In 2019, enterprises worldwide reported that every hour of infrastructure downtime cost them an average of $301,000- $400,000. If a system is down for five hours, that’s $1.5 million lost—and that’s on the low end. Five hours of downtime can impact companies for months down the road. It’s in the hands of DevOps practitioners to ensure systems are up and running and budgets are kept in line. But if they don’t have the proper tools on hand that allow them to juggle their responsibilities while adding value to the business, it makes their jobs that much more difficult—or, dare I say, impossible.
Teams simply can’t afford to go offline to fix incidents, but neither can they afford to manually sift through data to find the root cause. By automating the incident management process, developers have more time to focus on building new products and capabilities that drive revenue. With a self-healing IT infrastructure, teams can tackle these issues before they become larger issues costing millions of dollars.
Imagine you’re running to catch a bus and your heart rate increases, but when you sit down, it doesn’t come back down to a normal rate. This could quickly become a much larger, even fatal issue. In this instance, the body should “self-heal” to get back to a normal rate. On a similar note, a self-healing IT infrastructure allows teams to quickly get back on track by fixing issues before they become a $1.5 million problem.
Let’s look at how DevOps practitioners can turn a self-healing IT infrastructure into a reality.
Self-Healing Infrastructure Needs Observability and AI
Observability is the practice of collecting deep data from applications and services to provide insights through three core components: logs, traces and metrics. While these three components are essential to a self-healing infrastructure, they are most powerful when used together. Similar to our senses of sight, hearing and touch, they each tell us something different but are equally important. When combining the power of all three, development teams can determine where, when and how an incident occurred and take action as needed.
We all know the pain of traditional monitoring tools. They don’t surface immediate issues or identify root causes. They rely too heavily on developers to interpret and analyze immense amounts of data then sift through it in a tedious and time-consuming process requiring extra budget for more human power, and extra time to identify and remediate incidents. Using today’s cloud-native self-service approaches to combine observability and artificial intelligence, teams can set up tools themselves that automate the process of gathering and correlating metrics, logs and traces at machine speed to provide a complete, intelligent and actionable picture of what’s happening and why. And that’s where a self-healing IT system starts.
The Future Is Within Reach
By ingesting observability data, applying AI to analyze that data and create insights around root causes, then leveraging automation in a closed-loop, dev teams can not only see what’s happening but also take action on it for remediation. When this closed-loop process is done intelligently at machine speed, that’s when self-healing becomes a reality.
The idea of a self-healing IT infrastructure doesn’t have to be a distant vision. In fact, the democratization of cloud computing and advanced data science have put the required observability technology within reach of teams of any size with any budget. When artificial intelligence and observability come together, DevOps practitioners can operate less and innovate more.
