Digital content consumption has never been higher. As new ways of consuming content are developed, it has given rise to increased competition and market volatility. In the face of these developments, the media and entertainment industry are forced to relook at its IT operations and service availability.

The COVID pandemic opened new doors where first-run movies were being launched on OTT platforms. Regular monitoring of IT infrastructure is a must for the media and entertainment industry. If the digital infrastructure of a media company fails, it may not broadcast content to its users. AIOps (Artificial Intelligence for IT Operations) has proved to be a vital solution for the media and entertainment industry.

Use of AIOps for media and entertainment industry

1. Discovery of data

Data is very important for the media and entertainment industry and, they need to collect it. An AIOps based analytical platform will easily discover data related to your services and business applications. You can collect system logs, data regarding KPIs, event data, and a lot more with an AIOps based analytics platform. However, at the start, you will have to provide training models to an AIOps based analytics platform as it will work as fuel.

You can have access to structured and unstructured data in one place. You don’t have to put manual efforts into collecting data as an AIOps platform will do it for you. The data discovery process can be easily automated with the best AIOps tools and products available in the market.

2. Event correlation

The ‘media and entertainment’ industry is dependent on its IT infrastructure for broadcasting content. Many events occur within the IT infrastructure and are related to each other. Businesses need to identify which events are of more importance than others. Besides events, businesses also must correlate incidents within the IT infrastructure. The need for alert, incident, and event correlation is due to the following reasons:

• The monitoring tools may produce many alerts for incidents within the IT framework. To prioritize these alerts, event correlation is performed. A business cannot afford to miss out on critical alerts that can downgrade service reliability.
• Multiple tickets may be generated by monitoring tools for the same IT incident. To identify the redundant incidents, event correlation is needed.
• Real-time user monitoring tools can help you in determining the relations between different events. An IT incident may force another incident.
• With event correlation, you can group incidents into different categories. For example, you can group incidents within the network layer and incidents within the business websites separately.

3. Advanced analytics

Once you have provided enough training data to your AIOps based analytics platform, it will provide you with high-end analytics. With advanced analytics, you can quickly determine the root cause of an IT incident. An AI automated root cause analysis solution will significantly reduce the MTTD (Mean Time to Discover). AI has already proved useful for finding patterns and relationships between data entities with ease. The high-end analytics provided by AIOps platforms cannot be produced with manual efforts. How the AIOps platform will help you in improving the performance metrics for the media and entertainment industry is as follows:

• An AIOps based analytics platform will provide event data in real-time. Since you will be identifying incidents in real-time, you can improve your MTTD.
• AI automated root cause analysis solutions perform faster event correlations to discover the source of an IT incident. When your IT teams are aware of the root cause of an IT incident, they can fix it quickly thus, improving the organization’s MTTR (Mean Time to Repair).
• With low MTTD and MTTR, you can improve the uptime of your business applications. When unnecessary system outages don’t occur, you boost your service availability and reliability.

4. Self-learning

An AIOps based analytics platform will learn as it works for your organization. It supports all three types of learning that are supervised, unsupervised, and reinforced learning. The media and entertainment industry must focus on providing engaging content to viewers and often neglect the monitoring process. Real-time user monitoring tools will not only automate IT processes but also recognize events and IT incidents. If an IT incident occurs more than once, an AIOps based analytics platform will recognize it.

5. Actionable insights

Suppose that a sports broadcasting channel is down, and an IT expert is not present on the spot to solve the issue. In such a case, AIOps platforms can be helpful as they provide actionable insights. The basic steps for solving the IT issue will be listed by an AIOps based analytics platform. For incidents occurring more than once, AIOps platforms will remember how it was solved previously.

Another reason for using AIOps in the media and entertainment industry is that it reduces the MTTA (Mean Time to Acknowledge). There may be numerous IT teams in your organization and, you need to know which one is responsible for fixing a particular incident. An AIOps based analytics platform will inform you about which team is most suited to solve any IT incident.

How AIOps can aid in providing a personalized experience to customers?

With an AIOps based analytics platform, you can get to know about customer data. You can analyze the customer data to determine user preferences and then broadcast content accordingly. You can also monitor customer experience on your business applications and websites with AIOps. An AIOps based analytics platform can also perform synthetic monitoring and can resolve incidents proactively. With an improved digital experience and preferred content, you can provide a personalized experience to your customers.

In a nutshell

Giants in the entertainment industry like Netflix and TikTok are already using AI for enhancing their recommendations system. With an AIOps platform, you can fully adopt AI for your organization and boost service availability. Start using AIOps for better observability into software systems!