What do mall food courts and Honeycomb have in common? We both love sampling! Not only do we recommend it to many of our customers, we do it ourselves. But once Refinery (our tail-based sampling proxy) is set up, what comes next? Since sampling is inherently lossy, it’s good to be sure the organization’s most important measurements aren’t negatively affected.
Our friends at Tracetest recently released an integration with Honeycomb that allows you to build end-to-end and integration tests, powered by your existing distributed traces. You only need to point Tracetest to your existing trace data source—in this case, Honeycomb. This guest post from Adnan Rahić walks you through how the integration works.
The Accelerate State of Devops Report highlights four key metrics (known as the DORA metrics, for DevOps Research & Assessment) that distinguish high-performing software organizations: deployment frequency, lead time for changes, time-to-restore, and change fail rate. Observability can kickstart a virtuous cycle that improves all the DORA metrics.
The needs of observability workloads can sometimes be orthogonal to the needs of compliance workloads. Honeycomb is designed for software developers to quickly fix problems in production, where reducing 100% data completeness to 99.99% is acceptable to receive immediate answers. Compliance and audit workloads require 100% data completeness over much longer (or "infinite") time spans, and are content to give up query performance in return.
Salary Finance is a UK-based financial well-being employee benefit program. Over the last seven years, the company grew from a startup to a scaleup, earning rave reviews along the way from its more than 4,000 customers. However, with fast growth also comes natural growing pains. As their customer base expanded, so did the number of incidents they experienced, which also became harder to diagnose due to lack of visibility into their increasingly complex environment.
The W3C trace context specification is an amazing standard and a massive leap in standardization of telemetry correlation in the current climate of microservices being the de facto for new systems (that’s a debate for another day).
Tech debt is usually one of the most fraught topics on engineering teams. Engineers often feel they aren’t allowed enough time to address tech debt. Product partners wonder why engineers spend so much time working on it—or at least talking about it. “The business” always seems to insinuate that engineers should do less of it, instead focusing on shipping value to customers.
The OpenTelemetry Go project now supports automatic instrumentation via eBPF! This is a big milestone for the project and makes it significantly easier to generate data from your Go apps: The automatic instrumentation agent is still in s/alpha/beta today, but it’s ready for you to try on your applications!
Honeycomb's Refinery is a tool that customers can use to help manage the volume of their telemetry. It's rare to have too much telemetry—it's not often that someone says "I wish I didn't have all this information!" However, telemetry is data, and data is not necessarily information—particularly when you’re drowning in it. Honeycomb's query engine is so fast and powerful that many customers can send us all their telemetry.
According to the Uptime Institute’s 2022 Outage Analysis report, one out of every five companies has experienced a “serious” or “severe” incident over the past three years—a percentage that’s increasing. Those incidents are expensive: over 60% cost more than $100,000, while 15% set their companies back close to $1 million.
