Logging is a data collection method that stores pieces of information about the events that take place in a computer system. There are different kinds of log files based on the kind of information they contain, the events that trigger log creation, and several other factors. This post focuses on log files created by the three main operating systems--Windows, Mac, and Linux, and on the main differences in the ways to access and read log files for each OS.

At LogDNA, we’re all about speed. We need to ingest, parse, index, and archive several terabytes of data per second. To reach these speeds, we need to find and implement innovative solutions for optimizing all steps of our pipeline, especially when it comes to storing data.

My career as a software engineer started in 2007 at Purdue University. I was working in the Linux kernel and researching how data was shuffled between the kernel and the user application layers. This was happening in huge clusters of machines that all talked to each other using OpenMPI — how supercomputers, like those at Los Alamos National Labs, operate to perform their enormous calculations around meteorology, physics, chemistry, etc.

To retain a competitive advantage in today’s fast-paced digital market, organizations need to focus on their application stack. Error-prone or bug-ridden applications may deter potential customers from visiting a site again. Organizations must monitor application performance at every level to ensure optimal performance of business applications.

Although AWS sometimes feels like magic, it’s just software that controls capacity and allocation on their previously provisioned hardware. RDS is one of the services that can feel especially magic, because of the general difficulty and drudgery required to set up and manage a production database. In a matter of minutes, anyone can have a production database, complete with replication, automatic failover, backup schedules, and point-in-time recovery.

As engineers, we are constantly bombarded with complex machine data. In order to better monitor and troubleshoot our environments, we must analyze and gain an accurate understanding of this data to best evaluate how our systems are performing and combat any issues that may occur. Yet, sifting through this data while managing the added intricacies of serverless architecture, microservices, containers, and other technologies make our jobs increasingly difficult to navigate.

At Atlassian, we want to give our customers choice in how they deploy Atlassian products: in the cloud, managed by Atlassian, or on the infrastructure of your choice with Server or Data Center. Many of our on-premise customers begin their Atlassian journey with our server products, with the ability to download our software and install it on a single server that you control. This gets you up and running quickly.

Statuspage customers logged more than 194 years of collective incidents in 2018. That’s a whopping 87% increase from the 104 years logged in 2017, and we aren’t even through December yet.