Last year we introduced Live Tail — the ability to see a live feed of all the logs in your system, in real time, within Kibana. This ability to see a live stream of logs as they are being outputted from the different processes in a monitored environment was a greatly requested feature, and since being introduced we have received some excellent feedback from users that has allowed us to improve the basic functionality of Live Tail.

Looking to learn about Logstash as quickly as possible? This article is for you: we’ll install Logstash and push some Apache logs to Elasticsearch in less than 5 minutes.

Logging is an important part of understanding the behavior of your applications. Your logs contain essential records of application operations including database queries, server requests, and errors. With proper logging, you always have comprehensive, context-rich insights into application usage and performance. In this post, we’ll walk through logging options for Rails applications and look at some best practices for creating informative logs.

In a previous post, we walked through how you can configure logging for Rails applications, create custom logs, and use Lograge to convert the standard Rails log output into a more digestible JSON format. In this post, we will show how you can forward these application logs to Datadog and keep track of application behavior with faceted log search and analytics, custom processing pipelines, and log-based alerting.

From production monitoring to security concerns, it’s critical for businesses to analyze and review their log data. This is particularly true for large and enterprise companies, where the sheer amount of data makes log analysis the most efficient way to track key indicators. CTOs, in particular, are dealing with the challenges of this massive amount of data flowing through their organization, including how to harness it, gather insights from it, and secure it.

Sumo Logic is no different than most companies — we are in the service of our customers and we seek to build a product that they love. As we continue to refine the Sumo Logic platform, we’re also refining our feedback loops. One of those feedback loops is internal dogfooding and learning how our own internal teams such as engineering, sales engineering and customer success, experience the newest feature. However, we know that that approach can be biased.

The Sumo query language can be a source of joy and pain at times. Achieving mastery is no easy path and all who set on this path may suffer greatly until they see the light. The Log Operators Cheat Sheet is a valuable resource to learn syntax and semantics of the individual operators, but the bigger questions become “how can we tie them together” and “how can we write query language that matters?”