Increasingly, the speed and scale of a business can be measured by the resilience and performance of its applications. That’s why organizations are opting to modernize legacy applications by rewriting them using cloud-native tools and platforms. A Gartner study found that by 2025, cloud-native platforms will be the foundation for more than 95% of new digital initiatives, compared to less than 40% in 2021.

Effective log management is a fundamental aspect of maintaining and troubleshooting today's complex systems and applications. The sheer volume of data generated by various software and hardware components can make it challenging to identify and resolve issues in a timely manner. Open-source log management tools offer a cost-efficient and customizable approach for collecting, analyzing, and visualizing log data.

This article is the third of a four-part series of articles about Elasticsearch monitoring. In the first article, we put together an Elasticsearch guide, covering how Elasticsearch works and why the setup and tuning of Elasticsearch requires a good knowledge of configuration options and performance metrics.

Observability has become one of the most important areas of your application and infrastructure landscape, and the market has an abundance of tools available that seem to do what you need. In reality, however, most products - especially leading open source tools - were created to solve a single problem extremely well, and have added additional supporting functionality to become a more robust solution; but the non-core functionality is rarely best of breed. Examples of these are Prometheus and Grafana.

Let’s say you have a script that works when run in an interactive session, but does not produce expected results when run from cron. What could be the problem? Some potential culprits include: Or it could be something else. How to troubleshoot this then, and where to start? Instead of trying fixes at random, I prefer to start by looking at logs.