How to Leverage AIOps Tools for Improved Digital Experience?

Introduction

Comparing today’s IT infrastructure and the conventional one makes it challenging to manage
the dynamic and instantly changing IT environment. Whether it be Microservices or
containerization, IT companies have already moved towards modernization and everyday
challenges to manage operations.

To witness great results and run the IT operations smoothly, one needs to integrate automation
into their strategies and tactics. With the ideal use of artificial intelligence and machine learning,
the AIOps platform is transforming the overall digital experience of IT organizations.

The AIOps platform provides a holistic view of overall IT operations, including servers, network
layers, incident management, to monitor the end-user devices for conquering the complexity of
IT operations. The overall improvement with the help of AIOps helps the organization in
reducing cost, improving dependability, and enhancing new innovations. To move forward with
the blog, let us first understand AIOps in detail.

Definition – AIOps (Artificial Intelligence for IT Operations)

According to Gartner – “AIOps combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.”

Gartner coined the term AIOps in 2016.

AIOps offers automation in identifying and resolving common IT issues using incredible
technologies such as big data analytics, machine learning (ML), and Artificial Intelligence (AI).
Modern IT infrastructure generates an immense volume of data and logs. AIOps allows the Ops
team to manage the data and prevent outages from getting robust uptime and attaining consistent
service delivery.

How does AIOps Work?

In this world of innovation and massive technology upgradation, we are surrounded by highly
complex systems. To conquer this problematic situation, AIOps is the solution. It helps
collaborate between teams and provides data availability for all the teams to examine and
monitor.

AIOps helps enrich the data with the combination of AI and Machine Learning. This objective is
to benefit the team to work more efficiently on data and reduce manual intervention. Reducing
the data silos and promoting a collaborative work environment encourages excellent
observability that provides the ultimate customer experience.

Apart from these, several incidents are far from human intervention and require the
organization’s attention. Therefore, AIOps leverages its focus on such incidents and resolves
them in real-time before the occurrence.

Whether that technician will fix the problem proactively or want to achieve a faster mean time to
resolution (MTTR), integrating AIOps will add some incredible benefits to your organization
and help resolve the issue faster to provide your customer with a better solution experience.

Some Amazing and Result-Driven Benefits of AIOps:
When we talk about AIOps, it comes with some incredible and result-driven benefits that help
the organization build a robust digital customer experience.
Whether improving uptime across touchpoints, identifying potential failure in the organization,

or implementing proactive remediation, AIOps provide actionable analytics by analyzing the
datasets efficiently. So, let us look at various ways in which AIOps improve IT efficiency.

• 1) Automating IT operations is a significant benefit of AIOps. By relying on machine learning and analytics, AIOps enables the automation of IT operations.
• 2) AIOps address issues in real-time and resolve them instantly to lessen mean time to resolution (MTTR) and downtime.
• 3) AIOPs reduce help desk ticket volumes by preventing the problem from occurring.
• 4) AIOps helps fully break down the data silos across all IT infrastructure. It makes data available for all the team members to analyze and monitor and promotes collaboration between team members.
• 5) AIOps helps save time and reduce operational costs with faster resolution and automated remediation.

AIOps, offer you enhanced IT support, which leads to robust digital transformation. From solid
business decision-making to accurate data-driven insights, enterprises can implement better
optimization of assets which gives you incredible results in the long run.

Things to Keep in Mind While Leveraging AIOps Tools for Improved Digital Experience

As you have decided to implement or leverage AIOps in your enterprise, you have a list of
choices, whether you leverage it through the commercial offering or choose the open-source
technologies. So, no matter which approach you choose, you always need the key factors or
verticals to implement them proficiently into your enterprise operations.
1) Create a Unified Data Repository
Your enterprise must create a comprehensive data repository that contains an extensive range of
datasets and data types. All these datasets should be standardized and correlated from topological
data, alarm metrics, and log files to configuration management databases. Without evaluating
data, no AI process could be successful. Data is an integral part of AIOPs use cases.
2) Understand the Difference Between Real-time and Non-Real-Time Analytics

Once you have created a data repository, you need to organize the data based on real-time and
non-real-time data. Real-time analytics requires a complete set of different processes compared
to non-real-time analytics. So, it is crucial to separate real-time data from non-real-time data.
This process will simplify the overall job of AIOps, and you will get more accurate results.
3) Don’t Settle for Complicated Models.
Taking a large number of factors and creating complicated models is not helpful for any
enterprise. Also, sometimes organizations dump their whole data into the machine and assume
that it will manage the data deluge. But the reality is different, and it is suggested to use simple
models and fewer factors at the initial stage. Once you receive positive outcomes, you can move
forward to add more factors and receive quality outcomes.

3 Best AIOps Platforms for Your IT Infrastructure

1) Motadata AIOps

From solving network challenges to providing you detailed insights into the cloud, Motadata
AIOps is a next-generation tool that captures and monitors your complete data through various
factors such as metrics, traffic, routing, and logs.
This tool captures your overall data, whether end-to-end visibility of your network performance,
multi-cloud/hybrid infrastructure, or monitoring and analyzing data across cloud infrastructure. It
identifies anomalies that affect your business goals.
So, get better visibility and enhanced capability with this highly advanced network monitoring
tool by Motadata.

2) Dynatrace

Whether enhancing the customer experience or getting deep insights into your full application
stack, Dynatrace monitoring tool provides a detailed analysis of how the application impacts the
customers.
It lets you get all metrics and logs in real-time and helps monitor the hybrid multi-cloud IT
infrastructure.

3) Data Dog

If you are looking for a modern infrastructure monitoring tool, then Data Dog is the tool you
should consider, whether it be cloud or hybrid environment, Data Dog’s exceptional Saas-based
infrastructure monitoring tool provides comprehensive insights for managing the IT operations
proficiently.
So, communicate and troubleshoot impactfully with the incredible Data Dog monitoring tool.

Conclusion

AIOps is the critical requirement and the need of the hour in many organizations. AIOps can
improve a lot of aspects of IT infrastructure. From reducing alarm fatigue, integration
automation remediation to preventing security breaches, leveraging AIOps will help improve
overall digital transformation.
It goes beyond technology and converts raw data into proactive decision-making, which helps
organizations take robust decisions for overall business success.
So, whether you want to drive impact in the organization or witness digital transformation,
leveraging AIOps will keep pace with the ever-increasing customer demand and give the
organization a breakthrough result.