Operations | Monitoring | ITSM | DevOps | Cloud

DevOps has become the go-to-approach for IT to accelerate their ability to achieve business requirements and ensure the quality of the customer experience. Today’s economy and the customer experience drives IT across the entire stack. Our world has become digitally dependent, which mandates an ever-evolving IT environment that’s on-demand and always available.

By abruptly forcing most people to work from home, and by triggering an economic crisis, the global pandemic has upended business operations. Not only must business leaders facilitate remote work among their employees, but they must also accommodate new ways of interacting with suppliers, partners and customers. Meanwhile, businesses’ digital channels and infrastructure, already critical prior to the crisis, have become even more essential, and yet harder to monitor and manage.

In this second installment of this blog series, we’ll discuss the importance of analyzing metrics, and how AIOps helps you with this fundamental pillar of observability. Without proper metrics analysis, you’re left blind to potential outages, or possibly worse — inundated with false positive anomalies, leading to alert fatigue and ultimately business impacts. Automated discovery and analysis can’t be achieved with legacy tools nor will it scale with humans.

DevOps pipelines generate massive amounts of data. To maintain the stability and speed of application delivery, operations leaders must analyze it quickly and continuously. But how can they keep DevOps — and their business — agile? Gartner’s “Augment Decision Making in DevOps Using AI Techniques” provides, in our view, the answer for operations leaders to make precise data-driven decisions and automate actions for rapid application delivery.

To leverage IT innovations like cloud computing, containers and microservices, and to meet customer experience expectations, IT teams must monitor their applications and services differently. The reason is that developers are deliberately disseminating information through their code in order to understand and manage the complexity in today’s ephemeral and dynamic environments.

Algorithms are at the heart of the technologies we use in virtually every facet of our daily lives — formulas and processes that help us connect, solve problems and accomplish amazing things. Things like better speech recognition and landing an autonomous rocket on a drone ship, or giving us really great Netflix recommendations. But an algorithm is just a set of rules or a set of tasks to perform given a certain input.