Welcome to the next chapter of Grafana Loki! After five years of dedicated development, countless hours of refining, and the support of an incredible community, we are thrilled to announce that Grafana Loki 3.0 is now generally available. The journey from 2.0 to 3.0 saw a lot of impressive changes to Loki. Loki is now more performant, and it’s capable of handling larger scales — all while remaining true to its roots of efficiency and simplicity.

We are thrilled to announce the preview of Explore Logs, a new way to browse your logs without writing LogQL. In this post, we’ll cover why we built Explore Logs and we’ll dive deeper into some of its features, including at-a-glance breakdowns by label, detected fields, and our new pattern detection. At the end, we’ll tell you how you can try Explore Logs for yourself today. But let’s start from the beginning — with good old LogQL.

New in Cribl 4.5, the Model Driven Telemetry Source enables you to collect, transform, and route Model Driven Telemetry (MDT) data. In this blog, you’ll learn how to explore the YANG Suite to understand the wide variety of datasets available to transmit as well as how to configure the tools to get data flowing from Cisco IOS XE network devices to Cribl Stream.

Numerous companies keep launching AI/ML features, specifically “ChatGPT for XYZ” type productization. Given the buzz around Large Language Models (LLMs), consumers and executives alike are growing to assume that building AI/ML-based products and features is easy. LLMs can appear to be magical as users experiment with them.

On October 1, 2022, the UK Telecommunications Security Act (TSA) went into effect, imposing new security requirements for public telecom companies. The purpose of the act is noble, as it wants to ensure the reliability and resilience of the UK telecommunications network that underpins virtually every aspect of the economy and modern society.

Splunk’s extensible and scalable data platform has been instrumental in helping ITOps teams fully understand their tech environments and tackle any IT use case with data streaming, dashboarding, federated search, AI/ML, and more. But, with the explosion of telemetry and the growing complexity of digital systems, ITOps practitioners who rely solely on a logging solution are missing out on critical insights from their digital systems.

Site reliability engineers (SREs) and security analysts — despite having very different roles — share a lot of the same goals. They both employ proactive monitoring and incident response strategies to identify and address potential issues before they become service impacting. They also both prioritize organizational stability and resilience, aiming to minimize downtime and disruptions.

Stackify Retrace is an application performance management (APM) and log management platform designed to assist developers and DevOps teams in tracking, troubleshooting, and enhancing the performance of their applications and infrastructure. Stackify Retrace effectively combines APM with log management, enabling users to view detailed transaction traces for applications directly from the log statement to provide greater context and visibility for more effective analysis.

I recently attended SRECon in San Francisco on March 18 - 20, a show dedicated to a gathering of engineers who care deeply about site reliability, systems engineering, and working with complex distributed systems at scale. While there were a lot of talks, I’ll focus on a few areas that gave me the most insight into how having the right data impacts an SREs and an organization’s success.