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.

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.

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.

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.

Monitoring Solr is very critical because it handles the search and analysis of data in your application. Similifying this monitoring is necessary to gain full visibility into Solr’s availability and ensure it is performing as expectedn. We’ll show you how to do this using the jmxreceiver for the OpenTelemetry collector. You can utilize this receiver in conjunction with any OTel collector: including the OpenTelemetry Collector and observIQ’s distribution of the collector.

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.