It may be daunting at times to ensure that a globe-spanning enterprise has the necessary oversight and support. While the basics of IT monitoring and oversight have been in place for a long time, these older systems often break down due to changes in the ecosystem or a surge in IT-driven business services. When these breakdowns occur, businesses have a plethora of metrics and logs to examine, but no frameworks to analyze or act on that data. With a mountain of information to make sense of, businesses must leverage the structured metrics and analytical frameworks provided by AIOps to succeed.


AIOps will play a pivotal role in marshaling IT operations in the post-pandemic world and navigating their ever-increasing complexity to drive best-in-class digital experiences.


Wipro has partnered with AppDynamics to launch an integrated AIOps solution to leverage these mountains of data, traces, and logs within an enterprise. AppDynamics can leverage this operational data and apply it to models, application frameworks, and system baselines to provide clear context on application failures and the business impact.


With this unified view of application performance management, business monitoring, and end-user monitoring, companies can ensure business availability and a consistent user experience across their technology stack, from applications to infrastructure.


Developing a Structure

The biggest challenge in problem-solving is an unstructured problem. Event logs, metrics, and traces are three fundamental elements to start with, but to have a structured approach to an unstructured problem, businesses must dissect the problem and look at it in parts that, taken together, lead to the complete picture.


We start with the installation of the right monitoring, correlation, ITSM, and automation tools to establish a process to detect patterns. Patterns are repeating problem type(s) or behavior type(s) within the enterprise.


The next set of steps is to detect anomalies, establish a traceable root cause detection process, and establish analytics-driven responses. All of these will enable an IT team to see direct links between business transactions and IT events, logs, and metrics.


Once the traceability is established, it is much easier to establish the root cause of the problem and know what key resolution options are available. When we know what the issue is, where the issue is occurring, and what needs to be done, it becomes a question of engineering, which the automation ecosystem can remediate. After the problem is detected and correlated, it can be logged and remediated. This whole process can be done automatically, thereby reducing the effort and cost and, more importantly, enabling the company to detect and address problems proactively and swiftly.


The Business Experience Enrichment (BEE) Model

The 12-step Business Experience Enrichment model, also known as the Honey BEE model, exemplifies this process by enabling an enterprise to move from basic operations to AI-driven operations. ITSM tools, remediation tools, batch monitoring, and management tools each form part of a framework that’s simple and flexible. This begins sequentially but, based on a company’s maturity and hunger to innovate, can evolve to parallel steps.


The entire journey of detection, correlation, ITSM Integration, and remediation is covered within this execution model. By integrating them into the company’s landscape, each of these tools can build upon the holistic system. As the company discovers areas of innovation during this journey, it can add to the ROI immensely.


This system provides an easy way for companies to integrate AI into their IT operations, empowering them to focus not just on reducing technical challenges, but on innovation, automation, driving revenue growth, and improving the customer experience.


The BEE + AppDynamics Experience in Action

A large UK-based insurance provider had struggled to identify and address IT issues amid its complex web of applications. A single error could flood the system, delay remediation, and drastically impact the customer experience. Wipro and AppDynamics introduced intelligent alerting to this environment, which helped the company identify error sources, ascertain potential ripple effects, and find solutions to address it.


AIOps helped the company leverage cohort analyses to process vast amounts of data simultaneously, ultimately enabling it to predict about 30% of the routine problems with 70% accuracy, which reduced ticket volume by 20% within the first six weeks. These achievements immediately improved both the company’s operational performance and its user experience.


For modern enterprises, the overwhelming complexity of IT can no longer be solved with time and perseverance alone. With millions of daily business transactions, machines are better suited to analyzing and categorizing information. AIOps allows businesses to seamlessly monitor and control their environment to address critical use cases for application users, customers, business stakeholders, and IT teams. The future is AI; Wipro and AppDynamics are leading the charge.

Ravishankar Subramanian

Ravishankar Subramanian

Global Practice Head, AIOps, Wipro Digital


Ravi believes in harnessing the power of technology to orchestrate business results. A hands-on, tech-savvy business leader, he combines business outcomes with technical possibilities. Ravi has 23 years of industry experience and has lived and worked in 13 countries. He is fluent in English, Hindi, Tamil, Bangla and Spanish.

Madhu Kondapi

Madhu Kondapi

Solution Engineering Head, GSIs & GSPs, AppDynamics


With 15+ years' experience in Dev | Ops and Sales Engineering in world-class institutions like Cisco, Accenture & AppDynamics, Madhu is an experienced Solution Architect who’s been building teams from the ground up and managing global teams, bringing scale to solution sales in the GSI world.

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