On October 5, 2021, Facebook suffered a global outage that lasted for almost 6 hours. Instagram, WhatsApp Messenger, Facebook Workspace, and Messenger also stopped functioning. The Vice President of Infrastructure at Facebook, Santosh Janardhan, stated that this outage was not due to any cybercrime but specific configuration changes. According to Janardhan, these changes were on the backbone routers, and the outage occurred due to a command issued during a routine check of Facebook’s “global backbone.” IT Automation with AI has the potential to reduce such errors by cutting down on manual processes like these routine maintenance services. Automating these services can reduce downtime and help to make the entire system more efficient.

Understanding why Predictive AIOps can assist in Minimizing Outages

Therefore, it is essential to invest in the proper management of IT operations. Practical management tools and software applications can help to prevent or at the very least minimize the risk of an outage. However, for that to happen, IT departments need to catch up with the advancements quickly. AIOps is one such technological advancement that applies machine learning to predict possible outcomes of specific operations. So, when a company like Facebook invests in AIOps, they can figure out the aspects that require monitoring and optimization. For ages, people have been using manual methods to test various functions that cannot compete with the speed of AIOps automation. Artificial Intelligence for IT Operations will help operators gain valuable data on current and historical events within a concise time window. Operations teams and IT professionals can then compare the data to establish trends in the operations. By using predictive AIOps, IT professionals will be able to understand why the anomalies have been occurring. If Facebook begins the widespread use of AIOps, operations teams will quickly identify the anomalies before they even become events that can adversely impact the system. It will help to prevent outages of any scale.

AIOps can predict anomalies by using machine learning to assess the available data accurately. The operations team or an IT professional can use that data to check the root cause of the anomaly and then prevent an outage from affecting all services. Predictive AIOps can automate remediation workflows once it has enough historical data. AIOps uses natural language processing (NLP) and knowledge mining to process such data and enable automation.

Improving the Condition of Complex IT Infrastructure with Predictive AIOps

IT operations in large companies like Facebook are pretty complex, and therefore, downtime can increase, especially if there is a lack of proper management. The current IT infrastructure is hybrid, disparate, and has multiple layers. To handle complex operations, it is essential to use IT Infrastructure Managed Services. These AIOps services will not be replacing the existing tools but will be optimizing them.

AIOps assists the IT environment in the following ways:

• Improving Existing IT Infrastructure
  AIOps enables the augmentation of the existing IT infrastructure. It helps to bring together all disparate systems and ensure continuous data flow.
• Automation of Data Flow in the IT Environment
  Operations teams can check the data flow and make sense of the functions. AIOps essentially helps to simplify IT management, streamline all processes, and improve the IT environment.

Once the implementation of AIOps is complete, there will be fewer anomalies, and thus, the possibility of an outage happening again will be low.

AIOps tools can assist in improving the visibility of IT systems. A digital application like Facebook deals with a massive volume of data daily. While processing this volume of data, some alerts may come through. However, only a few will need any actions further than analysis. But manual processing and analysis of data can be time-consuming and increase the risk of anomalies. AIOps can sift through the available data and provide real-time insights. Professionals will find it easier to understand which data is relevant and which commands need not be released.

Apart from automating big data analytics, companies can also benefit from AIOps digital transformation solutions, AI machine learning functionality, and visualization solutions. These help to monitor how the system is performing. If the visibility is low, AIOps will help to expose the reason behind it so that IT professionals can rectify the issue. Most companies already use Network Performance Monitoring and Diagnostics (NPMD) tools and Application Performance Monitoring (APM). If they can introduce AIOps, it will be easier to ensure optimized performance and help in correlating events and the available data.

To launch AIOps, companies need to keep in mind the following points:

• Understanding AIOps Solutions
  All employees should become well-versed in AI and machine learning processes. This knowledge should be provided by the team leaders so that other employees get the motivation to educate themselves.
• Constant Testing at the Initial Stage
  Before applying AIOps on the entire IT infrastructure, Facebook and all other companies should run multiple tests. These test cases will determine if the AIOps approach is working and its impact on the system.
• Providing AIOps Knowledge to All Employees
  Once AIOps is introduced, team leaders must encourage and help other team members to learn more about the new tools. Eventually, AIOps implementation will become more consistent and can be used in every aspect.
• Standardization of AIOps
  To standardize the implementation of AIOps, companies will have to consider all variables and visualize the usage of advanced tools.

Conclusion

The best AIOps platforms provide enough room for experimentation. Companies can start with open-source platforms to understand how the system benefits from AIOps and then move on to more complex AIOps software solutions. Global IT solutions and service providers like GAVS Technologies offer AIOps platforms. Companies can use such platforms for digital transformation and IT automation. Combining predictive AIOps with digital transformation solutions can help companies avoid any IT infrastructure anomalies resulting in widespread outages.