The latest News and Information on Log Management, Log Analytics and related technologies.
Machine learning has infiltrated the world of security tooling over the last five years. That’s part of a broader shift in the overall software market, where seemingly every product is claiming to have some level of machine learning. You almost have to if you want your product to be considered a modern software solution. This is particularly true in the security industry, where snake oil salesmen are very pervasive and vendors typically aren’t asked to vigorously defend their claims.
In Part 1 of this series, we talked about the origins of observability and why you need it. In this blog (Part 2), we will cover exactly what observability is, what it isn’t, and how to get started. Before we can dive into how to approach observability, let’s get one thing clear: You can’t buy a one-size-fits-all observability solution.
Redis is an open-sourced, BSD 3 licensed, highly efficient in-memory data store that can be easily used as a distributed, in-memory key-value store, cache, or message broker. It is known for being extremely fast, reliable, and supporting a wide variety of data structures, making it a very versatile tool widely adopted across the industry. Redis was architectured with speed in mind and is designed in a way that it keeps all the data in memory.
We’ve got a lot of OpenTelemetry-flavored honey to send your way, ranging from OpenTelemetry SDK distribution updates to protocol support. We now support OpenTelemetry logs, released a new SDK distribution for OpenTelemetry Go, and have some updates around OpenTelemetry + Honeycomb to share. Let’s see what all the buzz is about this time! 🐝🐝
Hello, I’m Callum. I work on Grafana Loki, including the hosted Grafana Cloud Logs offering. Grafana Loki is a distributed multi-tenant system for storing log data — ingestion, querying, all that fun stuff. It also powers Grafana Cloud Logs.
In this post, we’ll discuss two functions in the Cribl Stream arsenal: The Aggregations function, which allows you to perform stats and metrics collection in flight, and the Chain function allows you to call one Pipeline from within another. The event flow will continue when the Chained Pipeline returns. To demonstrate their use, we’ll answer this question: How long did it take for Cribl to process events using your pipeline?