Best Practices to Succeed in AIOps Strategy

Best Practices to Succeed in AIOps Strategy

AIOps is an essential part of successful digital transformation initiatives. Software operators need to focus on two key challenges. One of these is collecting a vast amount of data. The other is being agile and proactive. AIOps practices focus on overcoming these challenges.

Four Best Practices of AIOps

Proper implementation of AIOps helps to overcome challenges. It also simplifies the adoption process. Here are four best practices of successful AIOps strategy:

1.      Manage Data

Tagging data while being ingested into the platform is the best way to manage data. Operators continuously input data like metrics, logs, inventory, topology, etc., to get value from it. Tagging makes the process of browsing, searching, and visualization easier than before. To get the best result, always make sure to tag data at the time of ingestion. Doing it at a later stage will not be much helpful.

2.      Secure Data

Operators need to use a secure connector to transfer data into an analytical platform. It requires ensuring the security of the data outside the in-transit process. They can use methods like dm-crypt that encrypts the data. To secure personal data, they can use the pseudonymization technique. Securing personal data is essential as it includes IP addresses. Cookies, etc.

3.      Leverage APIs

Another best practice is to automate the process of integration. Manually doing integration is both time-consuming and expensive. Leveraging API enables the user to configure and manage the applications. AIOps is very useful in remediation and proactive actions. With API, it provides flexible, open, and well-organized solutions.

4.      Hierarchy of Services and Proactive Analysis

Operators need to build a hierarchy of smaller components. It helps to find issues in a hybrid environment. The users also enjoy benefits like the automatic discovery of services, mappings, and the supporting infrastructure. AIOps also helps to process big data. It uses ML to detect issues in metrics. It predicts demand. Operators can proactively solve issues like lack of resources and prevent potential loss in revenues.

Implementing AIOps helps in performing analytics. It is a proven method. Best practices of AIOps helps operators to focus on their core work to provide the best IT solutions.