This series of six blogs outlines the basics of the Observability Maturity Model. Use it to identify where you are on the observability path, understand the road ahead and provide guidance to help you find your way.
Written by Andrew Puch and Brian Langbecker You use NGINX as a proxy for your application, and you want to leverage your favorite features in Honeycomb to help make sense of the traffic data. Have no fear: Honeycomb is more than capable and ready to help! Things you will need: Before you start with the instructions, let’s discuss a lightweight tool called Honeytail. This utility will tail log files, parse the various formats, and send the data to Honeycomb.
HTTP is the backbone of all API-centric, modern web apps. APIs are the place where the core business logic of an application lives. As a result, developers spend a lot of time optimizing the API business logic. This article addresses a Node.js developer’s dilemma while debugging an HTTP API request. We take a sample Node.js/Express.js-based HTTP service to demonstrate a new way of debugging Node.js applications using the Lightrun observability platform.
A logging framework is a software tool that helps developers output diagnostic information during the execution of a program. This information is used to debug the program or monitor its performance. There are many different logging frameworks available, starting with simple logging libraries to full-fledged logging and observability platforms.
Today, we’re announcing major new updates to Honeycomb’s PagerDuty integration. These updates put more of the information you need into PagerDuty notifications and allow for greater configurability. These enhancements are available to all users who leverage Honeycomb Triggers and Burn Alerts to send notifications via PagerDuty.
Classically, the space of observability lies within layers of information on a dashboard. It operates by using the fundamental trio of data — metrics, logs and traces — from each layer of the environment to assess the health of an IT infrastructure. However, a time component is critical, making the stack observable at any point in time. Gathering reliable data and insights into your IT infrastructure remains the primary role of observability tools and services.
It’s no secret that CI/CD pipelines make the lives of engineering and operations easier by accelerating the feedback loop for higher quality code and apps. They build code, run tests, and safely deploy new versions of your application. But just like any aspect of development, poor integration, invisible bottlenecks, and bugs can plague your pipelines. And debugging them? Well, it’s complicated.
A prelude to our upcoming six-part Observability Maturity Model Fundamentals blog series. By Lodewijk Bogaards At StackState, we have spent eight years in the monitoring and observability spaces. During this time, we have spoken with countless DevOps engineers, architects, SREs, heads of IT operations and CTOs, and we have heard the same struggles over and over.
Technically speaking, observability offers visibility into the data being generated by your infrastructure devices, systems, and applications — but in reality, it offers the opportunity to see what’s happening, There’s no guarantee that you’ll get what you want; you have to set things up in a way that makes it possible for you to get the insights you need.
