To many engineers, the idea that you can accurately and comprehensively track your application's user experience using just a few simple metrics might sound far-fetched. Believe it or not, there are four metrics that aim to do just that. They're called the four Golden Signals and should be a core part of your observability and reliability practices.

Traditionally, when monitoring or troubleshooting active incidents, engineers access logs directly on the source system. However, modern IT environments are now too complex, and engineers can no longer manage and analyze logs effectively this way. With the adoption of microservices and the use of cloud-native infrastructure, it’s no longer feasible.

Today, I’d like to tell you about a new community-contributed integration that connects Honeycomb to your ServiceNow workflows. My new integration reimagines what’s possible when connecting observability tools with ITSM systems. This post explains how it works and how to get started with it.

Observability is a methodology that you incorporate into your enterprise architecture to provide greater visibility into what is happening. It helps us determine the states of the system from their external outputs and allows technicians to identify bottlenecks, predict issues and mitigate them. As the architectures of IT systems are becoming more complex and distributed we use observability to meet the need to measure their internal states.

Observability is a hot topic in the IT world these days. It is oftentimes discussed through the lens of the “three pillars of observability”: Logs, Metrics and Traces. Indeed these telemetry signal types help us understand what happened, where it happened and why it happened in our system.

When I started my career in information technology, I worked for a large insurance company in Omaha, Nebraska. At the time, they exclusively used Lotus Notes, an IBM product. Even as Microsoft Outlook gained popularity and functionality, the cost of changing email clients was insurmountable, so the company continued using Lotus Notes for many years.

In my last blog post, Building a Cost-Effective Full Observability Solution Around Open APIs and CNCF Projects, we introduced using ChaosSearch in combination with the most popular open source front- and back-ends in the application observability space. In case you missed it, the TL;DR version is that you can use a variety of open source projects and open API-based components to build the best-of-breed observability stack of your choice rather than relying on expensive, all-in-one solutions.

Building modern, cloud-native applications introduces new challenges to teams and organizations. As these systems grow and scale, struggles abound: inconsistent performance monitoring experiences across siloed tools, wasteful performance management practices with duplicated efforts, and mounting frustration from colleagues and customers. Surmounting these challenges requires multiple sources of data and truly unified observability.

We all know that observability is a must-have for operating systems in production. But we often neglect our own backyard — our software release process. We noticed we made that mistake here at Logz.io. We were wasting time and energy in handling failures in the CI/CD pipeline, and made our Developer-on-Duty (DoD) shifts tedious. That’s why it’s critical to incorporate your observability practices into your CI/CD pipeline.