What AIOps means for the datacenter

What AIOps means for the datacenter

What AIOps means for the datacenter

Let’s cut through the hype: what can AIOps do to help IT teams perform their mission

AIOps – In this modern era of the hybrid datacenter, consisting of cloud, a combination of on-prem technologies and management methodologies, IT operations teams are grappling with the resulting ever increasing complexity as they attempt to adapt to this new reality. One only needs to glance at the news to see the increasing number of slow-downs and outages bringing down banking and financial operations; forcing airports to a standstill; and impacting the accessibility of medical records.

The effects of our mounting data growth urgently need addressing. There is little doubt that we have just reached a stage where the complexity and rate of change has far surpassed traditional human IT teams’ ability to effectively manage the infrastructure.

Integrating with legacy
Technology advancement is a fantastic thing, but new products do not always effectively integrate within legacy environments, causing gaping vulnerabilities. This has resulted in organizations becoming ill equipped to keep up with the pace of change and get to grips with how these deployments affect the behaviour and performance of application workloads. The effect of these slow-downs and outages hit right at the customer, causing significant financial loss to the company, not to mention its damaged reputation and idled workers. To help navigate this tumultuous path, artificial intelligence for IT operations (AIOps -a term coined by Gartner), has arisen as a solution. It came about as IT operations teams found that they needed a new approach to manage the various elements and complexity of the technology stack as it increased.

While it is generally accepted that automation is a key priority for modern data centers (supporting IT teams in ensuring the consistent running of operational processes, aiding the reduction of costs and time spent on maintenance), a true understanding of AIOps it seems, evades many. In simple terms, AIOps can be viewed in a similar way, using anomaly detection and machine learning to enhance the human capability to understand, reducing the time it takes to locate and diagnose performance problems.

AIOps applied to infrastructure performance management (IPM) powerfully ensures optimum performance, overseeing the health and utilisation of business critical customer-facing applications, with the ability to provide alerts in advance of any potential blockages or latency issues within the infrastructure.

AIOps benefits
AIOps intelligently and effectively helps to monitor and oversee the complexity of all of the numerous disparate components and various deployments of the hybrid datacenter (be it cloud, flash storage, hyperconverged, etc.). It effectively monitors, correlates and prioritizes infrastructure processes for IT operations, so that they run as smoothly as possible, no matter what the stresses and strains on the ecosystem, be it ad hoc, or seasonal. AIOps is also used for capacity planning across the infrastructure to optimize application availability and performance. Leveraging heuristics and algorithms, it can detect and expose anomalies and the potential ticking time-bombs in the infrastructure. AIOps event correlation and analytics capabilities mean that it can mine an influx of less important alerts to highlight the ones that are critical to the running of the business.

As the stack has become more and more complex and mission critical, the capabilities of AIOps are urgently required. Traditional methods and proprietary, legacy tools are simply no longer up to the job in today’s hybrid, virtualized and multi-vendor environment.

This article originally appeared on datacenterdynamics.com To read the full article and see the images, click here.

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