Organizations around the world are turning to technology to revolutionize their businesses. They're doing this by providing intuitive and interactive on-demand services on a broad range of devices to millions of consumers around the world, 24 hours a day. This requires a rethinking of the entire IT stack and operations strategy.
In their 2019 report, Gartner lists several revolutionized technologies and delves into how those tools and solutions will challenge IT organizations from an operations and management standpoint.
Though the underlying application and service delivery stack has gone through massive transformation with virtualization, the cloud, microservices, containers and more, even today, the primary IT operations tools organizations use are relatively old.
Critical IT operations activities, such as migration, upgrades, patch management, capacity planning, service and change management are becoming extremely challenging due to the volume and varieties of data that exist across the IT stack. These IT complexities have exponentially gone up. Mean time to resolve (MTTR) and service-level agreement (SLA) requirements of business-critical services are achieved by increasing headcounts and over-provisioning infrastructure resources, thus increasing the total cost of ownership (TCO) of applications and operations dramatically.
CIOs and VPs of IT operations are looking for innovative ways to deliver business SLAs while keeping costs down. Cost reduction, as well as being competitive in the marketplace, are two key strategic objectives that every CIO knows well.
What Does A Unified AIOps And Automation Solution Look Like?
Artificial intelligence for IT operations (AIOps), combined with automation, provides IT with a complete solution that can automate critical IT operational tasks.
According to Gartner, "AIOps platforms combine big data and machine learning functionalities to support all primary IT operations functions through scalable ingestion and analysis of the ever-increasing volume, variety and velocity of data generated by IT. The platform enables the concurrent use of multiple data sources, data collection methods and analytical and presentation technologies.”
AIOps solutions collect data from structured, semistructured and unstructured data sources across hybrid IT, with its highly scalable data ingestion and discovery capabilities, and apply various rules, policies and machine learning-driven techniques across data pipeline to deliver powerful insights. Using time-series event correlation, pattern detection algorithms and multi-domain correlation and topology data, AIOps solutions identify the root cause of incidents much faster. Event clustering algorithms helps with noise reduction and the prediction of future events.
By deploying AIOps, enterprises can get a handle on massively growing operational data, reduce alert fatigue and reduce the average time it takes them to identify root causes of business-impacting incidents. It helps enterprises speed up technology and digital transformation and deliver innovative products and services faster. AIOps helps enterprises expedite workload migration to the cloud, gain visibility into cloud resources and glean insights into resource utilization. It also helps them right-size for specific application workloads and optimize cloud subscriptions for higher return on investment (ROI). Additionally, AIOps helps enterprises respond to seasonality-driven workload demands, security threats and compliance requirements.
Automation solutions, with model-driven workflow designs, analytics-driven execution framework and closed-loop automation, help businesses automate repeating IT tasks to optimize labor investment, increase service availability and reduce operational costs.
What Use Cases Does It Enable For Your Business?
AIOps integrated with automation platforms enables four categories of business and operations use cases. Let's dig a bit further into each:
1. Reactive
These scenarios include active business-impacting incidents that require prompt resolution to minimize impact. Network bandwidth congestion or having a network link down can prohibit customers from placing new service orders. An AIOps platform can quickly determine the root cause and notify the automation platform to add more capacity or bring back the network link to restore service health.
2. Predictive
Predictive analytics can foresee future events with a high degree of probability. They can predict a service outage or an infrastructure capacity exhaustion, such as disk volume or network bandwidth. An AIOps platform provides predictive recommendations to an automation platform to minimize or eliminate business impacts.
3. Anomaly
These scenarios, most of the time, impact business operations that require proper planning and remediation in a timely manner. Season-driven business anomalies, such as Black Friday, peak business hours and promotional events, generate higher traffic and resource consumption, requiring dynamic scaling of underlying infrastructure resources. Unplanned anomaly use cases include security threats that trigger abnormal behavior in application and infrastructure usage. AIOps platforms detect such anomaly scenarios and recommend actions for the automation platform that can keep your business services safe and healthy.
4. Prescriptive
Prescriptive recommendations cover use cases relating to resource optimization, compliance, changes management, etc. An AIOps platform can provide resource optimization recommendations to the automation platform based on usage analytics for over-provisioned and underutilized scenarios — all to adjust capacity allocation.
How To Decide If AIOps Is For You
AIOps may not suit every IT organization, especially smaller and confined IT organizations with less fragmentation. If these organizations have centralized toolsets doing jobs effectively and meeting business SLAs with low cost and overhead, investment in an AIOps solution may not be justifiable.
When it comes to adopting AIOps in your organization, your IT teams may become frustrated by the loss of control and change posed by the new system. They may not trust your new platform. Furthermore, if you operate your AIOps platform with unreliable data or with employees who are unskilled when it comes to artificial intelligence and machine learning, you may have a problem.
Implementing AIOps In Your Business
Enterprises can jumpstart their AIOps adoption by first getting cross-silo buy-in on AIOps concepts and values. They can identify operational pain points and use cases, experimenting with different solutions to decide whether they should buy or build their solution. If they do decide to buy, when selecting a vendor, it's important to look beyond IT to make sure that solution solves your business use cases.
A unified AIOps and automation platform can offer an emerging solution for enterprise IT stakeholders to achieve their digital transformation objectives, ensure customer satisfaction and increase their revenue growth. The only question remaining is as follows: Is this the right solution for your organization?
