As businesses increasingly rely on technology to drive growth, they face mounting pressure to keep their IT systems running smoothly. Even a minor glitch can frustrate customers and employees, hinder productivity, and lead to revenue loss. AIOps use cases help alleviate these pressures by automatically detecting anomalies and resolving IT issues before they disrupt business operations. In this article, we’ll explore the most common Artificial Intelligence Operating System use cases and how they can help you build a more intelligent, more resilient IT infrastructure that scales seamlessly with the demands of modern business.
AI Acquisition's AI operating system is a key tool for achieving your business objectives. With its focus on automating IT processes, this powerful solution enables organizations to minimize downtime and enhance overall system performance.
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AIOps, or Artificial Intelligence for IT Operations, leverages big data, analytics, and machine learning technologies to enhance IT operations. AIOps utilizes machine learning to automate various IT tasks, with AI playing a crucial role in functions such as anomaly detection and event correlation.
AIOps analyzes large volumes of machine data to identify patterns, determine the cause of existing problems, and forecast and prevent future issues. Today’s data environments are complex, with data spread across:
The result? Massive and unwieldy volumes of log data and performance data can quickly overwhelm IT teams, prevent analysts from performing valuable work, and impede visibility into the network's health and safety. AIOps solutions help IT professionals resolve these issues by effectively monitoring assets and expanding visibility into dependencies, both internally as well as outside of IT systems—and all without human intervention.
In 2016, Gartner coined the term AIOps as a shortened version of "Algorithmic IT Operations." It was intended to be the next iteration of IT Operations Analytics (ITOA). Within a year or so, however, Gartner shifted the phrase to "Artificial Intelligence for IT Operations." This subtle but powerful change in the marketing of the concept highlighted that AIOps was designed to bring the speed and accuracy of AI to IT operations.
IT operations management has become increasingly challenging as networks have become larger and more complex. Traditional operations management tools and practices struggle to keep pace with the ever-growing volumes of data generated from multiple sources within complex and diverse network environments.
To combat these challenges, AIOps tools:
Now that we know what AIOps is, let's discuss how it works. Most often, you'll perform AIOps via an AIOps platform. AIOps platforms need to analyze stored data and provide real-time analytics at the point of ingestion.
According to Gartner: "An AIOps platform combines big data and machine learning functionality to support all primary IT operations functions through the scalable ingestion and analysis of the ever-increasing volume, variety, and velocity of data generated by IT. The platform enables the concurrent use of:
More specifically, they define any AIOps platform by five key characteristics:
Let's break down how AIOps works, as defined by Gartner:
Modern businesses operate using increasingly complex architectures, rapidly growing tech stacks, and numerous applications. Widespread cloud adoption and reliance on scalable IT infrastructures mean businesses face countless potential issues. From reducing alerts to auto-remediating common issues to providing real-time visibility into their tech stack, automating the process of identifying and addressing these problems is now essential.
A recent industry survey revealed that 43% of organizations currently utilize IT automation solutions. Of the businesses that aren't using them, 60% plan to implement one within the next two years. The primary draw for these enterprises is the ability to minimize the manual intervention required to maintain their IT environments running smoothly and efficiently.
Using advanced tools driven by machine learning technology helps free you from reactive and time-consuming ITSM processes. Instead, AIOps opens the door for predictive analytics and intelligent remediations. This may lead to several positive business outcomes, including:
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System performance issues can occur at any time, day or night. Nevertheless, rather than limiting your business's ability to respond based on core operating hours, AIOps can enhance system and application functionality in real-time, 24 hours a day, 7 days a week.
AIOps combines historical data with current usage trends to more accurately predict when systems require optimization. By taking a proactive approach to system maintenance, AIOps helps prevent emergencies and maintains stable operations. Enhanced performance optimization can contribute to:
System outages can damage customer and partner relationships, breach SLA agreements, and result in lost revenue, irreparably damaging the brand's reputation. AIOps helps you mitigate these risks effectively, ensuring your business continues to meet customers' needs while complying with any regulatory bodies that govern your industry.
Security threats are prevalent in modern business settings. Unfortunately, your IT teams can't be everywhere at once to prevent them. AIOps flips this script, turning manual security practices into more proactive threat-hunting approaches.
In a traditional scenario, businesses might assign a security analyst to monitor specific systems for suspicious activities. Unfortunately, the more time spent sifting through device logs or network traffic patterns, the longer it can take to address and resolve significant issues.
AIOps helps minimize this costly waiting period by identifying unusual logins or potential data breaches as they occur. Through active monitoring, AIOps solutions can:
For example, Netflix utilizes AIOps to identify anomalies in its streaming service. This improves user experience by minimizing downtime.
While you may already have various ITSM protocols in place to help support teams track and respond to issues, "alert fatigue" is a common problem in many IT settings. IT staff can quickly become desensitized to potentially critical issues when regularly bombarded with uncategorized support issues or false alarms.
Instead of relying on your IT teams to filter through every system alert, AIOps provides a much more efficient alternative. By intelligently filtering and prioritizing alerts as they occur and "before" they reach IT teams, AIOps can assist in the following areas:
Intelligently alerting IT teams of new issues isn't the only way AIOps improves business efficiency. AIOps solutions can also streamline multiple areas of incident resolution.
AIOps can automate remediation strategies based on business policies or pre-established workflows, rather than relying on human intervention. For example, when monitoring network vulnerabilities, an AIOps solution might discover that critical software systems are missing specific security patches.
Instead of waiting for an IT team to intervene, AIOps can automatically perform real-time security updates to address the issue immediately, actively strengthening system and application security.
Addressing critical business issues quickly and efficiently is essential, but knowing "why" these issues occurred is even more crucial.
Root cause analysis is crucial to creating a more resilient business infrastructure. AIOps is a highly valuable asset that can help you gain the necessary perspective to better understand all the events leading up to a significant incident. For example, in a data breach, AIOps can help gather pertinent evidence for further analysis.
Due to the computing power of AI-driven investigative tools, AIOps can leverage system logs, network traffic data, or performance metrics to locate the source of a breach quickly. Once all critical evidence has been collected, AIOps tools can deconstruct the sequence of events that led to the breach and help businesses understand the gaps to prevent it from happening again.
Moving to the cloud can keep your business agile and unlock new opportunities for scaling. Nevertheless, this added flexibility can come at a high price if you're not careful. A recent survey revealed that more than a third of businesses could waste between 21% and 50% of their cloud spending.
AIOps can help your organization better control cloud spending by regularly monitoring usage patterns and automating various cost-saving initiatives.
AIOps can also execute specific actions, such as shutting down idle instances or right-sizing virtual machines to avoid under- or overprovisioning, helping you continually improve your cloud efficiency and bottom line. By reducing the number of redundant alerts sent to cloud management teams, you're less likely to miss essential usage stats that could impact monthly cloud spending.
As your business grows larger, the more data it collects and relies on. Unfortunately, this often leads to a proliferation of disparate data sources. Over time, these information silos make it difficult to source and extract actionable insights, thereby hindering business performance improvement.
AIOps helps overcome this roadblock by enabling IT teams to have the information they need when they need it to keep operations running smoothly, delivering:
AIOps can significantly simplify IT teams' ability to visualize critical business data. Whether analyzing system performance metrics, understanding user behavior, or evaluating security logs, AIOps enables IT teams to identify key data points across multiple data sources, thereby improving business efficiency and minimizing risks.
Growing your business often comes with unforeseen challenges that can materialize in unexpected demands on your infrastructure. Rather than relying on guesswork or being overly reactive to these changes, AIOps enables you to leverage advanced analytics and predictive forecasting to better plan for capacity adjustments.
AIOps provides ongoing performance monitoring of your IT environment. It can assess your current and historical business data to identify significant or even subtle spikes in infrastructure demand. Then, it uses this information to provide highly accurate capacity predictions for the coming months or years, allowing you to plan accordingly.
Together, event correlation and event analysis offer the ability to see through an “event storm” of multiple, related warnings to the underlying cause of events and decide on how to fix it. The problem with traditional IT tools, though, is that they don’t provide insights into the issue, just a storm of warnings.
AIOps utilizes AI algorithms to group notable events based on their similarity automatically. This reduces the burden on IT teams to manage events continuously and reduces unnecessary (and annoying) event traffic and noise. AIOps then perform rule-based actions, such as:
IT service management (ITSM) is a comprehensive term encompassing everything involved in designing, building, delivering, supporting, and managing IT services within an organization. ITSM includes the policies, processes, and procedures for delivering IT services to end-users within an organization.
AIOps offers benefits to ITSM by leveraging AI to analyze data and identify issues, enabling IT departments to resolve them more quickly and efficiently. For ITSM, AIOps can be applied to data, from monitoring the IT service desk to managing devices. AIOps for ITSM can help IT departments to:
Legacy monitoring tools often require manually cobbling information together from multiple sources before it’s possible to understand, troubleshoot, and resolve incidents. AIOps offers a significant advantage through its ability to automatically collect and correlate data from multiple sources, thereby significantly increasing speed and accuracy.
The AIOps approach automates these functions across an organization’s IT operations, including:
Today, you have seemingly endless options on where your IT systems and applications live—in the cloud, on-prem, and even on the edge. The appeal of this hybrid cloud strategy is that it enables you to have all the necessary resources to ensure optimal application performance. But “always-on” is costly, and too many organizations overprovision to mitigate performance risks (and overspend in the process).
To address this waste, consider implementing FinOps (Finance + DevOps). This cloud financial management practice enables cross-functional teams, such as Engineering, Finance, and Product, to collaborate and take ownership of cloud usage. AIOps helps you operationalize this approach by using data-driven cloud spend decisions to balance cost and performance safely.
By using software—not people—you can take appropriate actions and provide applications with the resources they need to perform when needed. You’ll also build trustworthy automation for your IT teams since data backs every action. The result: reduced costs, less alert fatigue, less waste, and documented ROI for your automation efforts.
According to a study from the IBM Institute for Business Value, CEOs ranked sustainability as the top challenge, ahead of regulations, cyber risks, and technology infrastructure. There are many ways to approach this challenge. Still, the most successful CEOs are leveraging their sustainability investments to optimize operations and embrace digital transformation—a win-win scenario that combines sustainability performance with improved financial outcomes.
To meet your sustainability challenges, start by optimizing your data center. Data centers worldwide account for 1-1.5% of global electricity use. You can make an immediate impact by making data-driven decisions on application resource allocation. When applications consume only what they need to perform, you can:
The continuous integration/continuous delivery (CI/CD) pipeline is an agile DevOps workflow that focuses on delivering software frequently and reliably. It enables DevOps teams to write code, integrate it, run tests, deliver releases, and deploy changes to the software collaboratively and in real-time. A key characteristic of the CI/CD pipeline is the use of automation to ensure code quality.
As you consider ways to improve your IT systems, employing observability to create a high-performing CI/CD pipeline is an excellent use case for AIOps. Observability, powered by AI and automation, replaces older, more manually intensive performance monitoring tools. You gain full-stack visibility to better understand your environment and speed up innovation.
You’ll also have automatic discovery, monitoring, and validation of the performance and integrity of applications in production, including your:
All reporting on metrics such as usage, availability, and response times.
Organizations continually seek to enhance the resilience of their end-to-end IT systems to mitigate risks associated with system failures, outages, and downtime. By applying this AIOps use case, you can strengthen end-to-end IT resilience and ensure uninterrupted service availability.
By leveraging real-time root cause analysis capabilities powered by AI and intelligent automation, AIOps enables ITOps teams to swiftly identify the underlying causes of incidents and take immediate action to reduce both mean time to detect (MTTD) and mean time to resolve (MTTR) incidents.
AIOps platform solutions consolidate data from multiple sources and correlate events into incidents, granting clear visibility into the entire IT environment through dynamic infrastructure visualizations, integrated AI capabilities, and suggested remediation actions.
Using predictive IT management, your IT teams can leverage AI and machine learning algorithms to automate IT and network operations, resolving incidents swiftly and efficiently, proactively preventing issues before they occur.
We’ve all been there—just when you’ve mastered one business tool, another comes along. 53% of organizations say their IT teams need to spend even more time managing technologies and infrastructure. This IT tool sprawl—characterized by the proliferation of multiple tools and applications across the IT environment—leads to increased:
For a more agile and streamlined incident management process and a better employee experience, the use case for AIOps tools is compelling. An AIOps platform provides a holistic view of your IT operations, enabling you to consolidate various IT tools into a centralized solution—a central pane of glass for monitoring and management.
Leveraging AI and automation, an AIOps platform aggregates, correlates, and analyzes vast amounts of data from various sources. It can also trigger notifications, alerts, and remediation actions, eliminating the need for cross-disciplinary emergency meetings.
Past experiences, current usage, and user feedback provide valuable data to help prevent issues similar to those in the past, which is crucial for continuous improvement. AIOps leverages this knowledge to continually become smarter and deliver tailored correlations, insights, and recommendations.
AIOPs have gained traction in various industries due to their ability to streamline and improve operational processes. Let's take a look at some examples of how AIOps is being applied in different sectors:
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