Operations | Monitoring | ITSM | DevOps | Cloud

In today’s highly competitive and volatile business environment, service outages can result in the loss of customers. Because of those high stakes, it’s imperative that companies take action to avoid outages. But how can you prevent them before they happen? Enter artificial intelligence (AI). AI and machine learning can run in the background to monitor systems and detect anomalies before humans can spot them. ServiceNow Predictive AIOps was designed with this purpose in mind.

Today, IT operations teams have to process large volumes of events or alarms in near real-time in order to protect service levels, stay competitive, and deliver a great experience to customers. If it takes too long for teams to spot and repair issues, an organization runs the risk of significant business service downtime, SLA penalties, and brand reputation damages. As IT landscapes continue to grow in scale and complexity, guarding against these risks becomes increasingly difficult.

At PagerDuty, we are committed to championing the customer — it’s a core company value. Our product has to provide great value, we have to provide excellent service, and we need to make it simple to do business with us. The Winter 2022 G2 Grid for AIOps Platforms Relationship Index showcases these values and highlights PagerDuty as a leading player in the AIOps space.

I am excited to announce today that BigPanda has secured $190 million in financing at a $1.2 billion valuation. This financing was led by Advent International and Insight Partners, together with our other existing investors. BigPanda is now officially a unicorn, and the clear leader in the rapidly growing AIOps market!

Time for a bit of a review! Join Jason as he looks back on some previous guests who have shared some opinions that range from the idiosyncratic to down right unpopular. Pulling from a handful of “Breaking Things” interviews, Jason covers death to VPNs, to the validity of “AI Ops,” check out the litany!

In our increasingly hyper-connected, data-dependent world, it can be difficult to keep track of where resources are, how to access them, and how to put data assets to work to run a more efficient and reliable enterprise. Traditional approaches to IT operations analytics are becoming outmoded as the sources and types of data grow more mobile, ephemeral, diverse and distributed.