Overview of AIOps
Gartner first coined AIOps in 2017. AIOps for Telecom is a constituent of two terms: AI (Artificial Intelligence) and Ops (Operations). Operation management is cumbersome for an organization. From customer experience to anomaly detection, all require a team of experts to handle a particular department’s operation. This leads to considerable costs for an organization in terms of money and time.
The current era is data-driven, and it is generating with high velocity and veracity. Finding the pattern from this data (big data) using Analytics and Machine Learning is both cost and time-efficient. AIOps is a way of utilizing Big Data and Machine Learning to handle an organization’s operation with scale and efficiency and is entirely automated. It lets the concurrent use of data sources, data ingestion methods, real-time analytics, and presentation of infographics.
A platform solution that solvers known IT issues and intelligently automates repetitive tasks. Click to explore about, Artificial Intelligence for IT Operations
What drives AIOps?
The working of AIOps is dependent on the following:
Machine Learning (ML)
It is a way of mathematically learning the pattern from data without human intervention. Machine Learning can find patterns from big data in less time, and with the power of analytics, it suggests better actions.
Performance baselining
Identifying the threshold performance gives better criteria for analyzing the performance of an event in real time.
Anomaly detection
Real-time judgment of an unusual event prevents an organization from losses such as customer, revenue, and trust.
Automated root cause analysis
Finding the causality of an event and auto-generating information concerning the context helps in finding a better remedial solution.
Predictive insights
Prediction of future behavior based on past data and auto-training on new data makes AIOps smart, efficient, and reliable.
Integrates a huge amount of data and uses machine learning to automate the IT processes. Click to explore about, How to Integrate AIOps for DevOps?
What are the benefits of AIOps Solutions?
Improved Time Management and Prioritization
AIOps helps businesses manage vast data volumes, distinguishing key events and prioritizing critical incidents. With machine learning (ML)-driven event correlation, it quickly identifies root causes and provides actionable insights for faster resolution.
IT Spend Reduction
By automating IT processes, AIOps reduces downtime and service disruptions, leading to significant cost savings. It proactively detects issues before they escalate, streamlining routine tasks and freeing IT teams to focus on strategic initiatives.
Accelerated Innovation
With AIOps eliminating operational burdens, IT teams can focus on innovation. This shift enables businesses to adopt new technologies, enhance performance, and stay competitive in a fast-paced market.
More Collaboration
AIOps fosters cross-team collaboration by offering a unified view of events, breaking down silos, and aligning efforts with data-driven insights. This improves communication, coordination, and operational efficiency.
Automation at Scale
AIOps enables scalable automation across IT systems, allowing teams to automate processes securely and efficiently. Both system-wide and SME-driven automation can be built to enhance productivity for all teams.
Digital Transformation
As a key enabler of digital transformation, AIOps helps businesses leverage AI and automation to streamline operations, improve customer experiences, and drive innovation in a rapidly evolving digital landscape.
Key Features of an AIOps Platform
Enhanced Visibility
Captures subtle changes in infrastructure every millisecond, aiding in precise problem tracking
Holistic Monitoring
Provides a holistic solution, covering everything from real-time data ingestion to anomaly detection
How is AIOps helping the Telecom industry?
There are several ways in which AIOps is helping the telecom industry, which are listed below:
Improving Customer Experience
Telcom is a customer-centric industry. The long waits in the queue of technical support, billing disputes, updation of credentials, etc., cause a customer to switch to another carrier partner. The introduction of chatbots for solving conflicts and the use of ticket routing algorithms has exponentially decreased customer wait time and improved customer experience. These things happen in real time.
Anomaly Detection
Telecom is highly vulnerable to anomalies, such as identity theft, data breaches, fraudulent transactions, etc. AIOps for Telecom is all set for handling such defects. It is trained using advanced ML algorithms on big data, and the patterns generated by these algorithms can detect anomalies with high accuracy. The predicted anomalies are then prioritized and create a no-panic situation for the company.
Customer Segmentation
Dividing the customers into groups based on the opt services, billing information, payment type, revenue generation, etc. AIOps find such groups or clusters in real-time and give better suggestions about buying behavior and upselling capacity. Such clusters will also lead to the monetization of tailored content for the customers.
The best AIOps tools for the telecom industry
Prometheus: An open-source monitoring system fetches real-time data from HTTP metrics, and a flexible query language model makes it an excellent choice for AIOps.
AIOps Use cases
Root Cause Analysis
Automated root cause analysis is a leading AIOps application in the telecom industry. It pinpoints the underlying cause of an issue and leverages historical event data to determine the most likely reason for an incident, providing insights across various systems
Intelligent Alerting
AIOps gathers data from different IT systems and consolidates it into ‘incidents,’ preventing a surge of alerts triggered by related issues. Smart alerting reduces the number of critical alerts, allowing operators to focus on key issues that impact users and business outcomes
Cohort Analysis
Manually analyzing large datasets is challenging, especially with multiple datasets in action. In modern distributed architectures, hundreds of active datasets make it impossible for humans to spot outliers in configurations or versions of deployed applications
Automated Remediation
AIOps continuously resolves known issues through automated feedback loops. It detects problems by analyzing past incidents via root cause analysis (RCA) and then suggests the most effective and efficient methods for remediation
Conclusion
To fulfill rising expectations of modern-day customer experience, telcos need to put as much focus on customer experience as they put into other functions. But the question here is – do you carry that expertise, experience, and resource base? AIOps is a boon for every emerging telecom industry. With a decade of industry experience and having attained a credible name in the IT domain, XenonStack works as a strategic business partner for industry across telcos. Some of the top brands in the Telecom industry rely on us to look after their CX initiatives.
