Five Interesting Reads: Data Center Operations Through the Eyes of AI



Five worthy readings is a regular column on five remarkable things we discovered while researching trending and timeless topics. In this edition, we will learn about the deployment of AI in data center operations and how it improves performance and efficiency.

Credits – Illustrator: Balaji KR

Artificial intelligence (AI) is talking about it. Organizations around the world are using technology to support their workforce and especially for mundane tasks so that human efforts can be devoted to more vital activities. Lately, AI has focused on data centers where critical data and applications reside and where only authorized personnel are allowed to enter. How can AI improve operations and performance in a data center? Let’s find out.

With the pandemic forcing the workforce community to stay at home or in remote locations, it has become inevitable for data center service providers to consider other options that would be employee-friendly. while doing the job. AI came to the rescue. Even before the pandemic, Google used AI to cool its data centers, which significantly reduced power requirements. Now, as staff movements are limited due to the pandemic, data center vendors are turning to AI to implement a few innovative and important applications.

The impact of AI is huge and fascinating, and it is deployed for many purposes in data centers. For example, a deployment for capacity planning will manage electrical load, IT resources, and other IT assets to meet customer demands. Other areas where AI is widely used are fault and anomaly detection, root cause analysis, and failure prediction, which also help reduce an organization’s carbon footprint. Advances now include the use of AI-powered robots to locate, inspect and replace faults on premises. Additionally, by using IoT devices and the data they collect, performance issues can easily be proactively addressed. With data collected in large amounts in the data center, the AI ​​in security information and event management technology helps keep cyberattacks at bay as it analyzes the data logs and creates a response system. incidents to counter anomalies.

While AI complements human efforts within data centers, there are gray areas that require constant attention. Industry standards that encompass monitoring AI deployments are necessary because the type and large amount of data is often unknown. A double hit can help stay in compliance with regulations to avoid costly violations and penalties, and streamline implementations. Simulations via AI can show the impact of changes to the infrastructure. Digital twin technology, along with the AI ​​built into DCIM tools, helps deliver better insights before data center changes are implemented.

Here are some interesting articles highlighting various use cases and best practices when using AI in data center operations:

1. Explore the impact of AI in the data center

A good alternative to the conventional method of hiring staff to maintain and monitor data centers is to deploy AI. Not only can it handle tasks such as server optimization and asset management, but it can also help with data and network security, as well as energy conservation within the data center. .

2. Role of chatbots and automation in data center optimization

In well-equipped data centers, AI is used for data management, IT workload management, and cost management. Now with the chatbots in the picture, several tasks are automated to achieve optimized results. Additionally, these bots can be leveraged to provide better interaction and user experience based on the needs of IT teams.

3. AI in data center operations: the effects of artificial intelligence

Another use case involves increasing our reliability on the services provided by data centers. This is provided by using predictive algorithms to take power and latency measurements to maintain performance. In addition, each IT component can be studied via AI, supplemented by advanced monitoring.

4. Impact of AI on Data Centers: AI and Performance Monitoring

To establish optimal performance, AI provides an understanding of expected scenarios versus actual scenarios. This provides a level of insight for effective performance monitoring, which saves costs and energy. Additionally, with exception reporting, teams can adapt a needs-based approach while remaining effective in monitoring and maintaining data center operations.

5. Best Practices for Preparing Data Centers for AI, ML, and DL

As the infrastructure evolves to meet the growing needs and analysis of data, data scientists and IT administrators must work closely together to determine the requirements for AI to become a valuable part of operations. AI is supported by machine learning (ML), a subset of AI that provides the algorithms and techniques for the computer to learn, and deep learning (DL) which is often described as the evolution of ML. Additionally, setting benchmarks and metrics when determining scalability will help choose a suitable approach to integrating AI into data centers without causing issues.

The future looks bright with AI taking a lot of load, despite a few challenges. If these hiccups are removed with the help of appropriate actions, the benefits can be greater than we ever imagined. It’s up to data center vendors to use AI wisely to gain an edge over their competition and stay on top. There is more to AI in data center operations than it looks and we will see these advancements in the years to come.

The article Five Worthy Reads: Data Center Operations Through the Eyes of AI first appeared on the ManageEngine blog.

*** This is a syndicated Security Bloggers Network blog from ManageEngine Blog written by Monisha Ravi. Read the original post at:



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