Operations | Monitoring | ITSM | DevOps | Cloud

AIOps Essentials: What is AIOps? | AIOps Use Cases with Elastic Observability (1/5)

Artificial intelligence for IT operations (AIOps) is a way to automate tasks that are typically carried out by site reliability engineers (SREs). It aims to make the lives of SREs easier by helping them reduce the amount of noise coming from systems, surface issues more easily, and perform root cause analysis by correlating data from different systems. AIOps can also automate actions based on identified problems using machine learning. In this video series, we demonstrate how to use Elastic to implement AIOps.

AIOps Essentials: How to Reduce Noise in Ingested Telemetry on Elastic | AIOps Use Cases (2/5)

Artificial intelligence for IT operations (AIOps) is a way to automate tasks that are typically carried out by site reliability engineers (SREs). It aims to make the lives of SREs easier by helping them reduce the amount of noise coming from systems, surface issues more easily, and perform root cause analysis by correlating data from different systems.

AIOps Essentials: Issue Detection using Anomaly Detection on top of APM | AIOps Use Cases (3/5)

Artificial intelligence for IT operations (AIOps) is a way to automate tasks that are typically carried out by site reliability engineers (SREs). It aims to make the lives of SREs easier by helping them reduce the amount of noise coming from systems, surface issues more easily, and perform root cause analysis by correlating data from different systems

AIOps Essentials: How to use Distributed Tracing for Root Cause Analysis | AIOps Use Cases (4/5)

Artificial intelligence for IT operations (AIOps) is a way to automate tasks that are typically carried out by site reliability engineers (SREs). It aims to make the lives of SREs easier by helping them reduce the amount of noise coming from systems, surface issues more easily, and perform root cause analysis by correlating data from different systems.

AIOps Essentials: Automating actions from AIOps analysis | AIOps Use Cases (5/5)

Artificial intelligence for IT operations (AIOps) is a way to automate tasks that are typically carried out by site reliability engineers (SREs). It aims to make the lives of SREs easier by helping them reduce the amount of noise coming from systems, surface issues more easily, and perform root cause analysis by correlating data from different systems.

5 best incident management tools of 2023

Put simply, managing incidents—big or small—is good for business. Not only is it a regulatory requirement, but also a factor in your profits. Your customers expect smooth operations, good customer service and protection. A dedicated incident management tool can help protect all of these. While many may think of incidents as an IT or DevOps issue, it’s hard to over emphasize that they can happen in any department.

Automating Root Cause Analysis with AIOps

A lot is expected of automation in IT environments in the next few years. By 2024 Gartner predicts IT automation will drive a 20% reduction in unplanned downtime and lower operational costs by 30%. At the same time, the efficiencies generated by IT automation and analytics will allow organizations to refocus 30% of their IT operations management resources from support to “continuous engineering.”

Why DevOps needs an AIOps approach?

This need for AIOps was simmering conveniently and gradually reaching its threshold when the pandemic suddenly hit the world, pushing organizations into remote work. The sudden, global-scale change raised challenges for IT operations teams to monitor and detect incidents in a distributed environment and maintain cybersecurity and compliance. While the pandemic pushed some organizations into the reality of remote work, others were already on their way to digital transformation.