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The latest News and Information on Observabilty for complex systems and related technologies.

The Business Case for Observability with Context

My team was not happy with me. I had just convened a meeting of my direct reports — and the managers that reported to them — to deliver the news personally. “No more new tools,” I told them. “We have everything we need to do our job. Our environment just doesn’t change that fast. So stop bringing me requests for new tools. The answer is no.” It was unquestionably the right call at the time, but today, it would be laughable.

Mix & Match! Tracing Header Interoperability Between OpenTelemetry and Beelines

We’ve released support for tracing header interoperability in all of our Beelines. This means you can now mix and match distributed services instrumented with Beelines or with OpenTelemetry, and your traces will be preserved in Honeycomb!

Raw & Real Ep 7 The Tracing You Deserve So You Can Observe

Distributed tracing is key to building and operating reliable services that make your customers happy. Traces pinpoint where failures occur and what causes poor performance. With tracing and observability, you can visualize the entire life cycle of service requests and discover hidden latency, errors, and optimization opportunities monitoring can’t show you. So why doesn’t everybody do it? Setting up tracing is notoriously difficult, but it doesn’t have to be. Honeycomb Instrumentation Engineer Paul Osman has the easy-breezy steps for you to get the tracing you deserve.

The importance of metadata in your Kubernetes observability initiatives

Kubernetes is a popular container orchestration system at the heart of the Cloud Native Computing Foundation projects. It automates the deployment, lifecycle, and operations of containers, containerized applications, and "pods," which are groups of one or more containers. The platform itself, along with each of these workloads, may generate event data. There are different kinds of data associated with these processes.

Lightrun & JFrog - Achieving Complete Agility With Continuous Debugging And Continuous Observability

CI/CD has become the de facto standard for infusing the software development process with hardcoded agility. Organizations are now integrating DevOps concepts and practices into their workflows in order to get great features out of the door faster and reduce internal friction. But your ability to understand what’s going on in a production service is pre-defined by the logs, metrics and traces (i.e. the three pillars of observability) your developers pre-defined during development. There is, however, a need for agility even after the service is live - in order to adhere to strict SLAs, decrease MTTR and save on logging costs.

Infrastructure Observability with Resource Events

You may have seen the Honeycomb white paper on metrics, and want to use the power of Honeycomb with metrics. Sending infrastructure metrics data to Honeycomb has always been possible, but with our focus on debugging the user experience inside the application, it isn’t the first or most obvious thing to do. This post will discuss why we use metrics in general and how to think about metrics in Honeycomb.

HAProxy Log Sampling

Log Sampling is a powerful feature introduced in HAProxy 2.0 that lets you define a percentage of your logs to create a representative view of your data allowing you to minimize your costs. Log files are the key to observability. They can provide helpful information that can be used for debugging as well as analytics that can be used to understand how users interact with an application.

Achieve Better Observability into AWS Services with the AWS CloudWatch Monitoring Template

Amazon CloudWatch — Amazon’s built-in infrastructure monitoring tool — monitors your Amazon Web Services (AWS) resources and the applications you run on AWS in real time. Here’s what you can do with this tool and how to access AWS CloudWatch monitoring dashboards.