In the current technologically competitive space, more organizations are shifting towards new-age technologies like AI and ML to gain an edge over others. Automation is used for different business processes like customer support, order tracking, and many others. The IT infrastructure is important for a business as it plays a crucial role in revenue generation. Monitoring of business applications and other components of IT infrastructure is a must for any business.
The need to manage complex organizations data
Gone are the days when a few analysts could analyze the data produced by an organization. Nowadays, businesses are producing large amounts of data that need to be managed. It is not possible for analysts to manually analyze large volumes of organizational data. Also, the data is diverse and complex as it contains system logs, user data, alert data, any other types of data. AIOps (Artificial Intelligence for IT Operations) is being used by businesses to manage this complex organizational data. Unlike traditional monitoring tools, AIOps based analytics platform provides high data discoverability. An AIOps platform will not need manual efforts for collecting and analyzing data. It will always collect data from software systems and business applications. The need to manage complex data was one of the main reasons for the creation of AIOps platforms.
Benefits of automating monitoring processes
As stated above, the need to manage the complex organizational data led to the demand for automation in monitoring. However, organizations opt for automation in monitoring due to its various benefits:
1. Cost optimization
Automation is not seen as an expense by organizations nowadays. Instead, they view it as an investment that can help in the long run. If the demand for system monitoring increases, businesses must spend funds on the training and onboarding of in-house system administrators. If a business uses AI for application monitoring, it can slash the training and onboarding costs. You don’t need to hire more IT professionals for fixing incidents within your IT framework. An AIOps based analytics platform will provide actionable insights for solving an incident and, you could do well with a small team.
The best AIOps products and tools in the market can predict exhaustive capacity. Since you will be taking proactive steps in repairing and management of your software systems, you will slash maintenance costs.
2. Reduced manual labor
You can decide the degree of manual involvement while using an AIOps based analytics platform. With automation and root cause analysis in monitoring, your IT teams will not spend hours looking for the root cause of an IT incident. You can dedicate your IT teams to more crucial business processes. An AI automated root cause analysis solution can detect the source of incidents within the IT framework quickly. AIOps platforms use historical data and event correlation to detect the root cause of an issue. It teams will save time on detecting the root cause of an incident and can improve their MTTD (Mean Time to Detect).
AI data analytics monitoring tools can also detect which team has the best resources to solve any particular IT incident. Your IT teams will not waste time on deciding who is best fitted to fix an IT incident. You can decrease the MTTA (Mean Time to Acknowledge) significantly for your organization. The MTTR (Mean Time to Resolve) is also reduced significantly with the aid of AI data analytics monitoring tools. Further, IT teams do not have to spend time in data discovery and event correlation. An AIOps based analytics platform can automate the data discovery and event correlation process.
3. Improved workflow
Automation in monitoring can take care of monotonous processes like the collection of system logs, user experience monitoring, synthetic monitoring, and many others. It will lead to improved workflow in your organization and, your employees will have a clear understanding of their job roles. You can dedicate your employees to important business processes that are responsible for generating revenue.
It may be tough to implement a workflow automation software architecture for your organization in starting. However, with time, you can reap the benefits of using automation for monitoring processes. When mundane IT tasks are automated, employees can focus on other business-critical activities.
4. Improved accuracy
Monitoring processes involve complex data analysis and event correlation. If your organization is using a large number of software systems, it will be difficult to reduce the alert noise. IT teams also must decide which incident alert is more important than others. All these processes are crucial and require high accuracy. A small mistake in the monitoring process can make the organization miss an IT incident.
If IT incidents are not addresses for a long time, it may result in system outages. AI for application monitoring will enhance the accuracy in finding the root cause of IT incidents and for other processes. Manual monitoring can be inconsistent at times but, automated monitoring will never be.
In a nutshell
More than 60% of businesses state that they intend to adopt an AI strategy for slashing costs in the future. You can also use an AIOps based analytics platform to automate your monitoring processes and slash operational costs.