Operations | Monitoring | ITSM | DevOps | Cloud

This is the second in a series of blog posts exploring the role that intelligent observability plays in the day-to-day life of smart teams. In this post, meet our clever ITOps engineer, James, as he reduces noise and distraction using intelligent observability.

I drive a 2005 Ford diesel pickup truck. Most of the time my truck runs great. But occasionally an orange light on the dashboard will flicker on to alert me that something is wrong. Unfortunately, there’s no information about what is wrong and why. My truck has a monitoring solution, but not an observability solution. In many cases, IT has the same problem as my truck.

One of the more delicate debates in the DevOps world is what observability has to do with monitoring. Is observability just a trendy buzzword that means the same thing as monitoring? Is observability an improved version of monitoring? Are monitoring and observability different types of processes that solve different problems? The answer to those questions depends in part on your perspective.

All the work presented in this blog post is open source and available as part of our Splunk Connect for Ethereum repository examples, including the instrumentation of Besu as a Docker container, the configuration of Splunk, and two applications showing how to monitor Besu syncing to the chain.

As IT environments become more complex, enterprises running business-critical workloads in dynamic environments need to ensure the performance and reliability of their applications. This is where observability comes in. Observability is the ability of the internal states of a system to be inferred from external outputs. Without it, your team’s productivity could be greatly diminished.

Today, we announced that Refinery is now generally available. With Refinery, it’s now easy to highlight the critical debugging data you need and to stop paying for the rest. Refinery is a sampling solution that lets you control resource costs at scale without sacrificing data fidelity. Support for Refinery is now also included in Honeycomb Enterprise plans.

Are you looking for a better way to troubleshoot, debug, and really see and understand what weird behavior is happening in production? Service-level objectives (SLOs) and observability can help you do all that—but they require collecting and storing the right data. If we’re naive with our telemetry strategy, we spend a lot of money on storing data without seeing adequate return on investment in the form of insights.

First things first. Observability is inherent as a principle to a system and not something that is instilled. Here, we are addressing observability as an open source based solution in the context of insightful monitoring within the ITOM landscape. ITOM is now in the middle of addressing the needs of the expanding and dynamic nature of IT infrastructure as a function. It is no longer about being a monolithic computing stack. It is now beyond monitoring discrete infrastructure elements.