Why use AIOps?

I was speaking with a friend about AIOps. His early stage startup team did not see the need for using artificial intelligence for operations. I found it surprising and wondered why? Another friend made the observation that startups are very short term focused. Why worry about a problem that you don’t have yet? I started to ask myself, who should use an AIOps solution?

One observation is, IT organizations do not lack tools, metrics, alerts, etc. On the contrary, it has too much data and lacks true visibility into it's operations and ability to deliver timely insights because of silos.

Is AI really necessary?

Gartner defined AIOps as the following: AIOps platforms combine big data and machine learning functionality to support all primary IT operations functions through the scalable ingestion and analysis of the ever-increasing volume, variety and velocity of data generated by IT.

According to McKinsey, Cloud represents a trillion dollar opportunity. Leveraging that opportunity requires all businesses to focus on making the necessary investments and attracting the talents to setup a cloud operating model that delivers speed, agility, efficiency and scalability. It is challenging, but the business implications are enormous.

How do I know if I should consider AIOps?

With adoption of containers, microservices, and cloud, IT organizations are struggling to manage the scale and complexity of the data that operations teams need to process to understand and manage their critical business applications. Ask yourself if your organization is struggling with one of these problems?

• How long does it take your organization to identify the root cause of an incident? Is it hours or minutes?
• Are too many people getting involved in a war room? Is it over 10? Does it get tense and political with finger pointing?
• How many tools are you using to manage your cloud operations? Is this over 8?
• Are you starting to drown in new IT events every day? Is it over 100 per day? How many of these events are false positives?
• Are you struggling to hire talents to manage your operations?
• Are silos preventing you to deliver real-time insights?

If you are facing some or all these problems, you may need to think about modernizing your operations with AIOps.

What are the benefits of AIOps?

AIOps tool can help you automate the analysis of data (events, logs, metrics, traces, etc.) from your tools and operations. Some will come with end-to-end solution for data ingestion and make them searchable. Others will layer on top of existing tools. The solution will provide better causality and quick root-cause-analysis that is critical for lowering your MTTR (mean time to recovery). The solution reduce alert noise by avoiding false positive events and reduce number of events with event correlation. It breaks down silos in the data organization by connecting them and creating necessary context. AIOps solution can detect correlation with a previous incident and can make remediation recommendations. With all the intelligent automation, it reduces the amount of SRE/support engineers necessary for operations because AIOps is all about automating incident management.

Build vs. Buy decision

Large organizations have the choice of building the solutions in-house. If your organization know how to architect for scale, high availability and have the necessary talents to develop machine learning (ML) and deep learning (DL) models, you may consider building the AIOps solution yourself. You will need technical leaders with excellent communication skills and clear understanding of Cloud, DevOps and ML/DL to solve the problems. Please be warned that a larger portion of AI projects fail because of scarcity of talents and data. A SaaS solution such as CloudAEye is a prudent choice if you decided to “buy”. Not only it reduces risks, it will allow you to speed up your time to market and use cutting edge AI solutions that are proven. More importantly, it will enable you to develop and deliver more strategic business initiatives and eliminate the toil to “keep the lights on”.

Epilogue: Should I do AIOps in the middle of COVID and the “great resignation”?

In light of COVID, companies are under pressure to react to a changing dynamic faster. Spotlight on increasing productivity, reducing cost, engaging with customers to keep them happy and retaining talents are top priorities for most CEOs. According to LinkedIn, 1 in 7 (compared to 1 in 69) jobs are remote now. Gone are the days when you can huddle together to debug or investigate a problem. If you help your employees to get a sense of purpose, they are more likely to stay. By helping your employees avoid the stress of operations to “keep the lights on” and enable them to reflect and connect with their own sense of purpose may not only solve the retention issue, this will give them energy and satisfaction about their work.

References

• The documentation for the CLI is available at docs.cloudaeye.com/cli-reference
• Product documentation for CloudAEye SaaS is available at docs.cloudaeye.com/index.html

Picture: CloudAEye SaaS Sign up Page