RabbitMQ metrics monitoring is important to ensure that RabbitMQ is performing as expected and to identify and resolve problems quickly. In this tutorial, you will install OpenTelemetry Collector to collect RabbitMQ metrics and then send the collected data to SigNoz for monitoring and visualization.
What is the hidden potential of OpenTelemetry? It goes a lot further than the (awesome) application of tracing and monitoring your software. The OpenTelemetry project is an attempt to standardize how performance is reported and how trace data is passed around your microservice architecture. This context propagation is a superpower for those who adopt OpenTelemetry tracing. Tracetest promises to make this deep tracing a huge new asset in your testing landscape, and SigNoz helps all engineers get insight into what OpenTelemetry can see.
OpenTelemetry is a Cloud Native Computing Foundation(CNCF) incubating project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). OpenTelemetry aims to provide a vendor-agnostic observability framework that provides a set of tools, APIs, and SDKs to instrument applications.
In the classic definition, Observability is something one step beyond monitoring; it’s how easy our system is to understand with the architecture and monitoring we have. The problem is a familiar one: we have monitoring tools but they’re not answering our question. This article shows how a Python developer can go from having traces but not answers, to fully understanding the root cause of a latency issue.
OpenTelemetry is a Cloud Native Computing Foundation(CNCF) project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). However, OpenTelemetry does not provide storage and visualization for the collected telemetry data. For visualizing OpenTelemetry data, you need an OpenTelemetry UI. The data collected by OpenTelemetry can be sent to a backend of your choice, which can then be visualized.
On a recent thread on the CNCF Slack’s OTel Collector channel, a user asked a question that shone a light on a topic I don't think has been effectively discussed elsewhere.
OpenTelemetry can be used for generating and collecting telemetry signals like logs, metrics, and traces. The advantage of using OpenTelemetry for observability is that it is open-source and frees you from vendor lock-in. You can use OpenTelemetry for multiple use cases
Are you looking for an OpenTelemetry alternative? Then you've come to the right place. There are no good alternatives to OpenTelemetry if your use case involves generating different types of telemetry signals like logs, metrics, and traces and their collection. In certain use cases, like monitoring only metrics or time-series data, you can use a tool like Prometheus.
OpenTelemetry is a Cloud Native Computing Foundation(CNCF) project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). OpenTelemetry lets you export the data it collects to any backend of your choice.