Operations | Monitoring | ITSM | DevOps | Cloud

Observability is made up of metrics, logs, and traces. These pillars help us understand the behavior of applications under normal execution, which further accelerates identifying anomalies in case of application failure or deviation from normal execution. Logging is not about tracing each and every operation, it is about sensible, consistent, and machine-readable log messages that expose the application behavior.

In 1927, the world was introduced to the origins of Artificial Intelligence (AI) in the form of a robot in the movie Metropolis. Throughout nearly a century since then, movies have continued to iterate on the complexities of AI, as both a fun take on it and serious commentary on the potential concerns and consequences. This is all well and good, but as AI has continued to evolve, we find ourselves asking, “how can we actually use this to make our lives easier?”

Technology trends transform human behavior permanently. In the past decade, we have improved as a society by embracing digital lives that drive faster collaboration and automation and save us a significant amount of time. The IT Operations landscape is not any different, and artificial intelligence (AI) is at the forefront of that.

If you’re reading this article, you’re most likely looking for a simple one-stop-shop way to understand logs. I’m sorry to be the one to tell you this, but logs are not simple enough to deal with easily. In fact, as you start approaching this topic on a practical level you’ll quickly realize how complex and annoying it truly is.

A key topic of conversation that comes up again and again with our customers is the challenge of collaboration in a remote work environment. Too many channels of communication or documentation are ineffective, and IT professionals are starting to feel fatigued by never feeling quite “in the know” with business decisions that are happening in real-time. When separated from colleagues, teams can feel distant and unmotivated or find it hard to stay focused.