Dernière mise à jour : 3 mars
New cloud monitoring and cloud management tools are becoming self-learning, with both pros and cons today
As someone who’s worked with AI for the last 30 years (yes, it was a thing 30 years ago), we have often thought of its capabilities were overrated and used for the wrong things in many cases. Now that it’s cheap thanks to cloud computing, and much more effective thanks to the pace of innovation, AI as a solution is coming up again, including the use in cloud operations.
The idea is to replace people with AI to be both proactive and reactive to cloud operational issues such as outages, resource governance, security attacks, and performance. Cloudops involves largely repeatable problems, right?
There are of course some upsides and some downsides to this. Moreover, although the use of AI in cloud operations maybe a foregone conclusion, there will still be a learning curve that is required. As long as you understand that and know what to expect in terms of ROI for both the short term and long term, we are okay with anything that that makes cloud operations more effective.
So, let’s look at the pros and cons.
The pros of AI for cloudops
The pros are that you can have a 7/24/365 monitoring and management program on the cheap. If you believe operational staff is expensive, try hiring them for shift work. AI-based monitoring and management systems never sleep, never take time off, and never ask for a raise. Once they are up and running, they cost almost nothing beyond their license fees and infrastructure costs. And they are self-learning at the same time; in other words, the more they run, the better that they get at the job.
Another pro is that these systems get smarter every day and share a common brain. People get smarter with experience as well, but they don’t do a good job sharing their experiences with others. People also retire and quit, with the knowledge and experience walking out the door with them.
The cons of AI for cloudops
One con is that the cost of rolling out these systems is high, even in the cloud. Vendors that have married AI and operational tools are going to charge a premium to get them up and running and in production. While the prices are all over the place, count on paying 50 percent more than for traditional tools, including consulting services for the first year or so to get the tools learning correctly.
Another con is that operations people don’t seem to like them no matter how well they perform. The number of passive-aggressive actions that I’ve seen over the years from people pushing back on AI-enabled operations tools has been huge.
They view this technology as not to be trusted, plus the fact that AI some day may displace their jobs does not make things better. Organizations that implement these tools need to have change agents, plus an understanding about the human factors with this technology.
Is the future AI-enabled cloud-operations tools? We don’t see how it won’t be. The pros will get better, and the cons will begin to diminish, like any other rollout of new technology. Hopefully, our new AI operations overlords will have mercy on us in a few years.