AIOps- Right step in the direction of Digital Transformation

Today’s world of ever-increasing and fast-changing IT landscape is resulting in massive volumes of infrastructure and application systems data and an equally wide variety of data being generated by monitoring tools.

Figure 1: Impact of Covid on IT Function

Given all these challenges, it will be almost impossible for IT Operations to manage the IT landscape by manual siloed processes. Therefore, AIOps is emerging as the solution to not only ensure an ‘Always On’ technology environment, but also enhance ‘User Experience’.

AIOps and its evolution

AIOps, a term coined by Gartner, “combines big data and machine learning functionality to support all primary IT operations functions through the 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 can enhance a broad range of IT operations processes and tasks, including performance analysis, anomaly detection, event correlation and analysis, IT service management, and automation.

As shown in Figure 2, IT Operations have evolved from multiple dashboards, siloed across various applications, infrastructure, network, database, middleware etc., to an AI-assisted single dashboard across various infrastructure and application components, enabling data analytics, root cause analysis and remediation both in real-time at the point of data ingestion as well as historical data. Using AIOps, organizations are able to achieve a reduction in noise, improvement in alert correlation, reduction in manual task, faster MTTR (Mean Time to Repair), and better root cause analysis through various use cases as defined below:

• Root Cause Analysis – Infrastructure teams are flooded with alerts, and yet there is only a handful that matters. AIOps can mine these alerts, use inference models to group them, and identify upstream root cause issues that are at the core of the problem.
• Anomaly/Threat Detection – AIOps can mine data using machine learning-based algorithms to detect any anomalies and threats. Especially when these threats are complex, multi-vector and layered, machine learning can expose patterns that can undermine business service availability.
• Auto Remediation – Traditionally, ITSM teams have to sift through voluminous data to identify and remediate incidents at the root cause. AIOps draws root cause inferences from various alerts and drives closed loop remediation without any human intervention.
• Capacity Optimization – Predictive and Proactive capacity planning through the use of statistical analysis or AI-based analytics to optimize application availability and workload across infrastructure. These analytics can proactively monitor raw utilization, bandwidth, CPU, memory and much more, to help increase overall application uptime.

Organizations will reap the benefits of adopting AIOps on various fronts:

• Improved Visibility – AIOps solutions help centralize data from a wide array of monitoring systems into a single application, providing managers with a better view.
• Cost Reduction – Save time and support costs while freeing agents to focus on higher-priority tasks.
• Increased IT effectiveness – AIOps enables better IT decision-making, resulting in increased productivity and more strategic business decisions.
• Data-driven decision making – Machine learning is based on algorithms that can learn from data without relying on rules-based programming. AIOps brings key ML techniques to your IT operations including pattern matching, predictive analysis, proactive planning, historical data analysis and causal analysis.
• Cyber Security – AIOps can align with the cybersecurity requirements of organizations where threat detection and data security are key. AIOps, through its intelligent algorithms can detect communication requests and their source to restrict the fraudulent entities from entering the organizations perimeter.

ARGES GLOBAL can help you in your AIOps journey
As an Intelligent Process Automation (IPA) company, ARGES GLOBAL has been helping clients embark on their Automation journey. We have been partnering with clients to help them in their end-to-end automation initiatives using AIOps, AI, ML, RPA, NLG, and Smart Workflows as the key technologies.

Figure 4: ARGES GLOBAL-  AIOps Go To Market

Using an agile and iterative approach to confirm design, validate tasks and agree on deliverables, the technology stack is integrated with the redefined and updated process and Deployed. The final phase is to Drive the change –  mentoring leaders and users, upskilling users, building new habits and institutionalizing new ways of working. Using this framework, we have helped clients at different stages of their AIOps journey. Given below are two examples of past client engagements.

For a Public Services Travel industry client, tracking the assets to ensure that they are loaded at the right time onto the right containers and vessels is key.

The scope of the engagement was to conduct an IT Operations study for two key systems that are used for managing and tracking the assets. Using the ARGES GLOBAL IT Operations Optimization Framework, the objective was to realize the following results:

• Quick identification of technical problems and improve resolution time
• End to end monitoring of systems using a single tool
• Predictive analysis and correlation of system logs

The proposed solution recommended remodeling the monitoring tools along with implementation of advanced unified monitoring system and custom development to achieve the desired results in a phased approach.

For a large manufacturer, managing rejections and reducing shipment delays needed to be addressed from both costs and brand perspectives.

The scope of the engagement was to identify the root cause of the various types of rejections using AIOps to analyze large pools of data generated by machines (PLC / SCADA). Anomaly detection and variance analysis of critical electro-mechanical parameters were used to proactively address issues and raise alerts in a timely manner to do the following:

• Reduce rejection rate for finished goods
• Ensure timely shipments of orders to customers
• Improved utilization of machines

The proposed solution was built using ARGES GLOBAL’s IPA framework using AIOps for Industry 4.0 to enable predictive and preventive maintenance for efficient manufacturing.

Reach out to us at info@argesglobal.com to know more about our AIOps Services and explore how you can make your IT Operations more proactive and efficient.