Due to the boom digitization has experienced in recent years, companies are generating more data than ever. Processing these amounts of data requires powerful IT infrastructures and teams to keep the systems running. So much for the theory. In reality, however, there is an severe shortage of skilled specialists in the IT industry, and the failure of a system can quickly cost millions of dollars.

The Evolution of Automation

However, if we consider IT environments as complex ecosystems, only one logical consequence remains: evolution. Evolution takes place everywhere at any time, and in this case the goal of further evolvement is independence from manual configurations to keep the system up and running in the event of unexpected disruptions. In short: a self-healing infrastructure.

Just imagine how complicated our lives would be if our bodies were nonfunctional for hours every time we cut on a piece of paper or bumped against the edge of a bed? Cheers to our self-healing powers! So why shouldn’t we apply this principle to our IT infrastructures, which have become almost as essential to our daily lives as a healthy body?

After all, given the heavy reliance on IT processes nowadays, DevOps teams should be able to immediately and automatically fix issues in the infrastructure to ensure that business processes are not interrupted through downtime. The ultimate goal of a self-healing infrastructure is to drive automation to the point where disruptive factors can be identified and fixed without manual intervention before it ends in a costly downtime.

Prospects of a self-healing infrastructure

The hardest part of the evolutionary process is to establish a new mindset and to create new structures. Where manual tasks have been performed over and over again and never questioned, automating these processes might not come to mind easily. But the prospects of implementing new technologies such as AI, machine learing and infrastructure automation speak for themselves. Since ongoing learning is part of every IT professionals path, understanding and implementing the values of AI and machine learning should be a priority in incident management.

Automating the incident management process allows teams to respond in real-time to the notification of potential issues. They just have to approve to the solution offered by the self-healing infrastructure. In this way, DevOps Teams can operate less and innovate more.

Best Practices

There is no industry-defined roadmap to achieve this state of infrastructure yet. In the same way as it needs a synergy of our senses to perceive our environment, a self-healing infrastructure runs on various core components, which ultimately work together. For the most part, it’s combining observability and artificial intelligence. Similiar to our senses, these components might be: logs, traces and metrics. Each of these tell us something different, but when combining the power of all three, development teams can determine where, when and how an incident occurred and take action as needed.

Another essential practice towards a self-healing infrastructue is to automate the infrastructure itself. The key here is Infrastructure as Code (IaC). When there are no servers to be manually provisioned and configured, DevOps teams can concentrate more on increasing the systems performance. Through the use of code, any source of errors can be located in a fractional amount of time.

Self-healing IT is here to stay

What seemed to be an utopian idea a few years ago, can soon become part of everyday business processes. Through the constant evolution of automation, new best practices in incident management will be adapted by more and more IT teams. Not only does the implementation of a self-healing infrastructure reduce the cost of running IT systems, it also helps securing these systems more efficiently by automating observation processes. With the ongoing improvement of service reliability, companies won’t have to fear expensive downtime and can focus on improving their customer service.


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