Artificial intelligence (AI) has been front-page news in the last several years. The technology is rapidly maturing and offering new applications and services across a wide range of disciplines. Generative AI products such as ChatGPT have garnered a lot of headlines recently and give the general public a taste of the abilities the technology can provide.

AI and the related technology of machine learning (ML) are being used to address business issues and requirements. Companies are implementing AI solutions to handle customer queries and improve service response time. AI is finding its way into virtually every area of the IT world. It has the potential to make a substantial impact on the way organizations support their IT operations.

What is AIOps?

AIOps is an emerging approach to managing IT operations using advanced AI and ML techniques. Gartner is credited with coining the term in 2016 and defines AIOps as a solution that combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination. The speed and accuracy with which AIOps solutions can address operational issues typically exceed what is possible with an all-human IT operations support team.

One of the factors influencing the interest in AIOps solutions is the diverse and distributed IT architectures favored by many modern businesses. Companies are opting for complex multi-cloud and hybrid environments to address specific business requirements. These infrastructures generate tremendous volumes of log and performance data that can be difficult to correlate and address productively. AIOps can help streamline the analysis of this information and allow IT teams to make more informed decisions regarding operational issues.

How Does AIOps Work?

An AIOps platform is comprised of several components and typically performs multiple steps to automate and optimize IT operations. The following steps form the foundation of an AIOps solution.

  • Data collection – AIOps employs a big data platform to consolidate data from diverse IT infrastructure components. Data sources may include historical log information, network components, and real-time operational data.
  • Data analysis – As it collects data from throughout the environment, an AIOps platform analyzes the information. It provides information such as the source of an alert and if it is critical and demands attention from IT support teams. ML algorithms and predictive analytics are employed to identify anomalies that are real threats as opposed to false alarms or background noise.
  • Root cause analysis – AIOps performs root cause analysis that can be instrumental in identifying how a problem originated. IT teams can use this analysis to take proactive measures to minimize recurrences of the issue.
  • Collaboration – AIOps notifies the appropriate teams and individuals after performing root cause analysis. It provides these entities with relevant information for effective collaboration to address operational issues and prevent them in the future.
  • Automated remediation – In many cases, the AIOps platform can automatically remediate operational issues by taking actions such as scaling resources or restarting services. This speeds up incident response and reduces the need for IT teams to manually intervene to address problems.
  • Training and continuous learning – IT organizations can aggregate data for use in training an AIOps system to address specific issues in the environment. For instance, the system can be trained to efficiently perform resource scaling to ensure all processes are running efficiently. The ML capabilities of AIOps systems enable them to continuously learn and become more proficient at identifying and automatically remediating problems.

What are the Benefits of AIOps?

A reliable AIOps solution should provide the following benefits related to a company’s IT operations.

  • Automate routine issues to relieve the strain on the IT support staff. AIOps can be used to support a help desk and automatically fill standard user requests such as password resets. The platform can also analyze alerts and determine whether action is required. In situations where supporting data indicates a false or non-impactful issue, the alert is not raised to the level of the IT team.
  • AIOps systems can identify potentially serious issues that may escape the notice of the IT team. For instance, AIOps may determine that an unexpected download to a mission-critical server may be dangerous and take action such as running an anti-malware tool. The pervasive nature of an AIOps solution enables it to augment an organization’s IT team and allow them to focus on problems that do not lend themselves to a simple solution.
  • Enhanced communication between various data center teams is supported by an AIOps solution. The platform can supply teams with data relevant to their responsibilities without the addition of information that does not address their concerns. The ML capabilities of an AIOps solution should continuously improve data flow as it learns which metrics are important to different support groups.

AIOps Best Practices

Following these best practices gives an organization an excellent chance of obtaining the preceding benefits.

  • Implementing and maintaining an AIOps platform is a complex undertaking that requires employees skilled in data science and machine learning technology. A lack of proper skills can doom an AIOps initiative to failure.
  • Identify systems that will get the most benefit from an AIOps solution. This may be systems that continuously have issues that affect uptime and service levels. The AIOps platform should be targeted at systems contributing to alert fatigue and those whose root causes cannot be easily identified by IT teams.
  • AIOps should be rolled out incrementally to address specific problems that affect the IT environment. Going too big too soon can bog down progress and minimize the benefits of AIOps. As an organization gains familiarity with the solution, it can be extended to cover larger areas of the infrastructure.

Incorporating AIOps Into Your IT Environment

VAST IT Services can help your company implement an AIOps solution in your cloud-based or on-premises IT environment. Our team has the requisite knowledge necessary to efficiently implement and train the platform to address the unique needs of your business. We can begin with a thorough assessment of your current environment and walk you through our managed infrastructure services which incorporate elements of AIOps to streamline operations.

Call us today and start taking advantage of the benefits of employing artificial intelligence solutions to improve IT operations.