We chose to use GoReleaser with our distro of the OpenTelemetry Collector in order to simplify how we build and support many operating systems and architectures. It allows us to build targeting a matrix of GOOS and GOARCH targets as well as automate creating a wide range of deliverables. Ones we have utilized are building tarballs, nfpm packages, docker images, and Homebrew formula.

As distributed environments become more complex, users often use distributed tracing tools to improve the visibility of issues evident within their traces. Throughout this post, we will examine some of the best open-source and other generally popular distributed tracing tools available today.

A full Observability stack has the goal of providing full centralized visibility to Development, Operations and Security teams into all of the Metrics, Logs and Traces generated by the applications and services under their domain. Many companies address these observability needs by buying a complete application performance management (APM) solution from a single vendor, like DataDog.

Bindplane OP is the first open source, vendor-agnostic, agent and pipeline management tool. It makes it easy to deploy, configure, and manage agents on thousands of sources, and ship metrics, logs, and traces to any destination. This blog shows you how to configure an existing OpenTelemetry Collector from any source to connect to Bindplane OP without needing to remove or reinstall the collector.

Global data, analytics and technology companies such as Equifax, and their Engineering teams, depend on log analytics for a variety of operational analytics use cases, from application troubleshooting to streamlining cloud operations and regulatory compliance management. ChaosSearch is uniquely positioned to help companies like Equifax significantly reduce the time, cost, and complexity of log analytics.

The way organizations process logs have changed over the past decade. From random files, scattered amongst a handful of virtual machines, to JSON documents effortlessly streamed into platforms. Metrics, too, have seen great strides, as providers expose detailed measurements of every aspect of their system. Traces, too, have become increasingly sophisticated and can now highlight even the most precise details about interactions between our services. But alerts have remained stationary.

The best part of my job is talking with prospects and customers about their logging and data practices while explaining how Cribl focuses on getting more value from observability data. I love to talk about everything they are doing and hope to accomplish so I can get a sense of the end state. That is vital to developing solutions that provide overall value across the enterprise and not just a narrow tactical win with limited impact.

A SIEM (Security Information Event Management) platform, along with several other tools that make you crave Alphabet Soup (XDR, UBA, NDR, etc), is a critical component of any organization’s security infrastructure. Between a constantly growing volume of logs, increasing attacks and breaches, and challenges finding qualified staff, many organizations may consider a SIEM migration. There could be several reasons for this.

When we say “logs” we really mean any kind of time-series data: events, social media, you name it. See Jordan Sissel’s definition of time + data. And when we talk about autoscaling, what we really want is a hands-off approach at handling Elasticsearch/OpenSearch clusters. In this post, we’ll show you how to use a Kubernetes Operator to autoscale Elasticsearch clusters, going through the following with just a few commands.