What is AIOps and VirtualWisdom

Garter defines AIOps as a multi-layered technology platform that automates and enhances IT operations by using analytics and machine learning to analyze big data collected from various IT operations tools and devices to automatically spot and react to issues in real-time.

Today's enterprises have fully embraced the modern hybrid data center, but its overwhelming scale and complexity have led IT operations teams to reevaluate their approach to infrastructure management. Enterprises must now make a wide range of considerations in the ongoing management of their hybrid IT infrastructure, including evaluating their best execution venue, as well as the efficacy of automation technologies based on AI and machine learning.

In this Q&A, Virtual Instruments' chief technology officer, John Gentry, discusses the increasing role AIOps plays in enterprises' hybrid IT infrastructure management strategies, and why an application-centric approach is the best way to extract maximum value from AIOps solutions and practices. 

What are the key elements of AIOps?

Gentry: An abbreviation of "artificial intelligence for IT operations, "AIOps' premise is to give enterprises' IT management teams a view into how IT is supporting the business. AIOps is described by Gartner as having two main components at its heart – big data and machine learning – which are supported by monitoring, service desk and automation capabilities to give continuous insight into enterprises' hybrid IT infrastructure. AIOps' key elements include data ingestion, correlation, visualization, AI-based machine learning, and applying algorithms and other advanced mathematics to drive data analysis and automation. 

What is the value of AIOps to the enterprise?

Gentry: True AIOps offers significant value to the enterprise, including providing a real-time, end-to-end view of how a business' critical applications are performing and how the underlying IT infrastructure supporting them can be optimized. AIOps provides a basis for both reactive and proactive problem identification and resolution, so enterprises' DevOps and IT operations teams can spend less time "firefighting" issues associated with infrastructure and applications.

Most large enterprises are using a plethora of narrow IT infrastructure management and monitoring tools that are siloed and vendor-specific. The major issue is that these fragmented tools don't have a shared context of the applications, don't share information with each other, and can't provide end-to-end visibility across the infrastructure needed to solve issues. By AIOps enabling application and operations teams to proactively predict and resolve problems before they occur, not only is costly downtime avoided, but the resulting data is fed into the AIOps solution's machine-learning powered engine so it can better anticipate problems in the future.

What is the importance of application-centricity in effectively utilizing AIOps?

Gentry: Application-centricity is a fundamental capability for an AIOps platform to provide insights that are meaningful to the business. To derive the full value of true AIOps, IT application and operations teams need to gain a comprehensive understanding of the performance, availability, capacity, and efficiency of hybrid IT infrastructure within the context of the applications it's supporting. This application-centric approach provides a contextual, end-to-end view of where the application lives at any given time, its business priority (and SLA tier), and how it is stressing or could stress the infrastructure. 

Once this end-to-end visibility is established, the AIOps solution can then apply AI-based analytics including machine learning, statistical analysis, heuristics, and expert systems, which enable the enterprise to ensure the performance and availability of the mission-critical applications across their highly complex hybrid environments. The app-centric approach also enables DevOps and IT operations teams to execute actions such as workload balancing and capacity management, which helps the enterprise further proactively identify and resolve infrastructure-related performance, capacity and utilization issues that are impacting business-critical applications. 

As an example, a true AIOps approach would learn how "normal" application behavior utilizes the infrastructure and how workloads are balanced across the public cloud and the on-premises servers, networks and storage arrays. Then, when a change in application behavior creates an imbalance that negatively impacts performance, the application of AIOps can automate the workload rebalancing.

Since a key part of AIOps is enabling automation, how close are we to true autonomous operations? How can we get there?

Gentry: The constant improvements to AI and machine learning technologies make them increasingly valuable to IT and operations teams. In the coming years, these smart technologies will move beyond simply interpreting data and recommending next steps, and will evolve to enable proactive automation with 'self-healing' orchestration-. To get there, it will require an authentic implementation of AIOps with real-time monitoring systems that can autonomously and continuously make decisions that lead to better business outcomes. 

What are the notable new features in the latest version of VirtualWisdom?

Gentry: By taking an app-centric infrastructure monitoring approach augmented with AIOps capabilities, the latest version of VirtualWisdom enables enterprises to proactively gain full control over the performance, availability, capacity, and efficiency of the infrastructure supporting mission-critical applications across their hybrid data centers.

In addition to an expanded WisdomAI engine (which delivers AI-based analytics including machine learning, statistical analysis, heuristics, and expert systems), notable new features in the latest version of VirtualWisdom include:

• Workload RightSizer, which enables customers to right-size VMs by scaling them up or down across an entire cluster or application, helping assure service delivery and business value 
• Workload Drift Analyzer, which determines when anomalous changes in application workload behavior are the cause behind observed performance issues. It also delivers real-time alerts to help IT operations managers proactively rebalance the workloads.
   

How does VirtualWisdom help enterprises achieve their AIOps initiatives?

Gentry: By taking an application-centric approach to hybrid IT infrastructure management, VirtualWisdom gives IT application and operations team the context and visibility they need to understand how the infrastructure is supporting mission-critical applications. Armed with this invaluable context and insight, enterprises can properly allocate resources across their environments, which helps avoid business-impacting outages and slowdowns. Meanwhile, by applying real-time, AI-based analytics, VirtualWisdom helps ensure the performance and availability of mission-critical applications across enterprises' highly complex hybrid environments.

Taken together, VirtualWisdom's app-centric approach and deep analytics enable enterprises to implement a superior AIOps approach to hybrid IT infrastructure management.

Do you have examples of any notable customer use cases highlighting VirtualWisdom's AIOps capabilities? 

Gentry: Virtual Instruments has worked with many companies to implement our new generation of AIOps capabilities. One such customer is RealPage, the leading SaaS provider in the real estate industry. RealPage uses VirtualWisdom, in combination with the AppDynamics APM platform, to provide an integrated, end-to-end view of how applications and infrastructure are performing together. The combination optimizes the performance, availability, and utilization of their critical analytics offerings that help their customers improve operating performance and increase returns on invested capital.

How do you see AIOps evolving, and how is Virtual Instruments aligning its product strategy to support the growing adoption of AIOps? 

Gentry: AIOps has proven that it can harness predictive analytics to help enterprises proactively ensure the performance and health of their hybrid infrastructures, and its next major milestone will be enabling increasing levels of automation. To help AIOps evolve into a tried-and-true industry enabling technology, we are working with our enterprise customers to understand how they can most effectively implement next-generation technologies like AI and ML to manage their complex hybrid environments – and the insights we gain from our customers inform our product roadmap. In addition, we believe the widespread adoption of AIOps depends on an ecosystem-centric approach, which is why we are partnering with companies like AppDynamics, ServiceNow, Dell EMC, VMware, and Cisco. Ultimately, Virtual Instruments' mission is to help enterprises realize the true power of AIOps so they can continue to deliver stellar experiences and services to their customers.

About John Gentry

John Gentry is an information technology professional with more than two decades of experience in product marketing, sales, and engineering. He's currently the Chief Technology Officer at Virtual Instruments, where he's responsible for keeping up with and understanding key IT industry trends that affect product strategy and strategic alliances. John was named one of eight global leaders inducted into the Information Age Data 50 and has held various positions at mid-sized systems integrators, start-up collocations, managed service providers and established storage networking companies.