For this post, we’ll use a small Flask app that allows users to input a city name and they receive the current weather information for that city. We’ll make an API call to openweathermap.org to get the weather information for the city.
At Mezmo, we see a massive opportunity to reduce Mean Time to Detection (MTTD) and Mean Time to Resolution (MTTR) by making log data more valuable and actionable. Today, we’re thrilled to announce the release of the Mezmo Exporter for OpenTelemetry- the first step in our continued work with the project to further simplify the ingestion of log data and make that data more actionable with enrichment of key OpenTelemetry attributes.
Frontend technologies typically talk to several services in your backend, and those services talk to other services. At the root of every issue is a single event that causes a domino effect. A domino effect that impacts every operation from the first experience on the frontend to the backend API call. Sentry can show you how these exceptions and latency issues impact every one of your services. For example, take the ever common and seemingly simple to resolve 500 - Internal Server Error.
You may have previously heard about OpenTelemetry (also known as OTel) if you have looked into improved ways of standardising different data types. In this article, we’ll delve into the key things you need to know about OpenTelemetry and how this unified standard may become the future of how logs, metrics, events and traces are all handled.
The latest Jaeger v1.35 release introduced the ability to receive OpenTelemetry trace data via the OpenTelemetry Protocol (OTLP), which all OpenTelemetry SDKs are required to support. This is a follow-up to the previous announcement to retire Jaeger’s “classic” client libraries. With this new capability, it is no longer necessary to use the Jaeger exporters with the OpenTelemetry SDKs, or to run the OpenTelemetry Collector in front of the Jaeger backend.
In this tutorial, we will go through a working example of a NestJS application auto-instrumented with OpenTelemetry. In our example we will use a simple application that outputs “Hello World!” when we call it in the browser. We will instrument this application with OpenTelemetry’s Node.js client library to generate trace data and send it to an OpenTelemetry Collector. The Collector will then export the trace data to an external distributed tracing analytics tool of our choice.
Application performance monitoring (APM) solutions were designed to catch anomalies in an application or website's backend and provide meaningful insights to rectify issues in real time. Lately, though, APM solution providers have been left playing catch-up to be more inclusive of newly emerging technologies and the operational challenges they bring. OpenTelemetry (OTel) simplifies the issues caused by the demands of modern applications.
