Over the years, natural language processing, in the world of search, went from interesting detail to a must have, especially in areas such as e-commerce. Engineers started incorporating classification, synonym generation, named entity recognition and much more into their search systems giving users better search results and in some cases leading to more revenue.
v6.0 Stable released! GrafanaCon LA is underway! Check out the live stream on the Grafana youtube channel. I am proud to announce that we are releasing Grafana v6.0 stable today. Before every major release I feel super excited about the progress that has been made and with this release, this is especially true.
In order to analyze logs efficiently, they must be structured effectively. Often, logs from different sources label data fields differently and/or provide data that’s completely unstructured. The problem is that both types of data need to be structured appropriately in order to key in on particular elements within the log data, such as: Monitoring on source address, Applying rules associated with user names, and Creating alerts for destination addresses.
When logging applications to a centralized location like LogDNA, developers have two options: using a logging agent or using a logging library. Both approaches will get your logs to their destination, but choosing one over the other can have a significant impact on the design of your applications and infrastructure. In this article, we’ll explain the difference between logging via agents and logging via libraries, and which approach works best in modern architectures.
