What Is an AIOps Strategy, and How Do You Develop One?
Year after year, the amount of data collected on IT operations increases. According to some estimates, the average IT operations team’s operational data volume doubles or triples every year. As a result of the flood, IT teams are scrambling to find any means they can to make sense of it all. Many organizations are turning to AIOps to parse and categorize these occurrences. AIOps isn’t suitable for every company, but it’s a good fit for many. This article will discuss what AIOps is and what it promises. We’ll also create an AIOps strategy for implementation in your company.
What is the purpose of AIOps?
You’ve probably heard of the DevOps philosophy, which aims to increase velocity and quality by bringing development and operations teams together. A DevOps team’s mission is to deliver better software faster. That’s fantastic! However, there is a price to pay. As previously said, operations events are growing at a rapid rate. More releases for more apps running on more servers result in an ever-increasing amount of data about your applications, services, and servers.
Because of the increasing complexities of IT systems, the explosive rise of data, and the abrupt increase in remote working arrangements, the demand for AIOps has increased.
Do you have an AIOps strategy in place?
Seek for an AIOps technology to run automated procedures using analytics from your data pools. This information is frequently stored in your organization’s monitoring solutions. Then, inquire about the platform’s dynamic thresholds, root cause analysis, forecasting, and anomaly detection features.
How can you get started with AIOps if your company is considering it? What are some of the methods to consider?
You must have a thorough awareness of what you must monitor and store. The monitoring technique becomes more sophisticated as the number of AI models increases. Then you must establish the acceptable performance requirements for a model or a group of models. Finally, a mechanism for retriggering training when performance falls below a reasonable level is required.
Every AIOps strategy, as previously said, must answer at least three questions. It’s the same with your AIOps plan. Fortunately, because we’ve limited the scope of this AI engagement to IT operations, we’ll be able to answer those issues more quickly.
What issues does AIOps aim to address?
This is the first question since it is the most crucial to answer. You should consider the benefit of AIOps adoption, just as you would any other new technology adoption. As previously stated, AI hardware and adoption are not inexpensive endeavors. While AI is undeniably exciting, it’s no different from any other software application. It can only answer questions you know how to ask, so be sure the ones you’re asking are worthwhile.
- There is far too much complication. Most enterprise-class business services now rely on a variety of new, dynamic technologies, including containers, cloud delivery models, virtual and software-defined components, and more, in addition to older systems like on-premises mainframes and distributed systems.
- There are far too many tools. New tools were added to the mix as new technology was incorporated. Teams are now dealing with hundreds of thousands of warnings that have a high rate of error and redundancy, thanks to dozens of technologies. Staff must spend too much time inspecting numerous systems and domains to discover the root cause of issues because they lack a unified view that spans their hybrid, heterogeneous settings. As a result, client satisfaction diminishes, and triage calls can last for hours.
- There is too much quick change. Organizations have begun to deploy containerized apps on a broad scale in recent years. The move from traditional application hosting technologies (such as virtual machines) to containers has dramatically increased the dynamic of application environments, with individual container instances spinning up and down regularly. Microservices applications, like containers, are inherently more complex than their predecessors because they comprise numerous services that start and stop at different times.
At this point, you should have a good idea of your AIOps strategy blueprint. It’s possible that you’re not aware of every piece of information. You may need to consult with your team to see if AIOps is the right fit for your operations. If you can answer the three essential questions, you’ll be well on your way. A DevOps managed service provider like CSE will assist you if you have problems answering some of those questions; Computer Solutions East makes data collection and model training easy. We’ve gathered decades of data and iterated our models multiple times. We’ve seen it all, so let us know if you need help putting together your AIOps strategy.
