If you're new to working with data, you might have heard of databases and data warehouses. But do you know what sets them apart? Knowing the differences between data warehouses and databases can clear up a lot of confusion for many people, especially with the volume of data we have these days. In this blog post, I'll discuss the differences between these two types of data systems. I'll also provide some examples to help illustrate the points made.

Learn how to manage and view systemctl logs in Linux with this guide, covering essential commands and best practices for troubleshooting.

Master Python logging with structlog! Learn how structured logs improve debugging, observability, and performance in your apps.

When it comes to logging tools, organizations often face a classic tech dilemma: build vs. buy. Should you invest in a robust, ready-to-use SaaS solution like Sumo Logic or dive into the customization rabbit hole with a PaaS option like Elastic? It's a debate as old as time—well, as old as software, anyway. Let's break it down in a way that actually makes sense, and hopefully, it’ll spark less drama than the pineapple-on-pizza debate.

Today’s dynamic multi-cloud ecosystems receive logs from countless sources. Relying on custom collectors and integrations can lead to tool sprawl, pipeline breakdowns, and time-consuming maintenance. Enter Sumo Logic’s Universal Connector, your streamlined solution for collecting logs from any source. With seamless API integrations, Universal Connector simplifies log collection and eliminates the overhead of building custom pipelines.

Managing log files effectively is crucial for ensuring a well-performing, reliable system. Logrotate, a popular log management tool, provides a flexible way to automatically rotate, compress, and remove old logs. Among its many configurations, two common approaches to trigger log rotation are size-based and time-based rotation. In this blog, we will explore the differences between these methods, compare their use cases, and help you decide which approach (or combination) suits your needs best.

An audit and error trail is one of the core pillars of a well-designed software application, regardless of the programming language used to build it. This trail typically comes in the form of logging. When your application produces useful, rich logs, you are better equipped to successfully maintain a production-grade system and troubleshoot any issues that might arise. When it comes to distributed Python applications, having correlated logs for each system is important for debugging.