Operations | Monitoring | ITSM | DevOps | Cloud

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.

Donnie Berkholz is a VP of IT Service Delivery and comments frequently on trends in IT infrastructure in his newsletter. We talked to Donnie about his typical day on the job, his initiatives in self-service platforms and product management and his take on top infrastructure management trends such as AIOps and Kubernetes.

Modern hybrid-IT environments are monitored by numerous multi-vendor and multi-domain monitoring tools that generate humongous amounts of alerts and events, most of which are not readily actionable. The Industry term for this is “Alert Noise”. Noisy alerts increase the risk of real alerts going undetected causing service outages. These alerts also carry siloed information missing the application or service context.

The sudden shift to remote work caused by the global pandemic has forced IT Ops pros to quickly adjust in multiple ways to maintain the uptime and stability of critical digital services. Amidst this crisis, AIOps has emerged as a lifeline, as it facilitates remote collaboration, streamlines incident management, and accelerates detection and resolution.