auto-remediate before a responder steps in, and by providing push button automation so teams can run automated response play and monitor results.
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