Increasing complexities in technological systems will necessitate the use of AIOps tools to minimize dependency on human intervention in data management.
In today’s technologically charged world, the evolution of the IT ecosystem is becoming the cornerstone to digital transformation across the industrial spectrum. However, this evolution also means that IT systems are becoming vaster and more complex than before, making them significantly more challenging to manage.
A major chunk of this concern stems from the sheer volume of data being generated by these systems, with a Seagate UK study showing that the global datasphere could contain 175 zettabytes of data by 2025. In this situation, a gap in intelligent analysis and monitoring tools could lead to several adverse events, from missed opportunities and alerts to expensive and excessive downtime; an observation that is steadily shedding light on the importance of tools like AIOps in modern IT infrastructures.
Automation is the foundation of the modern Information technology ecosystem, with artificial intelligence leading the charge. Managed service providers, cloud platforms, and various other organizations are beginning to understand the impact of AI on their digital transformation and are increasingly capitalizing on this trend by embracing a crucial IT trend – Artificial Intelligence for IT operations (AIOps).
AIOps is proving to be a boon for IT organizations in numerous ways, including staving off potential outages or performance glitches before they can manifest and influence customers and operations. More recent deployments are also starting to leverage AI systems for not just identifying or forecasting issues, but to create more intelligent and automated responses to anticipated events.
AI for IT operations is still considered a relatively early initiative. According to a Loom Systems-sponsored survey conducted in 2019, only 5% of organizations had implemented AIOps. However, over the years, many enterprises are beginning to realize that AI and automation go hand in hand, and together form a crucial catalyst for digital transformation. As a result, the scope of opportunity has broadened considerably for sectors like the Artificial Intelligence for IT operations (AIOps) market, which could exceed over USD 10 billion by 2027, as per estimates from a Global Market Insights Inc. report.
How is AIOps helping organizations navigate the COVID-19-induced burst in cloud migration?
While the transition to the cloud has been in the works for a few years, IT businesses have, now more than ever, started to prioritize a more cloud-first approach to scale up their digital transformation. The novel coronavirus pandemic especially has served as a major driving force behind the massive uptick in organizational spending towards migration to the cloud. According to Flexera’s 2021 State of the Cloud Report, the number of organizations spending nearly $12 million on cloud each year grew by almost double from 16% in 2020, to 31% in 2021.
In the pre-cloud era, data monitoring and management was a relatively simple task, involving just a few dedicated data feeds that provided insights on the performance of the machines, and a team of IT professionals to supervise. However, the emergence of technologies like hybrid cloud, public cloud, private cloud, and multicloud, alongside the copious amounts of data generated from the swift transition to cloud-native, has made the IT infrastructure so complex that adapting it as per evolving digital needs has become an uphill task for companies and their IT teams.
Fortunately, the impact of the pandemic on cloud adoption also placed renewed focus on AIOps, which began to emerge as a saving grace for organizations worried about their cloud vulnerabilities. This trend has also been picked up by prominent players like Digitate, which has made targeted efforts to enhance its AIOps offerings to accommodate the evolving needs of the cloud. One of these efforts was its introduction of Dragon in January 2022, which included the addition of improved multi-cloud support functionalities across its flagship ignio AIOps suite, alongside other out-of-the-box solutions to help enterprises propel the migration of their operations to the cloud.
AI to the rescue – AIOps and its role in addressing the challenge of 360-degree visibility in IT operations
Against the backdrop of this rapid transition to the cloud, and continual efforts by organizations to fine-tune their digital transformation, the role of IT systems in the modern business environment has taken on a more strategic tone. While potentially beneficial in the long run, this exponential surge in dependence on digital technology has also unearthed several key challenges faced by IT leaders today.
For instance, with nearly every task from security to performance management involving the use of highly specialized tools in recent years, gaining a holistic, 360-degree view of the overall IT operation is becoming a major pain point for IT teams worldwide. Furthermore, the labor-intensive and time-consuming task of manually managing an evolving network infrastructure is blocking IT teams from developing proactive strategic initiatives, instead keeping them confined to a reactive approach.
In this scenario, the IT industry is gradually gravitating towards AI for IT operations as a turnkey solution. Powered by features such as pattern matching and more, AIOps platforms are able to ingest, correlate, suppress and enrich data from various sources, and bring all infrastructure and application operations under a single management portal with a dashboard view of the entire IT ecosystem. This results in a significant reduction in alert noise and mean time to detect and respond; a great boon from an operational perspective. Additionally, organizations have the tools to greatly accelerate incident resolution protocols and offer predictive and actionable insights into IT operations.
Enterprise adoption of AIOps is also driven by its proven benefits, which is corroborated by studies like a recent OpsRamp survey which revealed that 87 percent of the respondents agreed that AIOps tools improved their data-driven collaboration. Organizational leaders are also taking heed of this trend and working towards integrating technology into their operating models to facilitate more precise and comprehensive data insights.
Take for instance, HCL Technologies’ strategic partnership with Moogsoft inked in April 2021, for the delivery of the first end-to-end automated remediation solution for IT incidents, assured business continuity, and innovations in customer experiences. Through a joint solution combining the AI-powered anomaly detection and correlation functionalities of the Moogsoft Observability Cloud with the automated remediation capabilities of the DRYiCE™ iAutomate, HCL was able to observe a 33% decrease in MTTR (mean time to restore) and a 62% reduction in help desk tickets.
Essentially, AIOps is serving as a guiding force for companies looking to transition from reliance on third-party specialists and sources to a more self-automated approach to their operations. Advanced AI models for IT operations are enabling modern IT systems to learn continuously through insightful data from their surroundings, in turn improving themselves and their suggestions and becoming more adaptable to changes in the long run. With the proper AI tools, integration, and support, IT operations will benefit from an increasingly autonomic approach to computing, and eventually establish a bespoke knowledge base that will help future IT systems transcend what human effort alone can achieve over time.
About the Author
An avid reader since childhood, Saloni Walimbe is currently following her passion for content creation by penning down insightful articles relating to global industry trends, business, and trade & finance. With an MBA-Marketing qualification under her belt, she has spent two years as a content writer in the advertising field. Aside from her professional work, she is an ardent animal lover and enjoys movies, music and books in her spare time.
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