This article is part of a longer piece on AIOps recently published on the Dynatrace Blog. To read the original in its entirety, click HERE.
AIOps will have a long-term and transformative impact on IT operations. The research firm, Gartner, predicts a significant uptick in AIOps investments over the next two years as organizations look for ways to improve IT outcomes, without breaking budgets or overworking technology staff.
The challenge? While some AIOps tools offer significant benefits over manual processes, not all of them can deliver the results organizations expect. To recognize both immediate and long-term benefits, organizations must deploy intelligent solutions that can unify management, streamline operations, and reduce overall complexity.
Here’s a look at what intelligent AIOps are, the challenges they solve and the benefits that they can deliver to the organization.
What is AIOps and what are the challenges?
Artificial intelligence operations (AIOps) is an approach to software operations that combines AI-based algorithms with data analytics to automate key tasks and suggest solutions for common IT issues, such as unexpected downtime or unauthorized data access. In practice, AI-driven solutions help reduce the burden on IT teams by allowing them to offload routine monitoring and management tasks so they can focus on mission-critical concerns.
Consider data from the recent Dynatrace 2020 Global CIO Report, which found that 86% of organizations are now using cloud-native technologies and orchestration platforms such as microservices, containers, and Kubernetes to meet growing expectations from stakeholders, customers, and employees.
Despite all the benefits of modern cloud architectures, 63% of CIOs surveyed said the complexity of these environments has surpassed human ability to manage. To tame this complexity, organizations now use an average of 10 different monitoring tools. Despite these investments, these organizations have complete visibility into just 11% of the applications and infrastructure in their environments.
AIOps solutions offer the potential to increase observability, automate processes, and enhance value at scale.
What are the benefits of AIOps tools?
In theory, implementing an AIOps solution across enterprise IT environments can improve efficiency, drive better overall business value, and improve customer success. But what does this look like in practice?
Effectively deployed, potential benefits of AIOps initiatives include:
Improved alert management
Many IT teams now suffer from “alert fatigue” as the volume, velocity, and variety of alerts increase exponentially in multicloud environments. As noted by CDO Trends, however, effective AIOps implementation can help reduce false alarms by up to 90% and reduce the impact of redundant or irrelevant notifications.
Enhanced event prioritization
Which alerts demand priority response, and which can wait? The sheer volume of data sources and potential security concerns makes this challenging for any IT team — add in multiple cloud environments and open-source resources, and effective management becomes almost impossible. AIOps solutions that use advanced algorithms based on fault-tree analysis can immediately identify the alerts that matter so teams can respond rapidly, automate more processes, and stay focused on what drives the business.
Reduced IT spend
According to our research, IT and cloud operations teams spend 44% of their time just “keeping the lights on” — ensuring tools and technologies work as expected and on-demand. By applying automated, AIOps tools, however, companies could save an average of $4.8 million each year.
Streamlined digital transformation
Digital transformation now drives business success, but only if organizations can manage the complexity of their modern environments with a common language and a single source of truth for all aspects of digital performance. Here, AIOps tools can help companies accelerate their digital transformation by consuming and analyzing the ever-increasing amount, diversity, and velocity of data in their multi-cloud environments, and applying AI analytics to streamline and automate their operations workflows.