Well, first of all, it’s fun, or I wouldn’t be doing it. I work with some intelligent, talented people, like Carlie Fairchild, publisher at LJ, and Katherine Druckman, our Webmistress. My job description as one of the LJ bloggers is to “write about whatever you want, as long as it is Linux related”. That’s pretty much the ideal job description for somebody like me who has been doing Linux full-time since shortly after Slackware first came out in 1993. I feel lucky to be writing for Linux Journal, which is currently celebrating its 16th year of publication, and is the original magazine of the global Linux community.
The Linux Journal audience runs the gamut from “Linux Wizard” to “Neophyte”. Given the self-selection process of the LJ readership, most of the people who come here, either directly to www.linuxjournal.com , or via to the Linux Journal Facebook page are genuinely interested in Linux.
Sometimes you feel like a lightening rod. One does encounter the occasional flame comment on a posting. But, I’m used to that. I ran the LANL, The Real Story blog from December, 2004 through July, 2005, and I can tell you that nobody on Linux Journal can flame like some of those unhappy campers who used to post on the LTRS blog. One of my previous LJ posts was even dedicated to the art of flaming, and included a couple of hints on how to fan the flames if the fire seemed in danger of dying out.
Usually, though, the LJ readership is genuinely interested in the material being covered in the articles, and the comments are positive, or at least fully engaged regarding the topic:
Why did you suggest Amarok? Rhythmbox is far superior. Any idiot knows that!
It’s a pleasure to see such enthusiasm. Seriously. Apathy is no fun at all.
Another thing I enjoy about writing here is that the LJ interactions provide constant exposure to what’s going on in the Linux world. Linux is big. Rarely a day goes by that I don’t learn something new. For example, today I heard about the Clementine project: Amarok 1.4.x forked and ported to Qt4. Amarok has been my favorite music player for a while, so I’ve made a note to myself to check out Clementine.
As Carlie told me when I hired on, “Do it as long as it’s fun. If it stops being fun, stop doing it.”
Which is exactly what I intend to do.
|Non-Linux FOSS: libnotify, OS X Style||Jun 18, 2013|
|Containers—Not Virtual Machines—Are the Future Cloud||Jun 17, 2013|
|Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer||Jun 12, 2013|
|Weechat, Irssi's Little Brother||Jun 11, 2013|
|One Tail Just Isn't Enough||Jun 07, 2013|
|Introduction to MapReduce with Hadoop on Linux||Jun 05, 2013|
- Containers—Not Virtual Machines—Are the Future Cloud
- Non-Linux FOSS: libnotify, OS X Style
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Linux Systems Administrator
- RSS Feeds
- Introduction to MapReduce with Hadoop on Linux
- Validate an E-Mail Address with PHP, the Right Way
- Weechat, Irssi's Little Brother
- Tech Tip: Really Simple HTTP Server with Python
- New Products
- Poul-Henning Kamp: welcome to
1 hour 53 sec ago
- This has already been done
1 hour 1 min ago
- Reply to comment | Linux Journal
1 hour 47 min ago
- Welcome to 1998
2 hours 35 min ago
- notifier shortcomings
2 hours 59 min ago
4 hours 36 min ago
- Android User
4 hours 37 min ago
- Reply to comment | Linux Journal
6 hours 30 min ago
9 hours 20 min ago
- This is a good post. This
14 hours 33 min ago
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?