With the move to microservices, DevOps practices, and now AI-assisted programming, teams are moving faster than ever. With that additional agility comes exponential amounts of data and increased operational complexity. The teams and processes responsible for keeping digital customer experiences highly available and seamless are struggling to keep up.

This is especially bad when incidents strike. Alert noise and alert storms are causing teams to spend too much time sifting out the signal from the noise. Once teams determine the signal to look at, they’re not sure what to do with it. In fact, according to PagerDuty surveys, 59% of the responders said that finding the root cause has become harder due to the complexity of the infrastructure and all the pieces that are around it. The solution isn’t more data – teams need more actionable information.

Organizations today are looking for a way to get data quickly and make sense of it to drive to the next best action. One way to do this is by gathering relevant data from leading cloud providers such as AWS and leveraging AI and machine learning to turn that data into actionable insights. Only then can teams drive to faster resolution and learn from it to set up automation that can deflect unnecessary noise for fewer incidents.

In this webinar, you’ll learn:

• How PagerDuty and AWS partner to deliver relevant insight in the incident response lifecycle in real-time
• How to reduce noise across an organization’s entire technical ecosystem using AI
• How to use AI and ML for more efficient triage to drive to resolution