Artificial Intelligence for IT Operations (AIOps) is an emerging discipline in the world of IT operations. But what is an AIOps platform? How does AIOps work? What can it do for an IT organization? And most importantly, how do you get started? This AIOps market guide reviews the definition of AIOps and the primary questions that teams may have as they learn how it can fundamentally transform their modern IT organizations.
AIOps stands for Artificial Intelligence for IT Operations. AIOps leverages a broad set of technologies, including machine learning, network science, combinatorial optimization, and other computational approaches, for solving everyday IT operational problems at scale. In simple terms, AIOps collects data from various sources and analyzes that data to give actionable insights to organizations.
Enterprises can address a wide variety of IT management activities using AIOps, including intelligent alerting, alert correlation, alert escalation, auto-remediation, root-cause analysis and capacity optimization. Traditional AIOps tools are not real-time and require manual intervention, however modern AIOps tools can be integrated with any existing platform. Modern AIOps not only analyzes data but also enables IT to make quick decisions based on actionable insights.
Top Trends In AIOps Adoption: The Future of Digital Operations Management?
“68% of IT decision-makers are piloting AIOps technologies to better manage the availability and performance of business-critical IT services”.
The AIOps market is experiencing rapid growth with explosive enterprise adoption, accelerated revenue growth and continuous investments from digital and IT operations vendors. While standalone point tools have defined and shaped the AIOps market to date, a number of adjacent AIOps vendors are either building or acquiring companies to assemble competitive AIOps portfolios.
By 2022, Gartner predicts that 40% of large enterprises will adopt AIOps solutions to cope with never-ending alerts and ensure faster recovery from disruptive IT outages.
Gartner predicts that large enterprise exclusive use of AIOps and digital experience monitoring tools to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2023.”
There are a number of AIOps vendors whose AIOps tools address a variety of use cases. Many of these must be continuously tuned and optimized for data ingestion, while others use native application, network and/or infrastructure monitoring instrumentation to provide a richer, more contextual view of service health and incident remediation workflows. Look for robust integrations and native instrumentation while selecting an AIOps provider.
Why AIOps?
AIOps solutions help IT infrastructure teams turn data (like alert streams) into actionable insights and anticipate problems while still delivering compelling end-user digital experiences. In fact, as demands on IT continue to increase, the ability to leverage AI as a service will soon be critical to successful operations. Here’s how AIOps solutions help enterprises run and optimize mission-critical systems:
Improve Response Time For Digital Interactions
Boost key metrics for incident management including mean-time-to-detection, mean-time-to-response, mean-time-to-restoration, and incident volume handled within a service window using AIOps platforms. The combination of machine learning and data science techniques in AIOps not only delivers faster incident coordination and response but also reduces the human time spent per alert with advanced analytics and probabilistic root cause analysis.
Eliminate Siloed/Redundant Processes
AIOps solutions offer the ability to consolidate event and incident insights from different IT management tools across on-prem and hybrid, public, and multi-cloud environments. A shared AIOps platform offers centralized visibility, faster impact analysis, and improved collaboration for a diverse set of stakeholders, including application owners, infrastructure teams, and business sponsors.
How Does AIOps Help?
AIOps Adoption And The Modern Enterprise
Data Ingestion and Consolidation
With greater digital infrastructure delivery in the modern enterprise, it’s only natural that ITOps teams are experiencing exponential data growth.
Actionable Insights
This rise in ITOps data volume, velocity, and variety have contributed to an increase in event noise. Modern ITOps environments are constantly generating alerts for incorrect configurations, events, and more.
Proactive Service Availability and Health
IT professionals are now drowning in ‘alert storms’ that negatively impact service availability and increase resolution time for IT outages. AIOps platforms will help navigate these alert storms and escalate mission-critical alerts to the proper teams for remediation and uptime restoration.
The OpsRamp State of AIOps Report
The Signal in the Noise: The truth on how AIOps is truly impacting business performance.
In order to understand the true impact of AIOps solutions, OpsRamp recently published “The State of AIOps” Report that is based on data from AIOps practitioners who are currently using machine learning-powered event management analysis. This survey identified can help to identify the most popular high-impact use cases for quick AIOps, including:
In order to implement AIOps, it is first important to identify the key problems that your enterprise is trying to solve.
Here are five essential steps any organization should undertake before adopting AIOps:
Define how AIOps solutions will be used
More than the “what” or “how”, it is more important to understand the “Why” of AIOps.
Set success benchmarks
There must be certain benchmarks set in place to determine whether the AIOps investment will be worthwhile and at the same time provide validation on effectiveness and accomplishment of the use case.
Segment data that matters
IT leaders need to focus on the specific data that matters to realize the full value from an AIOps investment.
Make an adaptable data collection and analysis plan
Collecting the right data requires a comprehensive, well-thought-out data aggregation plan that enables any company to become an AIOps-powered enterprise.
Setup the automation
Once you’ve identified the data, it’s time to automate as much as possible and replace the routine tasks which are normally
Rollout the solution
Finally, it’s important to build team momentum for this new approach to routine task elimination with AIOps tools.
What are the challenges to AIOps adoption?
While AIOps adoption is gaining steam, there are a few apprehensions which could prevent wider adoption. The accuracy of prediction models (54%), quality of large datasets (52%) for machine learning models and the IT talent (48%) needed for building machine learning algorithms are all key constraints for scaling AIOps solutions.
“AIOps is gearing up to become the next big thing in IT management…When the power of AI is applied to operations, it will redefine the way infrastructure is managed.”
AIOps, the convergence of AI and ITOps, will change the face of infrastructure management. This technology will impact both enterprise data center and cloud infrastructure management.
AIOps tools ingest a wide variety of data (logs, metrics, APIs, and text) to analyze historical behavior and predict future IT performance. Most enterprises today use AIOps to handle anomaly detection and root cause analysis. In the future, machine-learning powered insights will help transform IT operations and overall business performance by overcoming the complexities of the day-to-day IT management and free up room for greater enterprise innovation.
What’s driving accelerated AIOps adoption over the next five years? Two chief developments call for a new way of doing things:
Hybrid Environments
Stable and predictable data center environments have given way to dynamic infrastructures built on virtual, cloud, and software defined environments.
Emerging Workloads
AIOps adoption is also critical for new-age infrastructure workloads like containers, serverless, and smart machines, for fixing the technical debt, unleashing agility, and taking advantage of new business opportunities.
“AIOps, the convergence of AI and ITOps, will change the face of infrastructure management. This technology will impact both enterprise data center and cloud infrastructure management.”
How is OpsRamp’s service-centric AIOps solution better than the average AIOps tools?
While stand-alone AIOps tools can flag critical event patterns, OpsRamp’s service-centric AIOps solution combines data, context, and insights for end-to-end incident management. With OpsRamp’s AIOps solution, DevOps teams can handle incident workflow activities like event recognition, impact analysis, root cause identification, incident escalation, and automated remediation all in a single place.
