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.

Observability and Monitoring are viewed by many as interchangeable terms. This is not the case. While they are interlinked, they are not interchangeable. There are actually very clear and defined differences between them. Monitoring is asking your system questions about its current state. Usually these are performance related, and there are many open source monitoring tools available. Many of those available are also specialized.

Graphical processing units, or GPUs, aren’t just for PC gaming. Today, GPUs are used to train neural networks, simulate computational fluid dynamics, mine Bitcoin, and process workloads in data centers. And they are at the heart of most high-performance computing systems, making the monitoring of GPU performance in today's data centers just as important as monitoring CPU performance.

We can plausibly say the enterprise development market turned the tide on cloud-native development in 2020, as most net-new software and serious overhaul projects started moving toward microservices architectures, with Kubernetes as the preferred platform.