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.
A few weeks back, eG Innovations collaborated with David Wilkinson and conducted a webinar on the topic “Is Citrix Cloud Enterprise Ready? Best Practices to get the Most Out of Citrix Cloud Deployments.” Citrix Cloud implementations are growing in the industry today, and as organizations begin evaluating their cloud options, Citrix administration teams want to understand how Citrix Cloud will sustain, scale and be supported in lieu of on-premises Citrix deployments.
In a world where everything comes down to moments of truth, teams must respond to issues and opportunities in seconds. Rising customer expectations demand real-time response, and effective DevOps and ITOps shouldn’t just be tied to laptops and desks.
April 7, 1969. This date marks the beginning of the Internet Engineering Task Force (IETF) Request for Comments (RFC), which in its RFC 1 defined the Interface Message Processor (IMP) and laid the foundation for the computer world as we know it. What place do free server monitoring tools occupy in all of this?
When we introduced ‘remote actions’ in 2012, i.e. the execution of IT automation tasks from your smartphone, we aimed at empowering the mobile (IT) workforce of the future. We aimed at relieving IT people from being bound to their desks, notebooks and PCs.
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.
