How awesome would it be if machines resolve known, repetitive, and identifiable mundane problems while humans solve new complex problem? As a DevOps engineer managing cloud operations and handling tons of alerts everyday, had you wish this was true; that day isn’t far. Thanks to Algorithmic IT Operations (AIOps), which can reduce the stress and fatigued workload, eliminate alerts & repetitive events, improve business agility through intelligent management layers, and above all respond quickly to production incidents ten times faster.

Here’re the five AIOps that can help you navigate your DevOps tasks smoothly through 2017:

Adopt a Culture of NoOps For engineering teams to nurture the belief that “machines should solve known problems and engineers must focus on solving new problems,” they must first adopt NoOps philosophy, which essentially means saying NO to manual operations and yes to AIOps.

Automate Known Problems Engineers, who have managed production infrastructure, business services, applications and architected systems often observe that few problems are caused by known events and few problems have identifiable patterns. In such scenarios, these engineers would have had an idea on what to do when certain events or symptoms occur in their application or production infrastructure. Automating actions (response mechanisms) for such known events, along with the business logic embedded using algorithms, is the best way forward.

Build Diagnostics for Operational Issues Most of today’s tools just provide a text of what happened instead of providing a context of what is happening or why it’s happening, when events or alerts occurring due to problems are triggered. If there are diagnostic, algorithmic scripts or programs to tell why, rather than just when and where, it becomes easier to get the context, thus enabling to find the root cause faster.

Use Code as a Weapon Yes! You can create everything from automated actions to diagnostics using code to save hours of time after every deployment. In essence, using CODE as a mechanism for resolving problems should be the way forward.The key is to start applying algorithms for solving IT operational problems.As a DevOps engineer, if you are building the continuous integration or continuous delivery today then you should certainly deploy a trigger as part of your CI/CD pipeline that can monitor deployment for health metrics and invoke a rollback if it detects issues.

Adopt Intelligent DevOps Tooling With the availability of technologies like Docker, microservices, cloud and API driven approach to deploying applications at scale, days of using static tooling for deployments, provisioning, packaging, monitoring, APM and log management is almost over. It’s about time, embrace AIOps.

The Wrap-Up

A progression from DevOps to NoOps is a must, if you are building your application or solution with a credo that “machines should solve known problems and engineers must focus on solving new problems.” And for that progression to actualize from DevOps to NoOps, embracing AIOps is a must.

Botmetric is excited about working on an intelligent event-driven platform for managing incidents and operations for the cloud world. Botmetric, as a platform, handles most of the operational problems a DevOps engineer faces using application discovery, alerts data, cloud configuration, historic patterns and known events. The ultimate goal at Botmetric is to help customers move from DevOps to NoOps philosophy by bringing Algorithmic IT Operations for incident management in the cloud.

What is your take on AIOps and NoOps? Do share your thoughts below in the comment section, or on Twitter. Do read the Botmetric blog post on Alert Analytics to see how Botmetric is driving cloud management with NoOps capabilities.

Editor’s Note: This exclusive blog post is an adaption of the original article, DevOps to NoOps: Embrace Algorithmic IT Operations in 2017, penned by Botmetric CEO Vijay Rayapati.