One of the biggest challenges for a business organization is to maintain continuity. The IT infrastructure should keep running tirelessly to complete business processes every day. However, market disruptions and economic shifts can hamper the day-to-day operations of a business. Simultaneously, businesses are facing issues in creating a robust disaster recovery plan for IT failures. To overcome these challenges, business organizations are inclining towards new-age technologies like Artificial Intelligence (AI) and Machine Learning (ML). Read on to know more about business continuity and disaster recovery planning.
How do IT disasters hamper business continuity?
At present, business organizations are depended on several software systems for their essential operations. If an IT disaster abruptly shuts down software systems in an organization, the service availability will decrease. Without critical software systems, a business cannot guarantee service availability. Without day-to-day operations, businesses cannot generate revenue or connect with customers. As a result, the business organizations will be forced to cease their operations.
Even if an IT disaster occurs, your critical business processes should be up and running. Every business focuses on service resilience to keep their critical software systems running even during an IT disaster. An hour of downtime can slash the revenue generated by a company heavily. Businesses are focusing on creating a robust disaster recovery plan that could help them enhance their service availability. When a business has the capability of getting up again after IT disasters, it can ensure business continuity even during adverse times.
Challenges with maintaining business continuity
Since avoiding IT disasters is important for maintaining business continuity, businesses need better monitoring systems. The legacy monitoring tools are not advanced enough to predict IT disasters in 2021. The challenges with traditional IT tools for monitoring and disaster recovery are as follows:
- Most of the businesses have adopted cloud technology for pacing their operations. Data on the cloud is deleted the next second and, you won’t even have a chance to create a backup. Without business data, it is impossible to know the reason for an IT incident/disaster. The traditional data collection and monitoring tools cannot handle the complexity of the cloud environment.
- Lack of real-time user monitoring toolsis forcing businesses to compromise on user data. Real-time user monitoring tools can help fix IT issues immediately as they occur.
- Businesses are not ready for sophisticated cyberattacks on the IT infrastructure. The sensitive business data needs to be protected at all costs and businesses are unable to do that with legacy tools.
- When a disaster occurs, IT teams are unable to find the root cause. IT teams spend hours and even days to find the root cause of an IT disaster. It results in a huge downtime and degradation in service availability. If a company cannot fix IT disasters quickly, it cannot achieve business continuity.
- Large organizations have many software systems that are responsible for daily operations. An organization cannot recruit system administrators for each software system as it will be too costly. Businesses need a central monitoring solution that can cover the entire IT infrastructure and connected systems. With a central monitoring solution, businesses can look after IT incidents and thus boost business continuity.
Due to these challenges, traditional disaster recovery tools do not help boost business continuity. For minimizing the disasters within the IT infrastructure, businesses are now using Artificial Intelligence for IT Operations (AIOps). AIOps based analytics platforms are helping businesses to manage modern-day IT disasters.
How AIOps help maintain business continuity?
AIOps tools use AI/ML algorithms to perform real-time analysis without the need for manual labour. AIOps based analytics platform can help you maintain business continuity in the following ways:
- AIOps based analytics platforms are helpful in event correlation and root cause analysis. AIOps-based monitoring tool will collect data from all sources including cloud and user data. The data will then be used to perform event correlation. You can learn about the relationships between different events in your IT infrastructure. With better event correlation, you can know about IT disasters in real-time.
- Every time an IT incident occurs in your organization, an AIOps based analytics platform will help in getting back up stronger. Business risks can be identified in real-time this ensuring business continuity. Many organizations adopted an AIOps strategy to cope with the challenge of remote work culture. An AIOps based analytics platform can help NOC support teams to monitor an organization’s network remotely.
- With an AIOps based analytics platform, you will have complete control over your IT infrastructure. Diverse IT environments can be merged easily with AIOps. AIOps will bring all your software systems together for better application performance monitoring. Since you will have control over the IT infrastructure, you can mould it easily to cope with future challenges.
- AI for application monitoring can predict the exhaustive capacity of your critical software systems. You can predict the downtimes in your organization with an AIOps based analytics platform. You can then take proactive steps to avoid IT disasters and maintain business continuity.
How to implement an effective disaster recovery plan with AIOps?
Once you have installed an AIOps based analytics platform in your organization, you need to provide it with sufficient training data. The AIOps based analytics platform will then collect data about IT disasters that occur within the organization. Once the analytics platform is fully trained, it will provide you with actionable insights to overcome IT disasters. With high-end analytics, root cause analysis, and actionable insights, IT teams can overcome disasters in no time.
Studies show that a business will lose 5-20 percent productivity power every time it faces downtime. AIOps-based monitoring tools can help you in decreasing downtime incidents. With high uptime and service availability, you can maintain business continuity.