DevOps deeper dive: AIOps transformation
Every man and his dog has already heard about DevOps. Many companies have implemented DevOps already and some companies are just about to do it. Therefore, a new question arises: “What is AIOps?”. This is a less popular term than DevOps but in reality, they are closely intertwined. AIOps is a logical part of DevOps development. So, let’s discuss what is AIOps and whether you need to urgently call the DevOps consulting company ordering this service.
DevOps for AI or AI for DevOps?
Despite the tautological question, there is a lot of sense, so let’s define what we mean. DevOps for Artificial Intelligence (AI) is a part of DevOps-as-a-Service. In this case, you use a DevOps methodology for AI development. Machine Learning (ML) and AI are related to software development and anywhere you have the software development, you can implement DevOps for efficiency increase. Such an approach will give a lot of benefits like Continuous Implementation and Continuous Delivery, strong and cohesive teams and much more. If you read this, you surely know about all the advantages of DevOps philosophy.
AI for DevOps is a harder and deeper process. Imagine the next situation. You have a huge company specialized in logistic, finances or bank domains, for example. You already implemented DevOps to your workloads. You hire a few dozens of DevOps engineers who look for system logs and data during day and night. Is there any way to improve the current system? Yes, you can automate all the monitoring processes and it will be AIOps. How can it help to make your workflow more efficient?
When you have the large and heavy infrastructure it is pretty hard to manage all the information, make predictions and troubleshoot. Usually, after implementing DevOps-as-a-Service, DevOps engineers need to sit in front of the screen and monitor all the actions and logs. If the system needs more capacity, DevOps engineer will manually increase resources and cut them back after it’s no longer needed – or will have to write multiple scripts for Jenkins workers or build Ansible playbooks to automate this task.
What does AIOps offer in this situation? DevOps engineer with a team of Big Data specialists (Big Data analyst, Big Data architect/scientist and others) can make automated systems. This system will analyze logs and historical data to make the patterns. A qualified team of specialists can use the reinforced model of AI training to make patterns clearer.
As a result, you’ll get a self-estimated and self-healing system that can monitor changes and react according to them. DevOps engineer, in this case, needs to make all the preparations and train the system along with the other specialists. DevOps engineer set the thresholds for correct system reaction. Even if some failure occurs in the system, it quickly reboots and writes crash logs. DevOps engineers can analyze crash logs and make some changes to the system to prevent such crashes in the future.
Wrap up: do you need to implement AIOps to your company?
Despite huge benefits from AIOps, it is not for any business. This technology is most appropriate for large companies with complicated internal processes and infrastructure. AIOps is really needed for logistic companies, finance area or banks. These companies need to work without any pauses or decreases in efficiency. Thus, such companies will have only benefits from AIOps. Talking about small and average business, it is better to choose DevOps-as-a-Service for more cost-efficiency.
AIOps implementation is really expensive because you need to hire highly-qualified DevOps engineers and Big Data specialists to design and train AI algorithms correctly. Also, you need a lot of server capacity and other resources. It is not efficient for small companies because you’ll need to pay a huge sum and do not have a remarkable difference between DevOps and AIOps. The big companies will get a huge difference at the same time.
If you decide to implement AIOps you can hire specialists one by one or find a Managed Service Provider who’ll provide you with a dedicated team. This approach is the most cost-efficient because you don’t need to spend money and time for long recruiting processes, you are just hiring a whole team.
As a result, you’ll get a lot of benefits at a reasonable price.