How to boost your server management with AI

Server management has always been a tricky process, thus many organizations and individuals felt the need to incorporate measures to make it more efficient. AI brings new, never-seen-before automation capabilities, that can help users and companies manage their servers in less time, and with fewer investments.

For server management, AI can complete repetitive tasks, monitor servers, and reduce downtime. You can easily feel the benefits of AI tools for servers by simply trying them if you already have a server.

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Let’s look at how AI can help you take server management to the next level.

AI tools can be and are mainly used for purposes of automation, and analytics regarding complex IT tasks, and operational data associated with them.

In the context of servers, it means that AI is able to process data, spot issues, and vulnerabilities, monitor and analyze server performance, create and utilize the practice of smart resource distribution, and, ultimately, sustain the health and efficacy of the server infrastructure.

AI tools in general can be put under the category of AIOps or Artificial intelligence for IT operations. There’s a specific process AI follows when working with the server, and it looks something like this:

1. Gathering of data: AI collects data from the whole environment of your server, which includes logs, and performance metrics from the server itself, its software, and networks.

2. Data analysis: Then artificial intelligence goes through the data and analyzes it using its algorithms. It is especially good in terms of identifying patterns and correlations, not always obvious to human perception.

3. Issue recognition: AI can identify the problem and its root cause using the data it gathers and insights drawn from it. It can also offer the evaluation of the problem’s severity and complexity.

4. Automated response: While AI can help with troubleshooting issues, its main focus is automation, including the one associated with recognizing the issues and notifying about their occurrence.

One of the distinct characteristics of AI is that it learns and adapts quickly, and that’s how it is able to automate so many tasks, reduce server downtime, and ultimately improve server management.

Benefits of managing servers with AI

Implementing AI into server management brings many advantages and often results in:

• Advanced task automation: AI can automate many tasks that are currently done manually including monitoring, optimizing system processes, identifying issues, and troubleshooting. This way IT staff can focus on tasks that need their attention more.

• Cost saving: Leveraging automation will reduce time spent on completing tasks, thus decreasing the overall cost of operations.

• Increasing system reliability and security: AI can spot vulnerabilities and actual issues (including those related to security), and promptly give notifications and advice on how to eliminate problems.

• Providing valuable insights: AI draws analytics that can provide valuable insights into server performance, helping IT professionals to make informed decisions.

• More adaptability and scalability: AI itself can easily adapt to different demands and workloads, and it helps servers to do the same.

• Server performance optimization: AI tools can optimize the performance of the server by, for example, allocating resources or prioritizing tasks based on the load metrics, etc.

There are multiple AI tools that can improve your server management. They vary based on what areas of server management you want help with. You might have the following requests:

• Strengthening of cybersecurity: There are AI cybersecurity applications that help detect malicious traffic, unknown activity, or system vulnerabilities such as Darktrace, Cylance, and SentineIOne.

• Analyzing the data: AI can grasp huge amounts of data, analyze and summarize it for you to then have an accurate idea of the core pattern in the data. Apps like Julius AI, Coefficient, and Polymer can help you clarify information, analyze patterns and tendencies, and create a prognosis.

• Server monitoring: AI-based applications can monitor the server’s activity in real-time, identifying performance irregularities and finding ways to eliminate them. Tools like Prometheus, Zabbix, or Grafana Labs can help you monitor the server performance and are able to give advice on how to optimize it.

• Datacenter advancement: AI can even be used in a data center, where your physical server resides. Artificial intelligence can be integrated into the distribution management system of the facility and can help with managing power, cooling, network activity, or hardware monitoring, all of which will undoubtedly make it easier for the end user to optimize the software part of their server.